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This resource provides information on installation, configuration, running, troubleshooting and analysis algorithms for the following software:
DRAGEN TruSight Oncology 500 Analysis Software on Illumina Connected Analytics (ICA) v2.5.2
DRAGEN TruSight Oncology 500 Analysis Software v2.5.3 (for standalone DRAGEN server)
DRAGEN TruSight Oncology 500 Analysis Software v2.5.4 (for standalone DRAGEN server)
The content is applicable to all 3 software versions unless otherwise specified. The content related to setting up and running the analysis on ICA is only relevant to v2.5.2.
DRAGEN TruSight™ Oncology 500 Analysis Software supports data analysis for TruSight Oncology 500 Assay and TruSight Oncology 500 High-Throughput Assay, both Research Use Only (RUO).
The software provides local and cloud analysis for DNA and RNA libraries generated from formalin-fixed, paraffin-embedded (FFPE) tissue samples. The assays and the software are optimized to provide high sensitivity and specificity for low-frequency somatic variants across coding exons and additional regions of biological relevance in 523 genes for DNA biomarkers.
In addition, this software supports data analysis for TruSight Oncology 500 HRD (RUO), an optional add-on kit to TruSight Oncology 500, that enables detection of homologous recombination deficiency (HRD) through assessment of a genomic instability score (GIS).
TruSight Oncology 500 HRD is not available in Japan
Single nucleotide variants (SNVs)
Insertions
Deletions
Copy number variants (CNVs)
Tumor mutational burden (TMB)
Microsatellite instability (MSI)
Fusions
Splice variants
Absolute copy numbers (ACN)*
Loss of heterozygosity (LOH)*
Tumor fraction*
Ploidy*
Details of the regions covered by the assays can be found in the assay manifest file. Contact your local Illumina representative for more information.
*Requires TruSight Oncology 500 HRD add-on kit
Variant reporting by DRAGEN TruSight™ Oncology 500 Analysis Software is limited by a manifest file and a . The manifest file excludes regions where the probe set does not effectively capture targets, and the block list file excludes specific positions from variant calling. TSO 500 assay probes target at least 97% of the CDS of 474 genes. Please contact your local Illumina representative for more information if needed.
Local analysis is available using a standalone DRAGEN server. The software on the standalone DRAGEN server allows for analysis on a single DRAGEN server or splitting across multiple servers.
Cloud analysis is available on Illumina Connected Analytics with auto-launch (from BCL) or manual launch (from BCLs and FASTQs), see exceptions for NextSeq 1000/2000 and NovaSeq X in the instrument compatibility tabel below.
DRAGEN TruSight Oncology 500 analysis software v2.5.x is compatible with data generated on the Illumina instruments as summarized in the table below.
*Among v2.5.x, only DRAGEN TruSight Oncology 500 analysis software v2.5.2 is supported on ICA
**For the data generated with NextSeq 1000/2000 and NovaSeq X, analysis can be started only from FASTQs (not from BCLs). Only manual launch is available for ICA.
Exon-level CNVs
Multinucleotide variants (MNVs)
Genomic Instability Score (GIS Score) *
NovaSeq 6000
Yes
Yes
N/A
N/A
NovaSeq 6000Dx (RUO mode)
Yes
Yes
No
N/A
NextSeq 1000/2000
Yes**
Yes**
N/A
No
NovaSeq X
Yes**
Yes**
N/A
No
NextSeq 550Dx (RUO mode)
Yes
Yes
No
N/A
NextSeq 500/550
Yes
Yes
N/A
N/A
The block list represents high noise regions in the panel where false positive variant calls are likely produced. As a result, all positions in the gVCF are marked as Filter=excluded_regions to indicate variant call results are not reliable in such regions.
The block list includes the following genes:
HLA A
HLA B
HLA C
KMT2B
KMT2C
KMT2D
chrY
Any position with VAF 1% occurrence in six or more of the 60 baseline samples.
Sequencing data stored in BCL format are demultiplexed through a process that uses the index sequences unique to each sample to assign clusters to the library from which they originated. Each cluster contains two indexes (i7 and i5 sequences, one at each end of the library fragment). The combination of those index sequences are used to demultiplex the pooled libraries.
After demultiplexing, this process generates FASTQ files, which contain the sequencing reads for each individual sample library and the associated quality scores for each base call, excluding reads from any clusters that did not pass filter.
Sample Sheet templates for TSO 500 v2.5.x standalone DRAGEN server and ICA manual launch analysis can be found in the table below. For auto-launch compatible sample sheets, use BaseSpace Run Planner.
DRAGEN TSO 500 analysis software is compatible with several instruments and assay workflows (standard, XP), each of which have implications for the sample sheet.
Sample sheet templates contain all required fields, including index sequences in the proper orientation for all indexes from a given library prep kit. The templates are provided as a starting point for creating a sample sheet manually when launching analysis on a standalone DRAGEN server or on ICA using manual launch.
For interactive run planning or to create a sample sheet for ICA Auto-launch, use BaseSpace Run Planner to create valid sample sheets for either local or cloud analysis. To set up a run in BaseSpace run planner, refer to Sample Sheet Creation in BaseSpace Run Planner.
Users can visit the section to learn additional details on required fields and values as they fill-in their sample information. Use the lookup table below to select and download the sample sheet template that matches your instrument, assay, and workflow configuration:
*Lane numbers cannot exceed what is supported by the flow cell in use.
A sample sheet is required for each analysis with DRAGEN TruSight Oncology 500 Analysis Software. A sample sheet is a comma-separated value (*.csv) file format used by Illumina instruments, platforms, and analysis pipelines to store settings and data for sequencing and analysis. The DRAGEN TruSight Oncology 500 Analysis Software is compatible with the sample sheet v2. For general information on the sample sheet v2, refer to Illumina Connected Software - Sample Sheet.
The sample sheet includes a list of samples and their index sequences, along with additional information required to run DRAGEN TruSight Oncology 500 Analysis Software. For example, DNA samples with the TruSight Oncology 500 HRD add-on probes must be indicated in the Sample Feature column of the sample sheet. Appropriate index adapter sequences are determined by the assay used to perform analysis.
When running analysis on a standalone DRAGEN server or on ICA, a valid sample sheet can be created by:
BaseSpace Run Planner (preferred), see for details
Downloading and modifying a sample sheet template following the requirements, see for details
The run set up section of this guide includes specific instructions to plan a run and set up a valid sample sheet for each deployment of DRAGEN TruSight Oncology 500 Analysis Software.
Illumina Connected Analytics (ICA) subscription includes access to DRAGEN TruSight Oncology 500 Analysis Software. To get started, you need:
An ICA account with a valid subscription. Refer to the Software Registration page for information on how to register ICA subscription and iCredits.
A positive balance of iCredits for data storage. Please refer to the and for more information.
The table provides guidance on the storage needs and associated ICA storage size settings.
DRAGEN TruSight Oncology 500 Analysis Software can be used to run a subset of samples on different DRAGEN servers to decrease overall processing time. This is possible using a three stage process called scatter/gather, which consists of demultiplexing, analysis, and result gathering.
The first stage is demultiplexing. Demultiplexing runs once on the entire run folder, generates FASTQ files for each sample in the run, and then separates sample files into respective folders. Once complete, note the output directory containing the sample directories holding the FASTQ files.
The process for scattering the analysis on multiple DRAGEN servers is as follows:
Determine how many DRAGEN servers are available to run.
Refer to for more information.
Each sample is downsampled to 30 million RNA reads. This number represents the total number of single reads (eg, R1 + R2, from all lanes). When using the recommended sequencing configurations or plexity, the samples can have fewer reads than the downsampling limit. In these cases, the FASTQ files are left as-is.
Run demultiplexing on a single DRAGEN server.
Moving or modifying files during an analysis may cause the analysis to fail or provide incorrect results.
To sequence runs on multiple DRAGEN servers using the NovaSeq 6000 XP workflow, modify the sample sheet to include a subset of the lanes. For example, on an S2 flowcell, create two modified sample sheets with one containing the samples from lane 1 and the other from lane 2. This allows only the sample sheet to be modified instead of copying files between servers. This strategy would use the start from Run Folder commands without the --demultiplexOnly option. The entire run folder would need to be copied to each analysis server as demultiplexing is performed once per server.
Transfer the FASTQ folder output from the original DRAGEN server to additional servers.
Logs_Intermediates/FastqGeneration.
Run analysis software using the --fastqFolder option on both the original and additional DRAGEN servers.
Option 1 Copy the original SampleSheet.csv to each server. Then provide a subsetted list to the Bash script on each DRAGEN server with the intended samples/pairs to run.
Option 2 Copy and modify the SampleSheet.csv to each DRAGEN server to only contain the list of samples/pairs to run.
The software verifies that all samples in the sample sheet are contained within the FASTQ folders unless the --sampleOrPairIDs command-line option is present in the analysis launch. Failure to account for these checks results in an error.
Copy the results from demultiplexing and each analysis run onto a single server, and then generate the final /Results directory, which contains the aggregated results. Enter the --gather command followed by the output directories of the demultiplexing step and each individual analysis run.
Demultiplexing
DRAGEN_TSO500.sh --resourcesFolder /staging/illumina/DRAGEN_TSO500/resources --hashtableFolder /staging/illumina/DRAGEN_TSO500/ref_hashtable --runFolder /staging/{RunFolderName} --analysisFolder /staging/{DemultiplexAnalysisFolderName} --demultiplexOnly --sampleSheet /staging/illumina/{SampleSheetName}
Analysis
(one server)
DRAGEN_TSO500.sh --resourcesFolder /staging/illumina/DRAGEN_TSO500/resources --hashtableFolder /staging/illumina/DRAGEN_TSO500/ref_hashtable --fastqFolder /staging/{DemultiplexAnalysisFolderName}/Logs_Intermediates/FastqGeneration/ --analysisFolder /staging/{Node1AnalysisFolderName} --sampleSheet /staging/illumina/{SampleSheetName} --sampleOrPairIDs Pair_1,Pair_2
Analysis (additional servers)
DRAGEN_TSO500.sh --resourcesFolder /staging/illumina/DRAGEN_TSO500/resources --hashtableFolder /staging/illumina/DRAGEN_TSO500/ref_hashtable --fastqFolder /staging/{DemultiplexAnalysisFolderName}/Logs_Intermediates/FastqGeneration/ --analysisFolder /staging/{Node1AnalysisFolderName} --sampleSheet /staging/illumina/{SampleSheetName} --sampleOrPairIDs Pair_3
Gather
DRAGEN_TSO500.sh --analysisFolder /Gathered_Results --resourcesFolder staging/illumina/DRAGEN_TSO500/resources --runFolder /staging/{RunFolderName}/--sampleSheet /staging/illumina/{SampleSheetName} --gather /Demultiplex_Output /Node1_Output /Node2_Output
Small variant calling
TMB
MSI
CNV
[HRD] GIS
RNA library QC metrics
Run QC metrics, analysis status, and contamination
This TSV file also includes expanded DNA library QC metrics per sample, based on total reads, collapsed reads, chimeric reads, and on-target reads. Analysis using RNA samples also produces RNA library QC metrics and expanded RNA library QC metrics per sample based on total reads and coverage.
The MetricsOutput.tsv file is a final combined metrics report with sample status, key analysis metrics, and metadata. Sample metrics within the report include suggested lower specification limits (LSL) and upper specification limits (USL) for each sample in the run.
For troubleshooting information, refer to Troubleshooting
Reads are trimmed to 76 base pairs for further processing.
RNA alignment and fusion detection uses trimmed reads in FASTQ format as input. The outputs include a BAM file that contains duplicate-marked read alignments, an SJ.out.tab file that contains unannotated splice junctions, and a CSV file that contains fusion candidates.
DRAGEN aligns RNA reads in a transcript-aware mode using the human hg19 genome containing unplaced contigs (ie, chrUn_gl regions) and uses GENCODEv19 transcript annotations to identify splice sites. DRAGEN identifies and marks duplicate read alignments using start and end coordinates of alignments, which are adjusted for soft clipped reads.
Fusion and splice variant calling only use deduped fragments to score variants. DRAGEN identifies fusion candidates using chimeric split read alignments (pairs of primary and supplementary alignments) against multiple genes. DRAGEN scores and filters reads based on the various features of each candidate such as the number of supporting reads, mapping quality of supporting reads, and sequence homology between parent genes.
The DRAGEN RNA Fusion caller identifies gene fusions by searching for chimeric reads spanning two distinct parent genes. Based on the chimeric reads, DRAGEN first creates a list of fusion candidates, then scores the candidates to report the list of high confidence fusion calls from the candidate pool.
DRAGEN RNA Fusion caller performs the following steps:
Generates fusion candidate generation based on split read alignment.
Recruits additional evidence from fusion supporting discordant read pairs and soft-clipped reads.
Computes fusion candidate features such as gene coverage, read mapping quality, alternate allele frequency, gene homology, alignment anchor length, and breakpoint distance from exon boundary.
Scores and ranks the fusion candidates using a logistic regression model.
Selects a final list of fusion calls based on score and other filters including number of supporting reads, unique read alignment count, read through transcripts, and fusions matching the enriched regions.
RNA splice variant calling is performed for RNA sample libraries. Candidate splice variants (junctions) from RNA Alignment are compared against a database of known transcripts and a splice variant baseline of non-tumor junctions generated from a set of normal FFPE samples from different tissue types. Any splice variants that match the database or baseline are filtered out unless they are in a set of junctions with known oncological function. If there is sufficient read support, the candidate splice variant is kept. This process also identifies candidate RNA fusions.
Fusions identified during RNA fusion calling are merged with fusions from proximal genes identified during RNA splice variant calling. These are then annotated with gene symbols or names with respect to a static database of transcripts (GENCODE Release 19). The result of this process is a set of fusion calls that are eligible for reporting
The Illumina Annotation Engine annotates detected RNA splice variant calls with transcript-level changes (eg, affected exons in the transcript of a gene) with respect to RefSeq. This RefSeq database is the same RefSeq database used by the small variant annotation process.
Manual launch—Initiate DRAGEN TSO 500 analysis on ICA using the run files and sample sheet files in the project.
For the data generated by NextSeq 1000/2000 and NextSeq X, only manual option for launching analysis on ICA is available. The analysis can only start from FASTQs files.
For more information about using ICA or BaseSpace Sequence Hub, refer to the following support pages on the Illumina support site.
NovaSeq 6000/6000Dx (RUO) S4 Flow Cell
4,300
Large
NovaSeq X 1.5B
2,000
Large
NovaSeq X 10B
4,300
Large
NovaSeq X 25B
8,400
XLarge
NextSeq 1000/2000
350
Large
NextSeq 500/550/550Dx (RUO) HO flow cell
350
Large
NovaSeq 6000/6000Dx (RUO) SP Flow Cell
500
Large
NovaSeq 6000/6000Dx (RUO) S1 Flow Cell
1100
Large
NovaSeq 6000/6000Dx (RUO) S2 Flow Cell
2,500
Large
TSO500 + HRD
NovaSeq 6000Dx (in RUO mode)
Standard
TSO500 HT
NovaSeq 6000Dx (in RUO mode)
Standard
TSO500 HT
NovaSeq 6000Dx (in RUO mode)
XP*
TSO500
NextSeq 550
Standard
TSO500 + HRD
NextSeq 550
Standard
TSO500 + HRD
NovaSeq 6000
Standard
DRAGEN TSO 500 Analysis Software has optional and required fields that are required in addition to general sample sheet requirements. Follow the steps below to create a valid samplesheet.
The following sample sheet requirements describe required and optional fields for DRAGEN TSO 500 Analysis Software. Depending on the deployment (standalone DRAGEN server, ICA with auto-launch, ICA with manual launch), certain sections and required values can deviate from the standard requirements. These deviations are noted in the information below.
The analysis fails if the sample sheet requirements are not met.
Use the following steps to create a valid sample sheet.
Download the sample sheet v2 template that matches the instrument & assay run.
In the BCL Convert Settings section, enter the following required parameters:
In the BCL Convert Data section, enter the following parameters for each sample.
In the TSO 500 Data section, enter the following parameters:
TSO 500 Data Section header changes depending on the deployment:
Standalone DRAGEN Server and ICA with Manual Launch: TSO500S_Data
ICA with Auto-launch:
To ensure a successful analysis, follow these guidelines:
Avoid any blank lines at the end of the sample sheet; these can cause the analysis to fail.
When running local analysis using the command line save the sample sheet in the sequencing run folder with the default name SampleSheet.csv, or choose a different name and specify the path in the command-line options.
Refer to the following requirements to create sample sheets for running the analysis on ICA with Auto-launch. For sample sheet requirements common between deployments see . Samples sheets can be created using BaseSpace Run Planning Tool or manually by downloading and editing a sample sheet template
Refer to for this section's requirements.
The installation script for DRAGEN TruSight Oncology 500 Analysis Software installs the following software and dependencies:
DRAGEN TruSight Oncology 500 Analysis Software itself
DRAGEN Software if a compatible version is not present
Docker software if a compatible version is not present
A script required to generate DRAGEN genome hash table
A script to check that DRAGEN TruSight Oncology 500 Analysis Software is installed properly
DRAGEN server v3 or v4
Network-attached storage (NAS) with enabled mkfifo if performing analysis for the TruSight Oncology 500 High-Throughput assay
The following software is required to successfully install DRAGEN TSO 500 v2.5.4:
Linux CentOS 7.9 operating system (or later) or Oracle Linux 8 (or later), one of which is provided on the server. Oracle Linux 8 is recommended.
Docker Software, see table below for minimum version needed. If sufficient Docker software is not present on the server, the TSO 500 installer will install compatible Docker software.
DRAGEN Server Software*, see table below for minimum version needed as the host version on the server. If sufficient DRAGEN software is not present on the server, the TSO 500 installer will install compatible DRAGEN software.
*The DRAGEN Server Software version may be higher than the DRAGEN version used by the DRAGEN TSO 500 v2.5.4 pipeline (DRAGEN v3.10.16), which is provided inside the DRAGEN TSO 500 docker image.
TSOCombined license
TSO500_HRD license (to analyze data generated with the TSO 500 HRD add-on kit)
TSOCombined license has been pre-installed to DRAGEN servers in manufacturing since August 2022 and TSO500_HRD since February 2025 and additionally distributed to DRAGEN servers connected online. To generate a list of installed DRAGEN server licenses, run the following command: /opt/edico/bin/dragen_lic. If a license is not installed, contact Illumina Customer Care at for the license.
Illumina recommends logging in as root user for installation, but as a non-root user for running TSO 500 analysis.
A non-root user must be a member of the Docker group to run Docker. For more information on Docker permission requirements and alternatives to running as root, refer to the Docker documentation available on the .
Installing and uninstalling DRAGEN TruSight Oncology 500 Analysis Software and running the system check requires root privileges.
Run DRAGEN TruSight Oncology 500 Analysis Software without being logged in as a root user. Running the DRAGEN TruSight Oncology 500 Analysis Software as root is not required or recommended.
DRAGEN TSO 500 Analysis Software v2.5.4 is multi-version compatible. Multi-version compatibility refers to ability to be installed on a single DRAGEN server with software running a different version of DRAGEN software. For example, multi-version compatible pipelines running DRAGEN v4.3.6 can be co-installed on a server alongside DRAGEN TSO 500 pipelines running DRAGEN v3.10.17. For more details on DRAGEN multi-version compatibility, please visit .
Software versions without multi-version compatibility referred to as single-version compatible. DRAGEN TSO 500 Analysis Software v2.5.4 will disrupt installations of single-version compatible software from the DRAGEN server. To uninstall a previous version of DRAGEN TSO 500 Analysis Software, refer to the respective guide.
Compatibility of software for co-installation with DRAGEN TSO 500 v2.5.4 on a DRAGEN server is summarized in the table below:
*DRAGEN TSO 500 Analysis Software v2.5.4 can run on a single server with another multi-version compatible DRAGEN TSO 500 Analysis Software, e.g. DRAGEN TSO 500 v2.6.1, and should be installed before v2.6.1. DRAGEN TSO 500 Analysis Software v2.5.4 can be co-installed with multi-version compatible DRAGEN TSO 500 ctDNA Analysis Software or other DRAGEN pipelines with any order of installation.
**For example, DRAGEN Enrichment, DRAGEN Germline, DRAGEN WGS Heme v1.0.0 and others. Order of installation does not matter.
As a root user, perform the following steps to install DRAGEN TruSight Oncology 500 Analysis Software v2.5.4:
Contact Illumina Customer Care at to obtain the DRAGEN TruSight Oncology 500 Analysis Software installer package.
Download the installation package provided in the email from Illumina. The link expires after 7 days.
It is recommended to use a command line tool like wget or curl to download the file rather than pasting the link into the web browser bar. For example:
curl -o {filename} "{link}"
wget -O {filename} '{link}'
Where the file name is the installation script file name, and the link is provided by Illumina Customer Care.
Make sure no other analysis is being performed. Installing the software while performing other analyses prevent the installer process from proceeding
Copy the install script to the /staging directory to store the script in the directory.
Installation Script: install_DRAGEN_TSO500-2.5.4.run
MD5sum: sha256:0d871d8b93b4e535c0c1b5614c180fdb815f80764274279881c8a25a4e153160
Use the following command to update the run script permission:
chmod +x /staging/install_DRAGEN_TSO500-2.5.4.run
Use the following command to run the installation script (run time ~ 20 mins):
For Docker, use the following command:
sudo TMPDIR=/staging /staging/install_DRAGEN_TSO500-2.5.4.run. The script installs compatible DRAGEN software and removes any previously installed versions.
Review license requirements, how to check which licenses are installed and how to receive a license in . Licenses can be installed before or after DRAGEN TSO 500 software installation.
To install a license (TSOCombined and/or TSO500_HRD) on a DRAGEN server connected to the internet:
Confirm that the server is connected to the Internet, example: ping www.illumina.com
Run the following command: /usr/bin/dragen_lic -i auto
To install a license (TSOCombined and/or TSO500_HRD) on a DRAGEN server not connected to the internet:
Contact Customer Care at to request a license file for each of the needed licenses
Download and save the license file(s) to a location that is accessible from the DRAGEN server
For each license file, run the command, where <license file received> is the absolute path to the license file: sudo /usr/bin/dragen_lic -i /tmp/<license file received>.bin
To check the success of license installation, run: /usr/bin/dragen_lic. Installed licenses should be in the list.
After installation is complete, make sure the system functions properly by running the following command: /usr/local/bin/check_DRAGEN_TSO500-2.5.4.sh
The script checks that:
All required services are running
Proper Docker image is installed
DRAGEN TSO 500 Analysis Software can successfully process a test data set
The system check script runs for approximately 25 minutes. If the script prints a failure message, contact Illumina Technical Support and provide the /staging/check_DRAGEN_TSO500_<timestamp>.tgz output file.
If using MacOS to connect to a server, an error can occur if the local settings are not in English. To resolve the error, disable the ability to set environment variables automatically in Terminal settings.
The DRAGEN TSO 500 Analysis Software installation includes an uninstall script called uninstall_DRAGEN_TSO500-2.5.4.sh, which is located in /usr/local/bin.
Executing the uninstall script removes the following assets:
All DRAGEN TSO 500 Analysis Software related scripts located in /usr/local/bin
Resources found in /staging/illumina/DRAGEN_TSO500
The dragen_tso500:2.5.4: Docker image
To uninstall the DRAGEN TSO 500 Analysis Software, run the following command as a root user:
uninstall_DRAGEN_TSO500-2.5.4.sh
You are not required to uninstall Docker or DRAGEN software. To remove Docker, review the install instructions for your operating system in the Docker documentation.
The software processes sequencing data to perform quality control, detect variants, determine tumor mutational burden (TMB), microsatellite instability (MSI) status, and genomic instability score (GIS), and report results. The following sections describe the analysis methods used in DRAGEN TruSight Oncology 500 Analysis Software.
DRAGEN TruSight Oncology 500 Analysis Software uses the following workflows to analyze sequencing data.
FASTQ Generation
DNA Analysis
DNA Alignment and Realignment
Read Collapsing
Indel Realignment and Read Stitching
Small Variant Calling
RNA Analysis
Downsampling
Read Trimming
Alignment
Quality Control
Run QC
DNA Sample QC
RNA Sample QC
The Illumina DRAGEN TruSight Oncology 500 Analysis Software allows for analysis of sequencing data generated from the TruSight Oncology 500 HRD assay. When HRD samples are analyzed new results and metrics are included in the CombinedVariantOutput and MetricsOutput files respectively. The following tables detail how these scores and QC metrics are derived.
The contamination score evaluates presence of sample-to-sample contamination. The algorithm uses common germline SNPs in the homozygous state expected to have variant allele frequencies (VAF) at 0% and 100%. In contaminated samples, the VAFs shift away from the expected values allowing the detection of sample-to-sample contamination.
The contamination score can detect sample-to-sample contamination greater than or equal to 2% (more than 2% of DNA input is coming from the contaminant)
RNA expanded metrics are provided for information only. They can be informative for troubleshooting but are provided without explicit specification limits and are not directly used for sample quality control. For additional guidance, contact Illumina Technical Support.
Small Variant Filtering
Copy Number Variant (CNV) Calling
Phased Variant Calling
Variant Merging
Annotation
Tumor Mutational Burden (TMB) Scoring
Microsatellite Instability (MSI) Status
Contamination Detection
Duplicate Marking
Fusion Calling
RNA Fusion Filtering
Splice Variant Calling
Annotation
Fusion Merging
MinimumTrimmedReadLength
Required
Enter 35. Reads with a length trimmed below this point are masked.
MaskShortReads
Required
Enter 35. Reads with a length trimmed below this point are masked.
Cloud_TSO500S_DataSample_Description
Not Required
Sample description must meet the following requirements: - 1–50 characters. - Alphanumeric characters with underscores, dashes and spaces. If you enter a underscore, dash, or space, enter an alphanumeric character before and after. eg, Solid-FFPE_213.
IndexAdapterKitName
Not Required
The Index Adapter Kit used.
SoftwareVersion
Required
The DRAGEN component software version.
For DRAGEN TSO 500 v2.5.3 and v2.5.4 specify 3.10.16.
AdapterRead1
Required
If using 8 bp indexes starting with UP or CP (used with TSO 500): AGATCGGAAGAGCACACGTCTGAACTCCAGTCA If using 10 bp indexes with UDP (used with TSO 500 HT): CTGTCTCTTATACACATCTCCGAGCCCACGAGAC Analysis fails if the incorrect adapter sequences are used
AdapterRead2
Required
If using 8 bp indexes starting with UP or CP (used with TSO 500): AGATCGGAAGAGCGTCGTGTAGGGAAAGAGTGT If using 10 bp indexes with UDP (used with TSO 500 HT): CTGTCTCTTATACACATCTGACGCTGCCGACGA Analysis fails if the incorrect adapter sequences are used
AdapterBehavior
Required
Sample_ID
Required
Must match a Sample_ID listed in the TSO 500 Data section.
Index
Required
Index 1 sequence valid for Index_ID assigned to matching Sample_ID in the TSO 500 Data section.
Index2
Required
Index 2 sequence valid for Index_ID assigned to matching Sample_ID in the TSO 500 Data section.
Lane
Only for NovaSeq 6000 XP, NovaSeq 6000Dx, or NovaSeq X workflows
Sample_ID
Required
The unique ID to identify a sample. The sample ID is included in the output file names. Sample IDs are not case sensitive. Sample IDs must have the following characteristics:
- Unique for the run.
- 1–40 characters.
- No spaces.
- Alphanumeric characters with underscores and dashes. If you use an underscore or dash, enter an alphanumeric character before and after the underscore or dash. eg, Sample1-T5B1_022515.
- Cannot be called all, default, none, unknown, undetermined, stats, or reports.
- Must match a Sample_ID listed in the TSO 500 Data section.
- Illumina recommends that the sample ID be based on the pair ID. Example: <Pair_ID>-DNA,<Pair_ID>-RNA.
- Each sample must have a unique combination of Lane (if applicable), sample ID, and index ID or the analysis will fail.
Sample_Type
Required
Enter DNA or RNA.
For HRD samples, this parameter must be DNA.
Pair_ID
Required
A unique ID that links DNA and RNA from the same biological sample from the same individual. Pair ID shares, at most, one DNA and one RNA sample per run. eg, if a Sample_ID is TestSample1-DNA for DNA and TestSample1-RNA for RNA, the Pair_ID TestSample1 will link these samples that are on different rows in the sample sheet together.
If the pair ID is associated with more than one DNA or RNA sample, the analysis fails.
Sample_Feature
Required when using HRD add-on kit
SoftwareVersion
Not Required
The TSO500S software version
StartsFromFastq
Required
Set the value to TRUE or FALSE. To auto-launch from BCL files, set to FALSE.
Sample_ID
Not Required
The same sample ID used in the Cloud_TSO500S_Data section.
ProjectName
Not Required
The BaseSpace project name.
LibraryName
Not Required
Combination of sample ID and index values in the following format: sampleID_Index_Index2
LibraryPrepKitName
Not Required
The Library Prep Kit used.
GeneratedVersion
Not Required
The cloud GSS version used to create the sample sheet. Optional if manually updating a sample sheet.
CloudWorkflow
Not Required
Ica_workflow_1
Cloud_TSO500_Pipeline
Required
This value is a universal record number (URN). The valid values are:
Solid—urn:ilmn:ica:pipeline:e8eff7ef-1683-4f63-a0ba-9af542cd39e0#DRAGEN_TSO500_RUO_TISSUE_HT_v2_5_2_1_Pipeline
Solid HRD —urn:ilmn:ica:pipeline:172270e9-3678-45a9-a9f4-c9c7a0a32bb8#DRAGEN_TSO500_RUO_TISSUE_HRD_v2_5_2_1_Pipeline
BCLConvert_Pipeline
Required
The value is a URN in the following format: urn:ilmn:ica:pipeline: <pipeline-ID>#<pipeline-name>
Enter trim This indicates that the BCL Convert software trims the specified adapter sequences from each read.
Indicates which lane corresponds to a given sample. Enter a single numeric value per row. Cannot be empty, i.e the analysis fails if the Lane column is present without a value in each row.
Required for HRD enriched samples.
For DNA samples that have undergone HRD enrichment, enter HRD in this column of the sample sheet. If the sample has not undergone HRD enrichment, leave the field empty.
DRAGEN TSO 500 ctDNA
2.6.2+
Multi-version
Yes
DRAGEN TSO 500 ctDNA
2.6.1 or below
Single-version
No
DRAGEN pipelines**
4.3.6+
Multi-version
Yes
DRAGEN pipelines**
4.2 or below
Single-version
No
For Apptainer, use the following command:
sudo TMPDIR=/staging /staging/install_DRAGEN_TSO500-2.5.4.run -- --noDockerInstall This will not install Apptainer, but will install the analysis software in the SIF container format and modify the software to launch analyses using Apptainer.
During the installation process, you might be instructed to reboot or power cycle the system to complete the installation of the DRAGEN software. A power cycle of the system requires the server be shut down and restarted.
Log out of the server and then log back in.
Use the following command to build the DRAGEN server hash table (run time ~ 1 hr):
/usr/local/bin/build-hashtable_DRAGEN_TSO500-2.5.4.sh
Refer to Troubleshooting if any errors occur.
Docker
20.10 or greater
Docker 20.10.15
DRAGEN Server Software*
v3.10.x, where x >=19, v4.3+
DRAGEN Software 3.10.19
DRAGEN TSO 500
2.6.1
Multi-version
Yes*
DRAGEN TSO 500
2.6.0
Single-version
No
DRAGEN TSO 500
2.5.3 or below
Single-version
No
Median of median base coverage of genes scaled by length. An indication of median coverage depth of genes in the panel.
Count
TOTAL_PF_READS
Total number of reads passing filter.
Count
GENE_MEDIAN_COVERAGE
The median coverage depth of all genes in the panel.
Count
GENE_ABOVE_MEDIAN_CUTOFF
Number of genes above the median coverage cutoff.
Count
PER_GENE_MEDIAN_COVERAGE
Median deduped coverage across each gene (available in Logs_Intermediates only)
Count
PCT_CHIMERIC_READS
Percentage of reads that are aligned as two segments which map to nonconsecutive regions in the genome.
%
PCT_ON_TARGET_READS
Percentage of reads that cross any part of the target region versus total reads. A read that partially maps to a target region is counted as on target.
%
SCALED_MEDIAN_GENE_COVERAGE
PCT_TARGET_HRD_50X
Percent of HRD probe SNP panel covered by at least 50X coverage
DNA Library QC Metrics for GIS
EXCESSIVE_TF
EXCESSIVE TF indicates if there is excessive tumor content in sample. Troubleshooting: Samples with pure tumor fraction >90% are outside the design for GIS estimation (this includes pure tumor cell lines)
DNA Library QC Metrics for GIS
ALLELE_DOSAGE_RATIO
Proprietary Myriad Genetics estimate of b-allele dosage based on b-allele noise/signal ratio. B-Allele noise is correlated with coverage; lower coverage samples will have higher noise. B-allele signal is also correlated with tumor fraction; a higher tumor fraction produces a higher signal for b-allele sites. Samples with lower tumor fraction and higher amount of noise (or lower coverage) will have higher Allele Dosage Ratio. The upper limit of the score is 50, therefore any sample with 50 Allele Dosage Ratio can be assumed to have tumor fraction close to zero and typically has a GIS = 0.
DNA Expanded Metrics
MEDIAN_TARGET_HRD_COVERAGE
Median target fragment coverage across all target positions in the genome. Coverage is the total number of non-duplicate pair alignments that overlap.
Genomic Instability Score (GIS)
Proprietary Genomic Instability Score (GIS) indicating level of genomic instability in sample genome. Combination of Loss of Heterozygosity (LOH), Telomeric allelic imbalance and Large-scale State Transitions (LST) scores. The GIS scores provided by TruSight Oncology 500 HRD show good correlation (R2= 0.98) with Myriad Genetics GIS however they are not identical (Refer to TruSight Oncology 500 HRD Product Data Sheet Doc# M-GL-00748 for more details). GIS from alternative HRD assays should be not be considered equivalent to Illumina/Myriad GIS.
The contamination score is calculated using the SNP error file and Pileup file that are generated during the small variant calling, as well as the TMB trace file. The algorithm includes the following steps:
All positions that overlap with a pre-defined set of common SNPs that have variant allele frequencies of < 25% or > 75% are collected (only SNP are considered, indels are excluded)
Variants in CNV events are removed using a clustering method
The likelihood that the positions are an error or a real mutation is calculated by:
Estimating the error rate per sample
Counting mutation support
Counting total depth
The contamination score is calculated as the sum of all the log likelihood scores across the pre-defined SNP positions whose minor allele frequency is <25% in the sample and not likely due to CNV events:
CONTAMINATION_SCORE = sum(log10(P(vi is False Positive)))
The contamination score is output in the metrics output file, MetricsOutput.tsv
If a contamination score is equal or below 1457 (the upper specification limit provided in the "USL Guideline" field in the metrics output file, see Metrics Output page), the sample has less than 2% sample-to-sample contamination.
If a contamination score is above 1457, the sample has more than 2% sample-to-sample contamination. In this case, an estimation of the contamination can be obtained from the PCT_CONTAMINATION_EST metric, see more details on the DNA Expanded Metrics page. As noted, PCT_CONTAMINATION_EST is not valid unless the contamination score exceeds 1457.
Samples with highly rearranged genomes (HRD samples) can have variants with VAFs that shift away from the expected frequencies due to genomic rearrangement, which can lead to false-positive contamination scores
Visual examination can help determine if a shift of VAFs is due to true contamination
To build a VAF plot, use the {Sample_ID}.tmb.trace.csv file. Filter to only germline variants (for example, by using tags "Germline_DB" and "Germline_Proxi" in the column "Status") and use values in the VAF column.
Select Scatter from the Charts menu
Review plot as described above analyzing whether variants are scattered or clustered around 50% and 100% VAF
The BaseSpace Sequence Hub Run Planning tool is available and is used to generate a valid sample sheet in v2 format for use on a TSO 500 supported sequencer for both ICA and Standalone DRAGEN Server analysis options. Filling out the form on the user interface will produce a exportable sample sheet with the required fields filled in. Refer to ICA Auto-launch Sample Sheet Requirements for descriptions of fields that appear in ICA sample sheets.
The sections below represent each step in the BaseSpace Run Planning tool.
Users can manually enter sample information, or download a template file to bulk upload sample information. Users can import the completed template or a compatible sample sheet.
Once all details are captured and pass validation, the user can review the details on the Run Review screen. From here they can choose to edit details in previous screens or export the sample sheet. Once completed, press the Cancel button to finish run planning.
Note: once leaving this screen, the run and sample sheet will not be accessible.
Please review these guided examples of analysis workflows that include a step of setting up a run in BaseSpace Run Planning tool:
File name: {Pair_ID}_CombinedVariantOutput.tsv
The combined variant output file contains the variants and biomarkers in a single file that is based on a single sample. If using pair ID, the file is based on paired DNA and RNA samples from the same individual. The output contains the following variant types and biomarkers:
Small variants
Copy number variants (CNV) (with absolute copy number when HRD Assay is run)
TMB
MSI
Fusions
Splice variants
GIS (when HRD Assay is run)
Gene-level Loss of Heterozygosity (when HRD Assay is run)
Exon-level CNVs
The combined variant output file also contains Analysis Details and Sequencing Run Details sections. The details of each are listed in the following table:
Combined variant output produces small variants with blank fields in the following situations:
The variant has been matched to a canonical RefSeq transcript on an overlapping gene not targeted by TruSight Oncology 500.
The variant is located in a region designated iSNP, indel, or Flanking in the TST500_Manifest.bed file located in the Resources folder.
Small Variants - All variants with the FILTER field marked as PASS in the hard-filtered genome VCF are present in the combined variant output.
Gene information is only present for variants belonging to canonical transcripts that are within the Gene Allow List–Small Variants.
Transcript information is only present for variants belonging to canonical transcripts that are within the Gene Allow List–Small Variants.
*The BaseSpace Sequence Hub setting for run monitoring and storage must be selected on the instrument to use DRAGEN TSO 500 analysis auto-launch. For information on preparing your instrument for DRAGEN TSO 500 Auto-launch, refer to the documentation for your instrument.
DNA expanded metrics are provided for information only. They can be informative for troubleshooting but are provided without explicit specification limits and are not directly used for sample quality control. For additional guidance, contact Illumina Technical Support.
DNA Expanded Metrics
Copy Number Variants - Copy number variants must meet the following conditions:
FILTER field marked as PASS.
ALT field is <DUP or <DEL> .
Fusion Variants - Fusion variants must meet the following conditions:
Passing variant call (KeepFusion field is true).
Contains at least one gene on the fusion allow list.
Genes separated by a dash (-) indicate that the fusion directionality could be determined. Genes separated by a slash (/) indicate that the fusion directionality could not be determined.
Biomarkers TMB/MSI - Always present when DNA sample is processed.
Splice Variants - Passing splice variants that are contained on genes EGFR, MET, and AR.
Biomarker GIS - Present only if TruSight Oncology 500 HRD analysis is performed
Loss of Heterozygosity - Present only when TruSight Oncology 500 HRD is run. Loss of heterozygosity (LOH) must meet the following condition:
MCN field is equal to 0
Exon-level CNVs - Exon-levels CNVs must meet the following conditions:
BRCA1 or BRCA2 contains at least one affected exon.
ALT field is <DUP> or <LOSS> .
- Pair ID - DNA sample ID (if DNA is run) - RNA sample ID (if RNA is run) - Output date - Output time - Module version - Pipeline version (Docker image version #)
- Run name - Run date - DNA sample index ID (if DNA is run) - RNA sample index ID (if RNA is run) - [HRD] Sample feature - Instrument ID - Instrument control software version - Instrument type - RTA version - Reagent cartridge lot number
Median depth across all the unique loci occurring in all regions of the manifest file.
Lower median target coverage may be due to poor sample input/quality, library preparation issues or low sequencing output.
PCT_CHIMERIC_READS (%)
Chimeric reads occur when one sequencing read aligns to two distinct portions of the genome with little or no overlap. Metric is proportion of total number of non-supplementary, non-secondary, and passing QC reads after alignment to the whole genome sequence.
While this can be indicative of large-scale structural rearrangement of the genome, values that are elevated above the usual baseline may indicate enrichment probe contamination during library preparation. A suggested metric USL is 8% (those that are higher might see decrease performance in small variant and tmb scores).
PCT_EXON_100X (%)
Percentage of exon bases with 100X fragment coverage. Calculated against all regions in manifest containing _exon in name.
Can be used in combination with other PCT_EXON metrics to understand under or over coverage of exons.
PCT_READ_ENRICHMENT (%)
Percentage of reads that have overlapping sequence with the target regions defined in the sample manifest.
Indicative of general enrichment performance. Reduced proportions of enriched reads may indicate issues with the enrichment proportion of the library preparation.
PCT_USABLE_UMI_READS (%)
Percentage of reads that have valid UMI sequences associated with them.
As UMI reads are sequenced at the start of each read, loss of valid UMI sequence may be cause by sequencing issues impacting the quality of base calling in this portion of the sequencing read.
MEAN_TARGET_COVERAGE (count)
Mean depth across all the unique loci defined in the manifest file.
Lower mean target coverage may be due to poor sample input/quality, library preparation issues or low sequencing output. Large differences between the median and mean target coverage values may indicated a skewed distribution of target coverage.
PCT_ALIGNED_READS (%)
Proportion of aligned reads that are non-supplementary, non-secondary and pass QC versus aligned reads that are non-supplementary, non-secondary, mapped and pass QC.
PCT_CONTAMINATION_EST (%)
This metric should only be evaluated if the CONTAMINATION_SCORE metric exceed the USL. This metric estimates the amount of contamination in a sample. The contamination level is computed by taking 2.0* the average of the adjusted allele frequencies of all variants that were selected. The adjusted alllele frequency is either the actual allele frequency of the variant if it is less than 0.5, or 1 -allele frequency if it is greater than or equal to 0.5.
If the sample does not fail the CONTAMINATION_SCORE this metric has no intended meaning as it will be driven by statistical noise (e.g. the few variants that naturally fall outside an expected interval around 0.5 due to random chance)
High contamination estimates may be due to any of the following:
Inter-sample contamination caused by mixing of samples during extraction or library preparation.
Intra-sample contamination, due to mixing of clonally different cell populations during extraction. Large scale genomic rearrangements that cause unexpected VAFs for large numbers of variants.
PCT_TARGET_0.4X_MEAN (%)
Parentage of target (all locations in manifest) reads that have a coverage depth of greater the 0.4x the mean target coverage depth (see definition above).
Provides an indication of uniformity of coverage of the target regions in the manifest file. When trended over time reductions in this metric may indicate an issue with the enrichment process resulting in coverage bias.
PCT_TARGET_50X (%)
Percentage of target bases with 50X fragment coverage. Calculated against all regions in manifest file.
Can be used in combination with other PCT_TARGET metrics to understand under or over coverage of targets.
PCT_TARGET_100X (%)
Percentage of target bases with 100X fragment coverage. Calculated against all regions in manifest file.
Can be used in combination with other PCT_TARGET metrics to understand under or over coverage of targets.
PCT_TARGET_250X (%)
Percentage of target bases with 250X fragment coverage. Calculated against all regions in manifest file.
Can be used in combination with other PCT_TARGET metrics to understand under or over coverage of targets.
ALLELE DOSAGE_RATIO (with HRD add-on)
Proprietary Myriad Genetics estimate of b-allele dosage based on b-allele noise/signal ratio. B-Allele noise is correlated with coverage; lower coverage samples will have higher noise. B-allele signal is also correlated with tumor fraction; a higher tumor fraction produces a higher signal for b-allele sites. Samples with lower tumor fraction and higher amount of noise (or lower coverage) will have higher Allele Dosage Ratio. The upper limit of the score is 50, therefore any sample with 50 Allele Dosage Ratio can be assumed to have tumor fraction close to zero and typically has a GIS = 0.
MEDIAN TARGET HRD (with HRD add-on)
Median target fragment coverage across all target positions in the genome. Coverage is the total number of non-duplicate pair alignments that overlap.
TOTAL_PF_READS (count)
Total number of non-supplementary, non-secondary, and passing QC reads after alignment to the whole genome sequence.
Primarily driven by data output of sequencer, quality of library and balancing of library in library pool. If TOTAL_PF_READS is in line with other samples, but coverage metrics are more may suggest non-specific enrichment.
Low values for all samples indicate a poor quality run with possible low cluster numbers or low numbers of Q30 and PF%.
A low value for an individual sample indicates poor pooling of this library into the final pool.
MEAN_FAMILY_SIZE (count)
A UMI Family is a group of reads that all have the same UMI barcode. The family size is the number of reads in family. MEAN_FAMILY_SIZE is the mean of the entire population of reads assembled into UMI families.
The mean UMI family size decreases with increased unique read numbers, and more input DNA leads to more unique reads. Conversely over sequencing of a fixed population of unique DNA molecules leads to increased family size.
As a guide, for a good run with optimal cluster density, passing specs, even sample pooling, and good quality DNA we usually observe values <10.
UMI family size = 1 is not ideal as it is harder to correct for errors.
UMI family size of 2 to 5 enables efficient error correction without wasting sequencing capacity on high percentages of duplicate reads.
MEDIAN_TARGET_COVERAGE (count)
Sample Container ID
Optional
Unique Identifier for the container that holds the sample
DNA Index ID
Required
Index set ID options are based on selected Index Adapter Kit
DNA Sample Feature
Required for TSO 500 HRD
Column appears when TSO 500 HRD application is selected. Enter for HRD enriched DNA Samples
RNA Index ID
Required
Index set ID options are based on selected Index Adapter Kit
Project
Optional
Optional field to describe the associated project
Starts from Fastq
Required
True or False
If auto-launching TSO 500 from BCL files, set the value to False.
Run Name
Required
Run Name can contain 255 alphanumeric characters, dashes, underscores, periods, and spaces; and must start with an alphanumeric, a dash or an underscore.
Run Description
Optional
Run Description can contain 255 characters except square brackets, asterisks, and commas.
Instrument Platform
Required
Choose from TSO 500 supported instruments:
NextSeq 500/550
NovaSeq 6000/6000Dx
Secondary Analysis
Required
Application
Required
DRAGEN TruSight Oncology 500 Analysis Software - 2.5.x (with HRD)
DRAGEN TruSight Oncology 500 Analysis Software - 2.5.x
Description
Optional
Optional text field
Library Prep Kit
Required
TruSight Oncology 500
TruSight Oncology 500 High Throughput
Index Adapter Kit
Required
Read Lengths: Read 1 and Read 2
Required
Auto filled with the standard values, but can be optionally overwritten.
Lane Usage
Optional
Checkbox allows users to apply the same lane across samples.
Lane
Required if Lane Usage is unchecked
Specify lanes for each sample. The unmarked checkbox at the top of the dropdown selects all lanes.
Pair ID
Required
BaseSpace/Illumina Connected Analytics (to generate sample sheet for cloud analysis)
Local
TSO 500:
TruSight Oncology 500 (NovaSeq 6000Dx, NovaSeq X, NextSeq 1000/2000)
TruSight Oncology 500 (NovaSeq 6000, NextSeq 550)
TSO 500 HT:
The identifier used to pair DNA and RNA samples in a run. The field is mandatory whether a sample is part of a pair, or not.
To note: The Sample ID field in the generated samplesheet will be auto-filled based on the Pair ID values captured. “_dna” and “_rna” (for DNA and RNA samples respectively) will be appended to the Pair ID value to create the Sample ID.
If BaseSpace Run Planning tool is not available in your region, use the sample sheet template.
Import the sample sheet to the instrument and start the sequencing run. Refer to ICA Auto-launch Sample Sheet Requirements for sample sheet guidance.
Data is uploaded to BaseSpace Sequence Hub and then pushed to ICA. You can monitor the run in BaseSpace Sequence Hub.
Analysis auto launches in ICA when sequencing and the upload completes. You can monitor the status of the analysis in BaseSpace Sequence Hub or ICA
If necessary, you can requeue the analysis via BaseSpace Sequence Hub.
View the analysis output results in either BaseSpace Sequence Hub or ICA.
To avoid invalid sample sheet configurations, Illumina recommends using BaseSpace Run Planning tool to generate sample sheets. Using an invalid sample sheet can result in failed runs and analyses.
For the data generated by NextSeq 1000/2000 and NextSeq X, only manual option for launching analysis on ICA is available. The analysis can only start from FASTQs files.
BaseSpace Run Planning tool is a multi-step workflow that generates a manual launch or auto-launch capable sample sheet for export and requires the following additional settings:
Access to BaseSpace Sequence Hub.
ICA Run Storage is enabled under BaseSpace Sequence Hub settings.
Refer to the BaseSpace Sequence Hub support site page for information on setting up a BaseSpace Sequence Hub project.
You can requeue analysis of a run via the run's Summary page in BaseSpace Sequence Hub.
Refer to the BaseSpace Sequence Hub support site page for more information on requeuing an analysis.
NextSeq 500/550/550Dx (RUO) HO flow cell
350
NovaSeq 6000/6000Dx (RUO) SP Flow Cell
500
NovaSeq 6000/6000Dx (RUO) S1 Flow Cell
1100
NovaSeq 6000/6000Dx (RUO) S2 Flow Cell
2500
NovaSeq 6000/6000Dx (RUO) S4 Flow Cell
4300
NovaSeq X 1.5B
2000
Refer to the Software Registration page for information on how to manage accounts and subscriptions.
Please review these guided examples of using DRAGEN TSO 500 Analysis Software with auto-launch on ICA:
ICA standard storage is used by default as soon as the Project is saved. To connect a different storage source, set it up before creating your Project. For details and options, refer to the Storage section in Illumina Connected Analytics help.
Edit Project and Add Bundle: Edit the Project and add the bundle titled, "DRAGEN TSO 500 v2.5.2 (XX)." XX is a 2-letter code designating the region from which you are launching the analysis. Adding the Bundle automatically adds the pipeline and associated resource files and datasets to the Project. For information on Bundles, refer to the Bundles section in Illumina Connected Analytics help.
After adding the Bundle to the Project, an example dataset becomes available in the Demo_Data folder for the Project.
Upload the sequencing data: For information on viewing and uploading data, refer to the Data section in Illumina Connected Analytics help.
Start Analysis: In the Project, navigate to Pipelines, desired TSO 500 Pipeline, and then select "Start New Analysis". Set up the new analysis by configuring the parameters listed in the table below. When the required files are completed, start analysis.
Download Results: After analysis is complete, navigate to results in the configured output location.
Please see the Illumina Support Shorts for guidance on how to set up and run DRAGEN TSO 500 RUO analysis on ICA.
To launch an analysis via the ICA user interface, configure a DRAGEN TSO 500 pipeline analysis with the following parameters.
User Reference
The analysis run name.
User Tags
Text labels to help index the analysis.
Notify me when task is completed
Option to receive an email notification when analysis is complete.
Output Folder
The path to the analysis output folder. The default path is the project output folder.
Entitlement Bundle
Automatically populated from the project details.
Sample Sheet
Select a sample sheet in CSV format for the analysis.
To note: Sample Sheet selection is optional if starting from a run folder, and required when submitting a FASTQ folder.
FASTQ Folder Naming Requirements
When specifying input FASTQ folder names, avoid using folder names that consist entirely of numeric characters with a leading zero, as this will cause the software to error out.
Unsupported naming pattern:
'01234' (numeric-only with leading zero)
Supported naming patterns:
'12340' (numeric without leading zero)
'sample01' (alphanumeric)
For information about using pipelines, refer to Illumina Connected Analytics support site page.
The installation script for DRAGEN TruSight Oncology 500 Analysis Software installs the following software and dependencies:
DRAGEN TruSight Oncology 500 Analysis Software itself
DRAGEN Software if a compatible version is not present
Docker software if a compatible version is not present
A script required to generate DRAGEN genome hash table
A script to check that DRAGEN TruSight Oncology 500 Analysis Software is installed properly
DRAGEN server v3 or v4
Network-attached storage (NAS) with enabled mkfifo if performing analysis for the TruSight Oncology 500 High-Throughput assay
The following software is required to successfully install DRAGEN TSO 500 v2.5.3:
Linux CentOS 7.9 operating system (or later) or Oracle Linux 8 (or later), one of which is provided on the server. Oracle Linux 8 is recommended.
Docker Software, see table below for minimum version needed. If sufficient Docker software is not present on the server, the TSO 500 installer will install compatible Docker software.
DRAGEN Server Software, see table below for minimum version needed as the host version on the server. If sufficient DRAGEN software is not present on the server, the TSO 500 installer will install compatible DRAGEN software.
TSOCombined license
TSO500_HRD license (to analyze data generated with the TSO 500 HRD add-on kit)
TSOCombined license has been pre-installed to DRAGEN servers in manufacturing since August 2022 and TSO500_HRD since February 2025 and additionally distributed to DRAGEN servers connected online. To generate a list of installed DRAGEN server licenses, run the following command: /opt/edico/bin/dragen_lic. If a license is not installed, contact Illumina Customer Care at for the license.
Illumina recommends logging in as root user for installation, but as a non-root user for running TSO 500 analysis.
A non-root user must be a member of the Docker group to run Docker. For more information on Docker permission requirements and alternatives to running as root, refer to the Docker documentation available on the .
Installing and uninstalling DRAGEN TruSight Oncology 500 Analysis Software and running the system check requires root privileges.
Run DRAGEN TruSight Oncology 500 Analysis Software without being logged in as a root user. Running the DRAGEN TruSight Oncology 500 Analysis Software as root is not required or recommended.
DRAGEN TSO 500 Analysis Software v2.5.3 is single-version compatible. It does not include multi-version compatibility that refers to ability to be installed on a single DRAGEN server with software running a different version of DRAGEN software. For example, multi-version compatible pipelines running DRAGEN v4.3.6 can be co-installed on a server alongside DRAGEN TSO 500 pipelines running DRAGEN v3.10.17. For more details on DRAGEN multi-version compatibility, please visit .
Compatibility of software for co-installation with DRAGEN TSO 500 v2.5.3 on a DRAGEN server is summarized in the table below:
*Install DRAGEN TSO 500 Analysis Software v2.6.0 after installing 2.5.3. If v2.5.3 is installed after v2.6.0, re-execute the installation script for v2.6.0 to install the compatible version of DRAGEN Software without impacting v2.5.3.
** When co-installing v2.5.3 with DRAGEN TSO 500 ctDNA software on the same DRAGEN server, install the software with the highest corresponding DRAGEN Software version last. Find DRAGEN software versions for DRAGEN TSO 500 ctDNA software in parentheses: v2.1.1 (v3.10.9), v2.5.0 (v3.10.15), 2.6.0 (v3.10.17), 2.6.1 (v3.10.18).
***For example, DRAGEN Enrichment, DRAGEN Germline, and others
As a root user, perform the following steps to install DRAGEN TSO 500 v2.5.3 Analysis Software:
Contact Illumina Customer Care at to obtain the DRAGEN TSO 500 Analysis Software installer package.
Download the installation package provided in the email from Illumina. The link expires after 7 days.
It is recommended to use a command line tool like wget or curl to download the file rather than pasting the link into the web browser bar. For example:
curl -o {filename} "{link}"
wget -O {filename} '{link}'
Where the file name is the installation script file name, and the link is provided by Illumina Customer Care.
Make sure no other analysis is being performed. Installing the software while performing other analyses prevent the installer process from proceeding
Copy the install script to the /staging directory to store the script in the directory.
Installation Script: install_DRAGEN_TSO500-2.5.3.run
MD5sum: sha256:ab9fae7ba58842d797ba689e702693c0fd7a5c2852dda610dce6d68152fe1f8d
Use the following command to update the run script permission:
chmod +x /staging/install_DRAGEN_TSO500-2.5.3.run
Use the following command to run the installation script (run time ~ 20 mins):
For Docker, use the following command:
sudo TMPDIR=/staging /staging/install_DRAGEN_TSO500-2.5.3.run. The script installs compatible DRAGEN software and removes any previously installed versions.
Review license requirements, how to check which licenses are installed and how to receive a license in . Licenses can be installed before or after DRAGEN TSO 500 software installation.
To install a license (TSOCombined and/or TSO500_HRD) on a DRAGEN server connected to the internet:
Confirm that the server is connected to the Internet, example: ping www.illumina.com
Run the following command: /opt/edico/bin/dragen_lic -i auto
To install a license (TSOCombined and/or TSO500_HRD) on a DRAGEN server not connected to the internet:
Contact Customer Care at to request a license file for each of the needed licenses
Download and save the license file(s) to a location that is accessible from the DRAGEN server
For each license file, run the command, where <license file received> is the absolute path to the license file: sudo /opt/edico/bin/dragen_lic -i /tmp/<license file received>.bin
To check the success of license installation, run: /opt/edico/bin/dragen_lic. Installed licenses should be in the list.
After installation is complete, make sure the system functions properly by running the following command: /usr/local/bin/check_DRAGEN_TSO500-2.5.3.sh
The script checks that:
All required services are running
Proper Docker image is installed
DRAGEN TSO 500 Analysis Software can successfully process a test data set
The system check script runs for approximately 25 minutes. If the script prints a failure message, contact Illumina Technical Support and provide the /staging/check_DRAGEN_TSO500_<timestamp>.tgz output file.
If using MacOS to connect to a server, an error can occur if the local settings are not in English. To resolve the error, disable the ability to set environment variables automatically in Terminal settings.
The DRAGEN TruSight Oncology 500 Analysis Software installation includes an uninstall script called uninstall_DRAGEN_TSO500-2.5.3.sh, which is located in /usr/local/bin.
Executing the uninstall script removes the following assets:
All DRAGEN TruSight Oncology 500 Analysis Software related scripts located in /usr/local/bin
Resources found in /staging/illumina/DRAGEN_TSO500
The dragen_tso500:2.5.3: Docker image
To uninstall the DRAGEN TSO 500 Analysis Software, run the following command as a root user:
uninstall_DRAGEN_TSO500-2.5.3.sh
You are not required to uninstall Docker or DRAGEN software. To remove Docker, review the install instructions for your operating system in the Docker documentation.
You can use the following command-line options with DRAGEN TruSight Oncology 500 Analysis Software.
To learn more about the input requirements, use the --help command-line option.
Start the DRAGEN TruSight Oncology 500 Analysis Software with the DRAGEN_TSO500.sh Bash script. The script is installed in the /usr/local/bin directory. The Bash script is executed on the command line and runs the software with Docker (or Apptainer if specified).
For arguments, refer to . You can start from BCL files or from the FASTQ folder produced by BCL Convert. The following requirements apply for both methods:
Path to the sequencing run or FASTQ folder. Copy the run or FASTQ folder to the DRAGEN server into the staging folder with the following recommended organization: /staging/runs/{RunID}. You can copy the run folder onto the DRAGEN server using Linux commands such as
TruSight Oncology 500 (NovaSeq 6000, NextSeq 550)
NovaSeq X 10B
4300
NovaSeq X 25B
8400
NextSeq 1000/2000
350
DRAGEN TSO 500
2.6.1+
Multi-version
No
DRAGEN TSO 500 ctDNA
1.2 or below
Single-version
No
DRAGEN TSO 500 ctDNA
2.1.1, 2.5.0, 2.6.0, 2.6.1
Single-version
Yes**
DRAGEN TSO 500 ctDNA
2.6.2+
Multi-version
No
DRAGEN pipelines***
3.10.16
Single-version
Yes
DRAGEN pipelines***
Any version except 3.10.16
Single- or multi-version
No
For Apptainer, use the following command:
sudo TMPDIR=/staging /staging/install_DRAGEN_TSO500-2.5.3.run -- --noDockerInstall This will not install Apptainer, but will install the analysis software in the SIF container format and modify the software to launch analyses using Apptainer.
During the installation process, you might be instructed to reboot or power cycle the system to complete the installation of the DRAGEN software. A power cycle of the system requires the server be shut down and restarted.
Log out of the server and then log back in.
Use the following command to build the DRAGEN server hash table, which runs for approximately 60 minutes:
/usr/local/bin/build-hashtable_DRAGEN_TSO500-2.5.3.sh
Refer to Troubleshooting if any errors occur.
Docker
20.10 or greater
Docker 20.10.15
DRAGEN Software
v3.10.x where x is 16 or greater
DRAGEN Software 3.10.16
DRAGEN TSO 500
2.5.2 or below
Single-version
No
DRAGEN TSO 500
2.5.4
Multi-version
No
DRAGEN TSO 500
2.6.0
Single-version
Yes*
'test_sample' (alphanumeric with underscore)
Input Folder
The run folder or FASTQ folder that contains files to analyze.
Starts from FASTQ
True for analysis performed on files in the FASTQ folder. False for analysis performed on files in the run folder.
Sample or Pair IDs
Optional subset of Sample IDs or Pair IDs to analyze.
Storage Size
The storage size to allocate for the analysis. The default and recommended value is Large.
PASS
PASS variants.
base_quality
Site filtered because median base quality of alt reads at this locus does not meet threshold.
filtered_reads
Site filtered because the fraction of reads is too large.
fragment_length
Site filtered because absolute difference between the median fragment length of alt reads and median fragment length of ref reads at this locus exceeds threshold.
low_depth
Site filtered because the read depth is too low.
low_frac_info_reads
Site filtered because the fraction of informative reads is below threshold.
File name: {SAMPLE_ID}_DNAVariants_Annotated.json.gz
The small variants annotated file provides variant annotation information for all nonreference positions from the genome VCF including pass and nonpass variants.
The TMB trace file provides comprehensive information on how the TMB value is calculated for a given sample. All passing small variants from the small variant filtering step are included in this file. To calculate the numerator of the TmbPerMb value in the TMB JSON, set the TSV file filter to use the IncludedInTMBNumerator with a value of True.
The TMB trace file is not intended to be used for variant inspections. The filtering statuses are exclusively set for TMB calculation purposes. Setting a filter does not translate into the classification of a variant as somatic or germline.
Chromosome
Chromosome
Position
Position of variant
RefCall
Reference base
AltCall
Alternate base
VAF
Variant allele frequency
Depth
Coverage of position
The copy number VCF file contains CNV calls for DNA libraries of the amplification genes targeted by DRAGEN TruSight Oncology 500 Analysis Software. The CNV call indicates fold change results for each gene classified as reference, deletion, or amplification.
The value in the QUAL column of the VCF is a Phred transformation of the p-value where Q=-10xlog10(p-value). The p-value is derived from the t-test between the fold change of the gene against the rest of the genome. Higher Q-scores indicate higher confidence in the CNV call.
In the VCF notation, <DUP> indicates the detected fold change (FC) is greater than a predefined amplification cutoff. <DEL> indicates the detected FC is less than a predefined deletion cutoff for that gene. This cutoff can vary from gene to gene.
In analysis versions prior to v2.5, <DEL> calls in the VCF are marked as LowValidation. The LowValidation filter indicates that the calls have been validated only with in silico data sets and are provided as information only.
Each copy number variant is reported as a fold change on normalized read depth in a testing sample relative to the normalized read depth in diploid genomes. Given tumor purity, you can infer the ploidy of a gene in the sample from the reported fold change.
Given tumor purity X%, for a reported fold change Y, you can calculate the copy number n using the following equation:
For example, a tumor purity at 30% and a MET with fold change of 2.2x indicates that 10 copies of MET DNA are observed.
Path to the local analysis folder. The default location is /staging/DRAGEN_TSO500_Analysis_{timestamp}. If not using the default location, provide the full path to the local analysis folder. Folder must have sufficient space and must be on an NVMe SSD drive. For example, the /staging directory on the DRAGEN server.
Refer to table in for minimum disk space requirements.
--resourcesFolder
No
Path to the resource folder location. The default location is /staging/illumina/DRAGEN_TSO500/resources. If not using the default location, enter the full path to the resource folder.
--runFolder
Yes
Required when --fastqFolder is not specified. Provide the full path to the local run folder.
--fastqFolder
Yes
Required when --runFolder is not specified. Provide the full path to the local FASTQ folder. Analysis starts at this location.
--user
No
Optional for Docker. Specify the user ID to be used within the Docker container.
--version
No
Displays the version of the software.
--sampleSheet
No
Provide the full path, including file name, if not provided as SampleSheet.csv in the run folder
--sampleOrPairIDs
No
Provide the comma-delimited sample or pair IDs that should be processed on this node with no spaces. For example, Pair_1,Pair_2,Sample_1.
--demultiplexOnly
No
Demultiplex to generate FASTQ only without additional analysis.
--gather
No
Follow this option for any directories with results that should be gathered into a single Results folder.
--hashtableFolder
No
Defaults to the DRAGEN hash table location created upon install. If not using the default location, enter the hash table location.
Note:
Use full paths when specifying the file paths in the command line.
Avoid special characters such as &, *, #, and spaces.
When starting from BCL files, only the run folder needs to be specified. The immediate parent directory containing the BCL files does not need to be specified.
When running the analysis software using SSH, Illumina recommends using additional software to prevent unexpected termination of analysis. Illumina recommends screen and tmux.
Wait for any running DRAGEN TruSight Oncology 500 Analysis Software containers to complete before launching a new analysis. Run the following command to generate a list of running containers:docker ps
Select from one of the following options:
Start from BCL files in the run folder with the sample sheet included in the run folder.
DRAGEN_TSO500.sh \
--runFolder /staging/{RunFolderName} \
--analysisFolder /staging/{AnalysisFolderName}
Start from BCL files in the run folder with the sample sheet located in a folder other than the run folder.
DRAGEN_TSO500.sh \
--runFolder /staging/{RunFolderName} \
--analysisFolder /staging/{AnalysisFolderName} \
--sampleSheet /staging/{SampleSheetName}.csv
Start from BCL files in the run folder with a different sample sheet and demultiplexing only.
DRAGEN_TSO500.sh \
--runFolder /staging/{RunFolderName} \
--analysisFolder /staging/{AnalysisFolderName} \
--sampleSheet /staging/{SampleSheetName}.csv \
--demultiplexOnly
Start from FASTQ with the sample sheet included in the FASTQ folder and with different resources and hash table folders.
DRAGEN_TSO500.sh \
--resourcesFolder /staging/illumina/DRAGEN_TSO500/resources \
--hashtableFolder /staging/illumina/DRAGEN_TSO500/ref_hashtable \
--fastqFolder /staging/{FastqFolderName} \
--analysisFolder /staging/{AnalysisFolderName}
Start from FASTQ folder with sample sheet included in the FASTQ folder and subset of samples or pairs.
DRAGEN_TSO500.sh \
--fastqFolder /staging/{FastqFolderName} \
--analysisFolder /staging/{AnalysisFolderName} \
--sampleOrPairIDs "Pair_1,Pair2"
For the data generated by NextSeq 1000/2000 and NextSeq X, the analysis can only be started from FASTQs and not from BCLs.
If starting from BCL (*.bcl) files, DRAGEN TruSight Oncology 500 Analysis Software requires the run folder to contain certain files and folders. These inputs are required for Docker.
The run folder contains data from the sequencing run, make sure that the folder contains the following files:
Config folder
Configuration files
Data folder
*.bcl files
Images folder
[Optional] Raw sequencing image files.
Interop folder
Interop metric files.
Logs folder
[Optional] Sequencing system log files.
RTALogs folder
Real-Time Analysis (RTA) log files.
The following inputs are required for running the DRAGEN TruSight Oncology 500 Analysis Software using FASTQ (*.fastq) files. The requirements apply to Docker.
Full path to an existing FASTQ folder.
The FASTQ folder structure conforms to the folder structure in FASTQ File Organization.
The sample sheet is in the FASTQ folder path, or you can set the path to the sample sheet with the --sampleSheet override command line option.
Make sure there is sufficient disk space for the analysis to complete. Refer to the --help command line argument details for disk space requirements.
Use BCL Convert to produce FASTQ files for DRAGEN TruSight Oncology 500 Analysis Software. Using bcl2fastq does not produce the same results and is discouraged.
Make sure that BCL Convert is set to write UMI sequences to the read headers in the FASTQ files.
Store FASTQ files in individual subfolders that correspond to a specific Sample_ID. Keep file pairs together in the same folder. Alternatively, store the FASTQ files in one flat folder structure where the FASTQ files are stored in one folder.
The DRAGEN TruSight Oncology 500 Analysis Software requires separate FASTQ files per sample. Do not merge FASTQ files.
The instrument generates two FASTQ files per flow cell lane, so that there are eight FASTQ files per sample.
Sample1_S1_L001_R1_001.fastq.gz
Sample1 represents the Sample ID.
The S in S1 means sample, and the 1 in S1 is based on the order of samples in the sample sheet, so S1 is the first sample.
L001 represents the flow cell lane number.
The R in R1 means Read, so R1 refers to Read 1.
--help
No
Displays a help screen with available command line options.
--analysisFolder
No
rsyncRun folder must be intact. Refer to Starting from BCL Files for input requirements.
If the analysis output folder path is different from the default, provide the analysis output folder path. Refer to Command-Line Options.
Before running the analysis, confirm that the output directory for the software to write to is empty and does not include results of previous analyses.
For optimal performance, run analysis on data stored locally on the DRAGEN server. Analysis of data stored on NAS can take longer and performance can be less reliable.
The DRAGEN server provides an NVMe SSD in the /staging directory to use as the software output directory. Network-attached storage is required for long-term storage.
When running the DRAGEN TruSight Oncology 500 Analysis Software, use the default settings or set the -analysisFolder command line option to a directory in /staging to make sure the DRAGEN server processes read and write data on the NVMe SSD.
Before beginning analysis, develop a strategy to copy data from the DRAGEN server to a network‑attached storage. Delete output data on the DRAGEN server as soon as possible.
The following are the run and analysis output sizes for each sequencing system per 101 bp:
NextSeq 500/550/550Dx (RUO) HO flow cell
32-55
82-85
150
NovaSeq 6000/6000Dx (RUO) SP Flow Cell
85-100
250-374
300
NovaSeq 6000/6000Dx (RUO) S1 Flow Cell
164-200
When launching the analysis, the software checks that the minimum disk space required is available. If the minimum disk space is not available, the software shows an error message and prevents analysis from starting. If disk space is exhausted during a run, the run shows an error and stops analyzing.
Moving or modifying files during an analysis may cause the analysis to fail or provide incorrect results.
Software
- Open the log file ./<AnalysisFolder>/Logs_Intermediates/pipeline_trace.txt. This log file displays each pipeline step run by the Nextflow workflow manager software. If a step fails, it is marked as FAILED. Each step generates log files that are stored in step-specific subfolders in the Logs_Intermediates folder. Review the log files in the relevant Logs_Intermediates folder for the step to identify potential sources of error.
- Open the errors folder ./<AnalysisFolder>/errors. The workflow creates an error file, error_<NameOfFailedStep>.json, for each step that failed during analysis. For steps that fail per sample, there is a separately labeled file for each sample that failed each step error_<NameOfFailedStep>_<SampleIDIfRelevant>.json. These files contain the command and stdout and stderr from the step.
Samples
In DRAGEN TruSight Oncology 500 Analysis Software, the analysis fails if a sample sheet is invalid. If an invalid sample sheet in suspected, log files can help troubleshoot a failed analysis. Use the following steps to find the log file for the sample sheet:
Navigate to the following location /<analysis_output>/Logs_Intermediates/SamplesheetValidation.
Open the SamplesheetValidation-.log file
Find a line with the following: SampleSheetValidationTask:NA:1 exited with return code 1 which has not been declared as a valid return code.
In addition to TSO 500 managed sample sheet validations, ICA managed TSO 500 errors include the following:
DNA alignment and error correction involves aligning sequencing reads derived from DNA libraries to a reference genome and correcting errors in the sequencing reads prior to variant calling.
DRAGEN unique molecular identifier (UMI) error correction comprises three main steps:
long_indel
Site filtered because the indel length is too long.
mapping_quality
Site filtered because median mapping quality of alt reads at this locus does not meet threshold.
multiallelic
Site filtered because more than two alt alleles pass tumor LOD.
no_reliable_supporting_read
Site filtered because no reliable supporting somatic read exists.
read_position
Site filtered because median of distances between start/end of read and this locus is below threshold.
str_contraction
Site filtered due to suspected PCR error where the alt allele is one repeat unit less than the reference.
too_few_supporting_reads
Site filtered because there are too few supporting reads in the tumor sample.
weak_evidence
Somatic variant score (SQ) does not meet threshold.
systematic_noise
Site filtered based on evidence of systematic noise in normal sample.
excluded_regions
Site overlaps with VC excluded regions bed.
CytoBand
Cytoband of variant
GeneName
Name of gene if applicable. A semicolon delimited list is used for multiple genes.
VariantType
Type of the variant: SNV, insertion, deletion, MNV
CosmicIDs
Cosmic IDs, if multiple concatenated by “;”
MaxCosmicCount
Maximum Cosmic study count
AlleleCountsGnomadExome
Variant allele count in gnomAD exome database
AlleleCountsGnomadGenome
Variant allele count in gnomAD genome database
AlleleCounts1000Genomes
Variant allele count in 1000 genomes database
MaxDatabaseAlleleCounts
Maximum variant allele count over the three databases
GermlineFilterDatabase
TRUE if variant was filtered by the database filter
GermlineFilterProxi
TRUE if variant was filtered by the proxi filter
CodingVariant
TRUE if variant is in the coding region
Nonsynonymous
TRUE if variant has any transcript annotations with nonsynonymous consequences
IncludedinTMBNumerator
TRUE if variant is used in the TMB calculation
360-665
800
NovaSeq 6000/6000Dx (RUO) S2 Flow Cell
290-460
890-1600
1500
NovaSeq 6000/6000Dx (RUO) S4 Flow Cell
800-1200
2700-4100
3000
NovaSeq X 1.5B
213
352
800
NovaSeq X 10B
1100
1800
3000
NovaSeq X 25B
1800
3300
4000
NextSeq 1000/2000
41
107
150
Search for errors in the sample sheet validation log and compare with the guidelines and warnings in Sample Sheet Requirements and the following tables.
Open the combined metrics output results file ./<AnalysisFolder>/Results/<PairId>/MetricsOutput.tsv. If a sample fails an analysis step, the Pair ID that contains the sample shows the failure under FAILED_STEPS in the Analysis Status section, and COMPLETED_ALL_STEPS shows as False. If available, review the individual log files for the failed steps under ./<AnalysisFolder>/Logs_Intermediates to identify potential sources of error.
Multinode Gather
If the following error appears, check if the sample or pair ID was included multiple times during separate node analysis runs, before being gathered together. If the error exists, rerun one of the analyses without the duplicate and reattempt gathering. ERROR:Gather:Destination file ... already exists - check if the same sample ID is in multiple input folders
Sample Sheet not found
Verify that SampleSheet.csv is present at the top level of the run folder with the name "SampleSheet.csv". If the sample sheet is in a different location, supply the sample sheet using the --sampleSheet option
Indexes are not valid for the sequencer and/or assay
See Valid indexes for assay and instrument combinations for correct indexes for the sequencer and assay.
Pair_ID is not unique
Pair_ID column is required in the TSO500S_Data section of the sample sheet, which pairs at most one RNA and one DNA sample together for analysis. If the sample does not have a pair, use a unique pair ID for single samples.
Sample Sheet is not in v2 format
Verify that the format of the sample sheet is v2. v1 sample sheet is not compatible with DRAGEN TruSight Oncology 500 Analysis Software.
Analysis does not run
Verify the analysis starts from the run folder, and BCLs or FASTQs are in the correct locations as outlined in Starting From BCL Files and Starting From FASTQ Files respectively.
TSO 500
UP1-UP16
CP1-CP16 (DNA Only)
TSO 500 HT
UDP0001–UDP0192
Lane Column without Values
Ensure that the column is completed. If lane is not applicable to the run, delete the column.
Format of v2 sample sheet is incorrect
Verify that the following sections and fields are present in the sample sheet and follow the individual rules in Sample Sheet Requirements [BCLConvert_Settings] - SoftwareVersion - AdapterRead1 - AdapterRead2 - AdapterBehavior - MinimumTrimmedReadLength - MaskShortReads [BCLConvert_Data] - Sample_ID - index - index2 [TS0500S_Data] - Sample_ID - Index_ID - Sample_Type - Pair_ID - Sample Feature (Optional)
HRD analysis is missing
Verify that HRD is in the Sample Feature column in the sample sheet. Refer to Sample Sheet Requirements for more information.
Sample_ID and/or Sample_Type is not present
Verify that the sample sheet has columns and values for Sample_ID and Sample_Type.
Unique sample IDs
Verify that the Sample_IDs are unique in the sample sheet.
Format of v2 Sample Sheet is incorrect
Verify that the following sections and fields are present in the sample sheet and follow the individual rules in Sample Sheet Requirements. [TS0500S_Data] - Sample_ID - Index_ID - Sample_Type - Pair_ID
- Sample Feature (Optional) Verify when FASTQs were generated using the HRD add-kit (Not available in Japan), Sample Feature is added to those DNA Samples. Refer to Sample Sheet Requirements for more information.
Incorrect folder structure
Verify that the FASTQ files are in the correct structure. Refer to Starting From FASTQ Files for more information.
Invalid FASTQ input files
If the FASTQs are invalid, start TSO 500 analysis from BCL files.
HRD analysis missing
Make sure that HRD is in the correct column in the sample sheet.
The output file directory contains information from previous analyses
If this issue is seen: specify a new target output folder and repeat analysis To prevent this issue: specify an empty directory before starting analysis
Single exon (single probe) genes are still reported in the CNV VCF file, but not the CNV TSV file
No action needed; software is working as expected.
Currently all single probe genes are not emitted to the Copy Number Variants section of our CombinedVariantOutput.tsv. However, you can still find these events in the cnv.vcf.gz.
Due to the single probe nature, accurate CNV calling has not been validated and as such they are emitted as REF
Testing of cell lines, contrived samples and commercial controls does not return expected results
Review recommendations for using these samples types here.
Failure type: ValueError: Could not find pipeline ID for app BCLConvert in sample sheet SampleSheet.csv
Action: Ensure StartsFromFastq field is in the [TSO500S_Settings] section, and it is not present in the [BCLConvert_Settings] Section. Refer to Sample Sheet Requirements for more information.
RunInfo.xml file
Run information.
RunParameters.xml file
Run parameters.
SampleSheet.csv file
Sample information. If you want to use a sample sheet that is not in the run folder or a sample sheet named something other than SampleSheet.csv, provide the full path.
The raw alignments are processed to remove errors, including errors introduced during FFPE preservation, PCR amplification, and sequencing. Reads from the same original DNA molecule are tagged with the same UMI during library preparation. The UMI allows DRAGEN to compare related reads, remove outlier signals, and collapse multiple reads into a single high-quality sequence. Read collapsing adds the following BAM tags:
RX/XU—UMI.
XV—Number of reads in the family.
XW—Number of reads in the duplex-family or 0 if not a duplex family.
DRAGEN performs a final alignment step on the UMI-collapsed reads. These final alignments are then written to a BAM file and a corresponding BAM index file is created.
DRAGEN continues to use these final alignments as input for gene amplification (copy number) calling, small variant calling (SNV, indel, MNV, delin), microsatellite instability (MSI) status determination, and DNA library quality control.
DRAGEN supports calling SNVs, indels, MNVs, and delins in tumor-only samples by using mapped and aligned DNA reads from a tumor sample as input. Variants are detected via both column wise pileup analysis and local de novo assembly of haplotypes. The de novo haplotypes allow the detection of much larger insertions and deletions than possible through column wise pileup analysis only. DRAGEN insertions and deletions are validated with lengths of at least 0–25 bp and more than 25 bp can be supported. In addition, DRAGEN also uses the de novo assembly to detect SNVs, insertions, and deletions that are co-phased and part of the same haplotypes. Any such co-phased variants that are within a window of 15 bp can then be reassembled into complex variants (MNVs and delins). The tumor-only pipeline produces a VCF file containing both germline and somatic variants that can be further analyzed to identify tumor mutations. Variant calling extends ± 10 bp into introns; details of the regions covered can be found in the assay manifest file. The pipeline makes no ploidy assumptions, enabling detection of low-frequency alleles.
DRAGEN small variant calling includes the following steps:
Detects regions with sufficient read coverage (callable regions).
Detects regions where the reads deviate from the reference and there is a possibility of a germline or somatic call (active regions).
Assembles de novo graph haplotypes are assembled from reads (haplotype assembly).
Extracts possible somatic or germline calls (events) from column wise pileup analysis.
Calibrates read base qualities to account for FFPE noise.
Computes read likelihoods for each read/haplotype pair.
Performs variant calling by summing the genotype probabilities across all reads/haplotype pairs.
Performs additional filtering to improve variant calling accuracy, including using a systematic noise file. The systematic noise file indicates the statistical probability of noise at specific positions in the genome. This noise file is constructed using clean (normal) samples. Regions where noise is common (eg, difficult to map regions) have higher noise values. The small variant caller penalizes those regions to reduce the probability of making false positive calls.
The DRAGEN copy number variant caller performs amplification, reference, and deletion calling for CNV targets within the assay. It counts the coverage of each target interval on the panel, uses a preprocessed panel of normal samples to normalize target counts, corrects for GC coverage bias, and calculates scores of a CNV event from observed coverage and makes copy number calls.
The BRCA large rearrangement step generates segmentation of the BRCA1 and BRCA2 genes for exon-level CNV detection from the BAM file. Using the same method as CNV calling, the large rearrangement component counts coverage of each target interval of the panel, performs normalization, and calculates the fold change values for each probe across the BRCA genes. Normalization includes GC bias correction, sequencing depth, and probe efficiency using a collection of normal FFPE and genomic DNA samples. Initial segmentation is performed for each gene with circular binary segmentation. The merging of segments is then determined by amplitude, noise, and variance at adjacent segments using thresholds established with in silico data. A large rearrangement is reported for genes with more than one segment. Coordinates of the exon-level CNV and the log2 mean fold change for each of the BRCA gene segments are found in the *_DragenExonCNV.json file.
The Illumina Annotation Engine performs annotation of small variants, CNVs, and exon-level CNVs. The inputs are gVCF files and the outputs are annotated JSON files.
The Illumina Annotation Engine processes each variant entry and annotates with available information from databases such as dbSNP, gnomAD genome and exome, 1000 genomes, ClinVar, COSMIC, RefSeq, and Ensembl. The header includes version information and general details. Each annotated variant is included as a nested dictionary structure in separate lines following the header.
The following table shows version information for each annotation database:
gnomeAD
2.1
COSMIC
v84
ClinVar
2019-02-04
dbSNP
v151
1000 Genomes Project
Phase 3 v5a
RefSeq
NCBI Homo sapiens Annotation Release 105.20201022
DRAGEN is used to compute tumor mutational burden (TMB) in coding regions where there is sufficient coverage.
The following variants are excluded from the TMB calculation:
Non-PASS variants.
Mitochondrial variants.
MNVs.
Variants that do not meet a minimum depth threshold (50).
Variants that do not meet the minimum variant allele threshold (0.05).
Variants that fall outside the eligible regions.
Tumor driver mutations. Variants with a population allele count ≥ 50 are treated as tumor driver mutations. Germline variants are not counted towards TMB. Variants are determined as germline based on a database and a proxy filter.
Variants with a population allele count ≥ 10 that are observed in either the 1000 Genomes or gnomAD databases are marked as germline. MNVs, which do not count towards TMB, may be marked as germline when all their component small variants are marked as germline. The proxy filter scans the variants surrounding a specific variant and identifies those variants with similar variant allele frequencies (VAF). If the majority of surrounding variants of similar VAF are germline, then the variant is also marked as germline.
The formula for TMB calculation is:
TMB=Eligible Region Size(Mbp)Filtered Variants
NonsynonymousTMB=Eligible Region Size(Mbp)Filtered Nonsynonymous Variants
Outputs are captured in a _TMB_Trace.tsv file that contains information on variants used in the TMB calculation and a .tmb.json file that contains the TMB score calculation and configuration details.
DRAGEN can determine the MSI status of a sample. It uses a normal reference file, which was created from a set of normal samples. Normal reference files were generated by tabulating read counts for each microsatellite site. The normal file contains the read count distribution for each microsatellite site.
MSI calling is assessed on a predefined list of 130 A and T repeats. The first step in calculating the MSI score is determining how many sites are assessable. A site is considered assessable if it has at least 60 spanning reads. A spanning read is defined as one that extends 5 bp before and after the repeat.
Once assessable sites are identified, the distribution of repeat lengths is compared to the panel of normals. A site is classified as unstable if:
Jensen-Shannon distance ≥ 0.1, and
P-value ≤ 0.01.
After all sites are evaluated, DRAGEN reports:
The total number of sites assessed
The count of unstable sites
The percentage of unstable sites across the sample
Finally, the MSI score is calculated as:
Requires HRD add-on assay
Genomic instability score (GIS) is a whole genome signature for homologous recombination deficiency. The GIS is composed of the sum of three components: loss of heterozygosity, telomeric allele imbalance, and large-scale state transition. These components are estimated using the GIS algorithm contracted from Myriad Genetics, which uses an input of the b-allele frequency and coverage across a genome-wide single nucleotide panel. A panel of normal samples is used for both bias reduction and normalization prior to GIS estimation. Final GIS results can be found in the *.gis.json file.
The contamination analysis step detects foreign human DNA contamination using the SNP error file and pileup file that are generated during the small variant calling and the TMB trace file. The software determines whether a sample has foreign DNA using the contamination score. In contaminated samples, the variant allele frequencies in SNPs shift from the expected values of 0%, 50%, or 100%. The algorithm collects all positions that overlap with common SNPs that have variant allele frequencies of < 25% or > 75%. Then, the algorithm computes the likelihood that the positions are an error or a real mutation. The contamination score is the sum of all the log likelihood scores across the predefined SNP positions with minor allele frequency < 25% in the sample and are not likely due to CNV events.
The larger the contamination score, the more likely there is foreign DNA contamination. A sample is considered to be contaminated if the contamination score is above predefined quality threshold. The contamination score was found to be high in samples with highly rearranged genomes or HRD samples. 1% of HRD samples found to be above the threshold with no evidence for actual contamination.
Tumor fraction is calculated as described in the User Guide, section “HRD Metrics Report” and leverages the Myriad Genetics algorithm. Tumor fraction is output in the Logs_Intermediates/Gis/SAMPLE/SAMPLE.gis.json and Combined Variant Output file.
Ploidy is calculated as described in the User Guide, section “HRD Metrics Report” and leverages the Myriad Genetics algorithm. Ploidy is output in the in the Logs_Intermediates/Gis/SAMPLE/SAMPLE.gis.json and Combined Variant Output file.
This is a beta feature. Beta feature results are included in the Combined Variant Output file and other files. However, disclaimers that the results are generated by beta features are only provided in the Combined Variant Output file. Requires HRD add-on assay.
Absolute copy numbers are calculated by leveraging the Myriad Genetics algorithm. The algorithm segments the entire genome using the HRD panel and provides an A and B allele estimate for each segment. After the TSO 500 pipeline determines CNV calls (using the TSO 500 panel), the segment covering the gene is identified, and the A and B allele numbers of the segment overlapping the gene are reported. If the gene is within 300 kbases from the segment boundary, the estimate is unreliable and “-1” is output. Absolute copy numbers are output in the Logs_Intermediates/Gis/SAMPLE/SAMPLE.abcn_annotated.vcf, Logs_Intermediates/Gis/SAMPLE/SAMPLE.abcn_genes.tsv and Combined Variant Output file.
This is a beta feature. Beta feature results are included in the Combined Variant Output file and other files. However, disclaimers that the results are generated by beta features are only provided in the Combined Variant Output file. Requires HRD add-on assay.
Gene-level loss of heterozygosity is calculated based on the minor copy number reported in the abcn_annotated.vc f. If the minor copy number is 0 then the gene is assumed to have a loss of heterozygosity. Gene-level loss of heterozygosity is output in the Logs_Intermediates/Gis/SAMPLE/SAMPLE.abcn_genes.tsv and Combined Variant Output file.
The software calculates several quality control metrics for runs and samples.
These metrics and guidelines apply to DRAGEN TSO 500 v2.1 and above.
The Run Metrics section of the metrics output report provides sequencing run quality metrics along with suggested values to determine if they are within an acceptable range. The overall percentage of reads passing filter is compared to a minimum threshold. For Read 1 and Read 2, the average percentage of bases ≥ Q30, which gives a prediction of the probability of an incorrect base call (Q‑score), are also compared to a minimum threshold. The following tables show run metric and quality threshold information for different systems.
The values in the Run Metrics section are listed as NA in the following situations:
If the analysis was started from FASTQ files.
If the analysis was started from BCL files and the InterOp files are missing or corrupt.
DRAGEN TruSight Oncology 500 uses QC metrics to assess the validity of analysis for DNA libraries that pass contamination quality control. If the library fails one or more quality metrics, then the corresponding variant type or biomarker is not reported, and the associated QC category in the report header displays FAIL. Additionally, a companion diagnostic result may not be available if it relies on QC passing for one or more of the following QC categories.
DNA library QC results are available in the MetricsOutput.tsv file.
The input for RNA Library QC is RNA alignment. Metrics and guideline thresholds can be found in the MetricsOutput.tsv file.
*To avoid failing RNA samples unnecessarily, Illumina does not recommend a universal threshold to determine RNA sample quality. RNA expression varies significantly across tissue types and a small panel size (55 genes), which makes normalization challenging. Tissue-specific thresholds could be considered for normalization.
All
All
Small variant TMB
MEDIAN_INSERT_SIZE
The median fragment length in the sample.
≥ 70
Small variant TMB
USABLE_MSI_SITES
The number of MSI sites usable for MSI calling.
≥ 40
MSI
MEDIAN_BIN_COUNT_CNV_TARGET
The median raw bin count per CNV target.
≥ 1.0
CNV
Fusion Splice
GENE_MEDIAN_COVERAGE*
The median deduped coverage across all genes in the RNA panel (55 genes).
N/A
Fusion Splice
PCT_PF_READS (%)
Total percentage of reads passing filter.
≥80.0
All
PCT_Q30_R1 (%)
Percentage of Read 1 reads with quality score ≥ 30.
≥80.0
All
PCT_Q30_R2 (%)
Percentage of Read 2 reads with quality score ≥ 30.
PCT_PF_READS (%)
Total percentage of reads passing filter.
≥55.0
All
PCT_Q30_R1 (%)
Percentage of Read 1 reads with quality score ≥ 30.
≥80.0
All
PCT_Q30_R2 (%)
Percentage of Read 2 reads with quality score ≥ 30.
PCT_Q30_R1 (%)
Percentage of Read 1 reads with quality score ≥ 30.
≥85.0
All
PCT_Q30_R2 (%)
Percentage of Read 2 reads with quality score ≥ 30.
≥85.0
All
PCT_Q30_R1 (%)
Percentage of Read 1 reads with quality score ≥ 30.
≥85.0
All
PCT_Q30_R2 (%)
Percentage of Read 2 reads with quality score ≥ 30.
≥85.0
All
CONTAMINATION_SCORE
The contamination score is based on VAF distribution of SNPs.
≤ 1457
All
MEDIAN_EXON_COVERAGE
Median exon fragment coverage across all exon bases.
≥ 150
Small variant TMB
PCT_EXON_50X
Percent exon bases with 50x fragment coverage.
MEDIAN_CV_GENE_500X
The median CV for all genes with median coverage > 500x. Genes with median coverage > 500x are likely to be highly expressed. Higher CV median > 500x indicates an issue with library preparation (poor sample input and/or probes pulldown issue).
<= 0.93
Fusion Splice
MEDIAN_INSERT_SIZE
The median fragment length in the sample.
≥ 80
Fusion Splice
TOTAL_ON_TARGET_READS
The total number of reads that map to the target regions.
≥80.0
≥80.0
≥ 90.0
≥ 9000000
LowQ
Splice variant score < passing quality score threshold value of 1.
PASS
Splice variant score ≥ passing quality score threshold value of 1.
LowUniqueAlignments
All splice junction supporting reads map to a unique genomic interval near at least one of the two splice sites.
Refer to the headers in the output for more information about each column.
If available, each splice variant is annotated using the Illumina Annotation Engine. The following information is captured in the JSON:
HGNC Gene
Transcript
Exons
Introns
Canonical
Consequence
The all fusions CSV file contains all candidate fusions identified by the DRAGEN RNA pipeline. Two output columns in the file describe the candidate fusions: Filter and KeepFusion.
The following table describes the semicolon-separated output found in the Filter columns. The output is either a confidence filter or information only as indicated. If none of the confidence filters are triggered, the Filter column contains the output PASS, else it contains the output FAIL.
Filter Column Output
DOUBLE_BROKEN_EXON
Confidence filter
If both breakpoints are distant from annotated exon boundaries, the number of supporting reads do not satisfy a high threshold requirement (≥ 10 supporting reads).
LOW_MAPQ
Confidence filter
All fusion supporting read alignments at either of the breakpoints have MAPQ < 20.
LOW_UNIQUE_ALIGNMENTS
Confidence filter
All fusion supporting read alignments map to a unique genomic interval at either of the breakpoints.
LOW_SCORE
Confidence filter
The KeepFusion column of the output has a value of TRUE when none of the confidence filters are triggered.
Refer to the headers in the output for more information about each column.
Fusion Columns
Gene A
The gene associated with the A side of the fusion. A semicolon delimited list is used for multiple genes.
Gene B
The gene associated with the B side of the fusion. A semicolon delimited list is used for multiple genes.
Gene A Breakpoint
[Information only] The chromosome and offset of the Gene A side of the fusion.
Gene A Location
Location of the breakpoint within Gene A: - IntactExon—Matches exon boundary - BrokenExon—Inside an exon - Intronic—Within an intron - Intergenic—No gene overlap (currently excluded) If multiple genes are in Gene A, then semicolon separated list of locations. This column is used internally to identify genes to report when a breakpoint occurs in a region overlapping multiple genes. Occasionally, additional values are listed for genes that were excluded from the GeneA list.
Gene A Sense
Boolean indicating whether left/right breakpoint order suggests fusion transcript is in the same sense of Gene A. If multiple genes are in Gene A, then semicolon separated list of bools.
Gene A Strand
Strand of Gene A, + for forward, - for reverse.
When using Microsoft Excel to view this report, genes that are convertible to dates (such as MARCH1 automatically convert to dd-mm format (1 Mar) by Excel. The following are fusion allow list genes:
ABL1
AKT3
ALK
AR
AXL
BCL2
BRAF
BRCA1
BRCA2
CDK4
CSF1R
EGFR
EML4
ERBB2
ERG
ESR1
ETS1
ETV1
ETV4
ETV5
EWSR1
FGFR1
FGFR2
FGFR3
FGFR4
FLI1
FLT1
FLT3
JAK2
KDR
KIF5B
KIT
KMT2A
MET
MLLT3
MSH2
MYC
NOTCH1
NOTCH2
NOTCH3
NRG1
NTRK1
NTRK2
NTRK3
PAX3
PAX7
PDGFRA
PDGFRB
PIK3CA
PPARG
RAF1
RET
ROS1
RPS6KB1
TMPRSS2
The fusion candidate has probabilistic score as determined by the features of the candidate.
MIN_SUPPORT
Confidence filter
The fusion candidate has very few fusion supporting reads (< 5 supporting read pairs).
READ_THROUGH
Confidence filter
The breakpoints are cis neighbors (< 200 kbp) on the reference genome.
ANCHOR_SUPPORT
Information only
Read alignments of fusion supporting reads are not long enough (12 bp) at either of the two breakpoints.
HOMOLOGOUS
Information only
The candidate is likely a false candidate generated because the two genes involved have high gene homology.
LOW_ALT_TO_REF
Information only
The number of fusion supporting reads is < 1% of the number of reads supporting the reference transcript at either of the two breakpoints.
LOW_GENE_COVERAGE
Information only
Each breakpoint in an enriched gene has fewer than 125 bp with nonzero read coverage.
NO_COMPLETE_SPLIT_READS
Confidence filter
For every fusion-supporting split read, the total number of aligned bases across two breakpoints is less 60% of the read length.
UNENRICHED_GENE
Confidence filter
Neither of the two parent genes is in the enrichment panel.
Gene B Breakpoint
[Information only] The chromosome and offset of the Gene B side of the fusion.
Gene B Location
Location of the breakpoint within Gene B: - IntactExon—Matches exon boundary - BrokenExon—Inside an exon - Intronic—Within an intron - Intergenic—No gene overlap (currently excluded) If multiple genes in Gene B, then semicolon separated list of locations. This column is used internally to identify genes to report when a breakpoint occurs in a region overlapping multiple genes. Occasionally, additional values are listed for genes that were excluded from the GeneB list.
Gene B Sense
Boolean indicating whether left/right breakpoint order suggests fusion transcript is in the same sense of Gene B. If multiple genes are in Gene B, then semicolon separated list of bools.
Gene B Strand
Strand of Gene B, + for forward, - for reverse.
Score
The quality of fusion as determined by DRAGEN server.
Filter
The filter associated with the fusion as determined by the respective caller. Results from different callers are not equivalent.
Ref A Dedup
Gene A uniquely mapping reads paired across or split by the junction. Does not support fusion. Duplicate reads are not included.
Ref B Dedup
Gene B uniquely mapping reads paired across or split by the junction. Does not support fusion. Duplicate reads are not included.
Alt Split Dedup
Uniquely mapping reads split by the junction. Supports fusion. Duplicate reads are not included.
Alt Pair Dedup
Uniquely mapping reads paired across junction. Supports fusion. Duplicate reads are not included.
KeepFusion
The determination whether the fusion should be kept or dropped from the list of fusions.
Fusion Directionality Known
Whether fusion directionality is known and indicated by gene order.
When the analysis run completes, the DRAGEN TruSight Oncology 500 Analysis Software generates an analysis output folder in a specified location.
To view analysis output, navigate to the analysis output folder and select the files that you want to view.
Single output folder structure is as follows.
Logs_Intermediates
AdditionalSarjMetrics— Contains per pair ID calculations to support the PCT_TARGET_250X metric.
Annotation—Contains outputs for small variant annotation.
Subfolders per sample ID—Contains the aligned small variants JSON.
Results
Metrics Output TSV (all pair IDs)
Pair ID—The following outputs are produced for each sample:
Multiple output folder structure is as follows.
Demultiplex Output
A Logs_Intermediates folder containing FASTQ files per sample.
Node(X) Output—The following outputs are produced for each node used:
This section describes each output folder generated during analysis and where to find metric and analytic files when the pipeline is executed. The same output folder structure and content exist in ICA and BaseSpace Sequence Hub.
Run ID
TSO500_Nextflow_logs
_manifest.json
The TSO_500_Nextflow_Logs provides information related to the execution of the pipeline on ICA as a whole and for specific nodes (when an analysis is split across multiple nodes). It contains files used to execute parts of the workflow on different nodes as well as records of the nextflow execution on those nodes.
TSO_500_Nextflow_Logs
_manifest.json
Contains the aggregated MetricsOutput.tsv file at the root level. Additionally, the Results folder contains a subfolder for each pair ID.
Results
MetricsOutput.tsv
Sample_1
The Results subfolder contains the following files:
Results
MetricsOutput.tsv
<Pair_id>
Contains folders for each submodule in the DRAGEN TSO 500 on ICA pipeline. The folders contain a copy of all the relevant files required to create the metric output files and report files, as well as the combined log files at the root level and subfolders for each sample.
Logs_intermediates
DnaDragenCaller
AdditionalSarjMetrics
Contains Errors.tsv. This file contains the summary of all the errors encountered during pipeline execution.
Errors
Errors.tsv
CombinedVariantOutput
Subfolders per pair ID—Contains the combined variant output TSV files.
A combined output log file.
Contamination
Subfolders per DNA sample ID—Contains the contamination metrics JSON file and output logs.
DnaDragenCaller
Subfolders per sample ID—Contains the aligned BAM and index files, small variant VCF and gVCF, copy number variant VCF, MSI JSON, and QC outputs in CSV format.
DnaDragenExonCNVCaller
Subfolders per DNA sample ID—Contains the exon-level CNV JSON,the supporting calculation, and the QC files.
DnaFastqValidation—Contains the FASTQ validation output log for DNA samples.
FastqDownsample
Subfolders per RNA sample ID—Contains FASTQ files and output logs.
FastqDownsample output
FastqGeneration
Gis—Contains GIS-related files for HRD samples.
Subfolders per HRD sample ID—Contains the GIS JSON, the supporting calculation, and the QC files.
Also contains the annotated CNV VCF and gene level TSV file with absolute copy number and minor copy number information
LrAnnotation
Subfolders per DNA sample ID—Contains the annotated exon-level CNV JSON.
LrCalculator
Subfolders per DNA sample ID—Contains the exon-level CNV VCF.
MetricsOutput
Subfolders per pair ID—Contains the metrics output TSV files.
A combined output log file.
ResourceVerification—Contains the resource file checksum verification logs.
RnaAnnotation
Subfolders per RNA sample ID—Contains the annotated splice variant JSON.
RnaDragenCaller
Subfolders per sample ID—Contains the aligned BAM, fusion candidates CSV and QC outputs in CSV format.
RnaFastqValidation—Contains the FASTQ validation output log for RNA samples.
RnaFusion
Subfolders per RNA sample ID—Contains the All Fusions CSV and Fusion Processor logs.
RnaQcMetrics
Subfolders per RNA sample ID—Contains the RNA QC metrics JSON.
RnaSpliceVariantCalling
Subfolders per RNA sample ID—Contains the splice variants VCF.
Run QC—Contains the Run QC metrics JSON, Intermediate Run QC metrics JSON, and log file.
SampleAnalysisResults
Subfolders per pair ID—Contains the Sample Analysis Results JSON and detailed log file.
SampleSheetValidation—Contains the Intermediate sample sheet and validation log.
Tmb
Subfolders per DNA sample ID—Contains the TMB metrics CSV, TMB trace TSV, and related files and logs. passing_sample_steps.json
—Contains the steps passed for each sample ID.
pipeline_trace.txt—Contains a summary and troubleshooting file that lists each Nextflow task executed and the status (for example, COMPLETED or FAILED).
run.log—Contains a complete trace-level log file describing the Nextflow pipeline execution.
run_report.html—Contains high-level run statistics (performance, usage, etc.)
run_timeline.html —Contains timeline-related information about the analysis run.
Metrics Output TSV
TMB Trace TSV
Small Variant Genome VCF
Small Variant Genome Annotated JSON
Copy Number Variant VCF
GIS JSON
MSI JSON
Large Rearrangements CNV VCF
Large Rearrangements CNV Annotated JSON
All Fusion CSV
Splice Variant VCF
Splice Variant Annotated JSON
A Logs_Intermediates folder containing step specific and component specific outputs and logs for every step/component run in the analysis pipeline for the sample run on the node.
A Results folder containing results only for the sample run on the node.
Gathered Output
A Logs_Intermediates folder containing step specific and component specific outputs and logs for every step/component run in each analysis pipeline on every node—this contains outputs for all samples and pairs ran across all nodes in the analysis.
A Results folder containing results for all samples and pairs ran across all nodes—results are organized by Pair_ID, then Sample_ID. This folder also contains summary files which contain information on all samples.
_tags.json
Logs_intermediates
Errors—This folder is only present when analysis fails
Sample_<#>
_tags.json
<SampleName>_MetricsOutput.tsv
<DNA_Sample_id>
CopyNumberVariants.vcf
DNAMergedSmallVariants_Annotated.json.gz
MergedSmallVariants.genome.vcf
MergedSmallVariants.vcf
microstat_output.json
TMB_Trace.tsv
<RNA_Sample_id>
AllFusions.csv
RNA_Annotated.json.gz
SpliceVariants.vcf
FastqGeneration
MetricsOutput
DnaDragenExonCnvCaller
DnaFastqValidation
Gis
Tmb
SampleAnalysisResults
SampleSheetValidation
passing_sample_steps.json
RnaFusion
Contamination
Annotation
RnaAnnotation
RnaDragenCaller
RnaSpliceVariantCalling
RunQc
FastqDownsample
PassingSampleSteps
ResourceVerification
LrCalculator
LrAnnotation
RnaQcMetrics
RnaFastqValidation