1 of 100

Illumina Connected Insights

Overview

Welcome

Illumina Connected Insights is a powerful software solution designed for interpretation and reporting of next-generation sequencing (NGS) data. The software accepts data from various DNA and RNA oncology assays and variant callers, supports variants frequently identified in tumor samples (e.g., SNVs, indels, CNVs, SVs, fusions, splice variants) and genome-wide biomarkers (e.g., TMB, MSI, GIS used to assess HRD), integrates multiple genomic databases to annotate data, providing insights into biological significance, and generates customized comprehensive summary reports.

Access Connected Insights

There are two ways to access Connected Insights:

Cloud

This deployment is hosted by Illumina.

🖊 Register your software

During the software registration process, you will need to create a domain and workgroup. Domains and Workgroups are used by Illumina Software to control access to your data and assets. When logging into Connected Insights, you will be required to select a workgroup to establish the context for your work.

🖥️ Log in

Once you have successfully set up your account and created your domain and workgroup, you can log in to Connected Insights. Follow the steps below.

Select your domain from the list.
Select the Illumina Connected Insights application tile from the Product Dashboard.
Select your workgroup from the menu. Once you select a workgroup, it will automatically be chosen during future logins.

Local

Install the software

🖥️ Log in

Navigate Connected Insights

Once you've logged in, click on a section below to help you navigate Connected Insights.

What's New

Other Oncology News

Cloud Software Update

What version am I using?

There are a few ways to find out which version you are using:

Navigate to the workgroup selector by clicking your workgroup name in the top right corner of the page and click Change Workgroup.

How do I upgrade to the next version?

If you wish to upgrade, follow these steps:

Decide which workgroups you want to transition to the new version and when. You can upgrade one, several or all of workgroups as convenient for your organization.
Then, a lab director user needs to:
1. Click your workgroup name in the top right corner of the page.
2. Click Change Workgroup.
3. Click the workgroup that you want to upgrade.
4. Click Next.
6. Click the Software Update tab.
7. Click Update. The workgroup will be upgraded to the next software version.
8. Repeat the above steps for each workgroup you want to upgrade.

Local Software Update

The Software Update page allows you to manage updating or initial installation of Connected Insights - Local software and the dependent packages. It provides details into the currently installed versions of software packages. Additionally, this page manages license updates, providing details on the last installed license date and the current remaining Genome Equivalent Sample (GEs) balance.

The following packages are supported:

Connected Insights - Local software: Updates only
Illumina Connected Annotations: Updates or initial installation
Illumina Connected Insight Data Reference: Updates or initial installation
Knowledge base files: Updates or initial installation
License file: Updates only

Install or Update software and dependent package

To install or update software or its dependent packages, refer to the instructions below:

From any page, click your username in the top right, select Administration Console, then Software Update. The Administration Console page is only accessible by Connected Insights - Local software users with an Administration role.
On the right-side pane, choose one of the options below based on where the packages are available:
- DRAGEN server v4 path /staging/icipackages/
- Mounted external storage drive (e.g. NAS) located at /mnt/<ici_mount>/icipackages/
- USB device connected and mounted to the DRAGEN server v4 (e.g., located in /media/usbinstall/)
- Local computer (only for Knowledge Base files and the license file). For this method, proceed to subsections Update Knowledge Base from Local Computer and Update License from Local Computer below.
❗ Before starting installation or updates, ensure only Connected Insights - Local software package(s) are available in one of the supported package locations specified above.
Click Check for Updates.
The application displays the compatible Connected Insights - Local software package(s) with an Install Now button next to each. Additionally, there is an Install All button which installs or updates all the dependent packages available within the selected location.
The Install All option is not provided when a higher version of Connected Insights - Local software package is available under the selected package location. In such cases, the Connected Insights - Local software must be installed followed by the dependent packages.
Select Install Now or Install All based on the options provided.
A confirmation pop-up will appear displaying the approximate time for installing or updating the selected package(s) and states the application will be inaccessible during this time.
Click Install Now in the confirmation pop-up.
❗ The application checks for the conditions below and only proceeds when the validations are successful. If one or multiple are not met, a pop-up window appears indicating the error and installation/updating will be blocked. Select Close, fix the conditions below, and try again.
- Package files integrity checks pass.
- No Case processing is in progress.
- /staging (on the DRAGEN server v4) has minimum of 200 GB free space.

If the validations above succeed, application starts the install or update process and displays the progress of package install/updates. During the install or update process, the application is inaccessible. After the install or update is completed, the screen refreshes to the Connected Insights - Local software login screen with a success message. Install or update any remaining packages if not done already.

If an update for an existing package fails, the application will automatically try to revert to the previous version of the package. You can then attempt to reinstall or re-upload the package from the Software Update page. If the rollback process also fails, the application will display an "Update Failed" message and restrict access to the application. For further troubleshooting contact Illumina Support.

Update Knowledge Base from Local Computer

The application allows you to install or update Knowledge Base files by uploading the files directly from user's personal computer. Refer to the instructions below:

From any page, click your username in the top right, select Administration Console, then Software Update. The Administration Console page is only accessible by Connected Insights - Local software users with an Administration role.
On the right-side pane, select the Local computer (only for Knowledge Base and license file) option.
Select the Knowledge Base file from your personal computer.
After the upload is complete, select Install.
A confirmation pop-up will appear displaying the approximate time for installing or updating the selected Knowledge Base package and states the application will be inaccessible during this time.
Click Install Now in the confirmation pop-up window.

❗ The application checks for the conditions below and only proceeds when the validations are successful. If one or multiple are not met, a pop-up window appears indicating the error and installation/updating will be blocked. Select Close, fix the conditions below, and try again.
Package files integrity checks pass.
No Case processing is in progress.
/staging (on DRAGEN server v4) has minimum of 200 GB free space.

If the validations above succeed, the application starts the install or update process and displays the progress. During the install or update process, the application is inaccessible. After the install or update is completed, the screen refreshes to the Connected Insights - Local software login screen with a success message.

Update License (ConnectedInsights-QuotaLicense.bin) from Local Computer

The application allows you to update Genome Equivalent Sample (GEs) balance by uploading the ConnectedInsights-local-QuotaLicense.bin file directly from user's personal computer. Download the license files sent by the Illumina Sales/Customer Support team on your personal computer and select ConnectedInsights-local-QuotaLicense.bin for this step. Refer to the instructions below:

From any page, click your username in the top right, select Administration Console, then Software Update. The Administration Console page is only accessible by Connected Insights - Local software users with an Administration role.
On the right-side pane, select the Local computer (only for Knowledge Base and license file) option.
Select the ConnectedInsights-local-QuotaLicense.bin license file.
After the upload is complete, select Install.

❗ The application checks for the conditions below when updating a license file and only proceeds when the validations are successful. If one or multiple are not met, a pop-up window appears indicating that the update cannot be installed. Select Close, fix the conditions below and try again.
The package file integrity checks pass.
The license file is intended for the target DRAGEN server v4.

If the above validation succeeds, the application proceeds to update the license and a success message is displayed. Upon successful License update, the amount of remaining GEs is refreshed to the current aggregated value under the License File section of the Software Update page.

Configure

Configuration

Overview

This page allows you to customize and optimize Connected Insights to suit your specific workflow and preferences. Here, you can configure various settings related to case management, data visualization, variant analysis, and report generation. By tailoring these options, you ensure that the tool aligns perfectly with your needs, enhancing efficiency and accuracy in your genetic analysis and reporting processes.

Getting Around

To navigate to the configuration page, click the ⚙ icon in the top right corner.

Typical Steps

The following steps are performed by a lab director user:

Step

Required

Default Provided

✔

Custom Case Data

The Custom Case Data page allows you to configure fields for case, subject, and sample information that accompanies cases in Connected Insights. The configuration covers field names, data type, restriction status, and the field category. When you upload the custom case data file, the fields in the file must be formatted to match the definition provided on this page. The information appears in the user interface on the Case Details screen and in the JSON and PDF reports in the corresponding sections.

To configure custom case data:

On the top toolbar, navigate to Configuration represented by the cog wheel icon.
Navigate to Case Data Definition.
In the right-side pane, select the Data Type from the drop-down list. This data type can be text, number, or a date. The type impacts the accepted inputs during data ingestion.
Enter a Custom Name. This name is the label that appears in the user interface and the PDF report.
Choose if you want this data to be Restricted from the drop-down list.
- Select Yes if the custom case data are sensitive. When you view the Case Details, the data are hidden with asterisks as indicators, and only displays if you select Show/Hide.
- If the data are non-sensitive, then select No.
Select Case, Subject, or Sample as the Associated Entity from the drop-down list. The corresponding data appears in the Case Details and on the PDF report.
Use the drag handles to change the order that data are displayed in Connected Insights and the final report.
Select Add to add the new custom case data definitions to the PDF report.
[Optional] Select the archive icon next to the custom case data definition to archive it so that it no longer appears on the final report.
[Optional] Select the X next to custom case data to remove an entry.

Pipeline and QC Configuration

Configure the pipeline metrics that appear on the report and edit the default values for each metric as follows.

On the top toolbar, select Configuration, and then select the General tab.
In the left-side pane, select Pipeline & QC Configuration.
Select the applicable pipeline. QC metric configurations display to the right of the selection.
Select Edit.
To add or remove metrics from the report, select the Add to Overview & Report toggle for each metric.
To edit specification limits for applicable metrics, select the Lower Spec Limit or Upper Spec Limit fields and enter the new value. If you cannot edit a value, NA replaces the field.
[Optional] To undo all of your changes, select Reset to Default Values.
Select Save. The updated metrics appear in the Lab QC tab of the case along with the Pass/Fail designations.

Preferred Transcripts

Upload the preferred transcript file as follows.

On the top toolbar, select Configuration, and then select the General tab.
Select Preferred Transcripts.
If there are no preferred transcripts, select Create One.
For Template File, select Upload and select your transcript file. You can also download a template to customize and upload as your preferred transcript file.
Select Open.
After the file displays, Select Save.
Select Download & View to download the transcript file.
[Optional] To upload an updated version of the file, select Upload New Version.

Custom Annotations

Custom Annotations allow you to annotate custom attributes (labels, scores, and population frequency) to variants or variants within a genomic region.

Create a new Custom Annotation file

Select the Test Components tab.
Navigate to Custom Annotations.
Select New.
Download the attached template.

The supported data categories for custom annotation in Connected Insights are as follows:

Filter: String labels
Score: Numeric values
AlleleFrequency: Allele frequency for population frequency data

Upload a new Custom Annotation file

Select the Test Components tab.
Navigate to Custom Annotations.
Select New.
Upload the file.

Download an existing Custom Annotation file

On the top toolbar, select Configuration, and then select the Test Components tab.
Select the Custom Annotations section.
Select the desired custom annotation.
Select Download.

Annotating Variants

Disease Configuration

The Disease Configuration section can be used to view, add, and edit the key genes associated with disease terms.

Add a New Disease Configuration

On the Configuration page, select the General tab.
Select Disease Configuration.
Select +New on the right side of the pane.
In the Disease Name field, type the disease name. This name can be based on a group of diseases or cancer types (for example, Bone).
In the Associated Disease Term(s) field, type a term (for example, Sarcoma).
Select the applicable term from the list that displays.
Make sure that the disease term displays under the field (for example, Sarcoma (SNOMEDCT: 1187396000)).
Under Key Genes, type a gene name in the field. You can enter one gene name per line, or multiple gene names separated by commas. A maximum of 250 names can be entered. The names are case-sensitive.
Select Save.

Update Disease Configuration

On the Configuration page, select the General tab.
Select Disease Configuration to expand the list of disease categories.
Select a disease (for example, Bone).
On the right side of the screen, select Edit.
Update the disease terms as follows. a. To add a disease term, type the term (for example, Sarcoma) in the Associated Disease Term(s) field. b. Select the applicable term from the list that displays. c. Make sure that the disease term displays under the field (for example, Sarcoma (SNOMEDCT: 1187396000)). d. To delete a disease term, select the X next to it. e. Select Save to accept any changes.
Update the key gene names as follows. a. For Key Genes, enter a gene name in the field. You can enter one gene symbol per line, or multiple gene names separated by commas. A maximum of 250 names can be entered. The names are case-sensitive. b. Select Save to accept any changes.
Update genome wide thresholds as follows. a. For Genome Wide Thresholds, enter values for the following Tumor Mutational Burden (mut/MB) thresholds:
- TMB-Low (the range starting point defaults to 0.0)
- TMB-High
  ❗ If there is a conflict between the low and high values, an error message displays indicating which value needs to be corrected.
b. Enter values for the following Microsatellite Instability (% unstable sites) thresholds:
- MS-Stable (the range starting point defaults to 0.0)
- MSI-High (the range end point defaults to 100)
c. Enter values for the following Global Instability Score thresholds:
- GIS-Low (the range starting point defaults to 0.0)
- GIS-High
d. Select Save to accept any changes.

Cancer Types with Key Genes

The following table shows the default key genes for select cancer types based on data provided by the Illumina Medical Affairs team.

Default Key Genes for Select Cancer Types

Cancer Type

Key Genes

Melanoma

BRAF, KIT, NRAS, NTRK1, NTRK2, NTRK3, TERT, GNAQ, GNA11, BAP1, SF3B1, EIF1AX, CDKN2A, BRCA2, PALB2, NF1, PTEN, CDK4, MC1R, MITF, MBD4

Prostate

ATM, BARD1, BRCA1, BRCA2, BRIP1, CDK12, CHEK2, FANCL, FGFR2, FGFR3, PALB2, PPP2R2A, RAD51B, RAD51C, RAD51D, RAD54L, NTRK1, NTRK2, NTRK3, ATR, EPCAM, ABRAXAS1, FANCA, GEN1, MLH1, MRE11, MSH2, MSH6, MUTYH, NBN, PMS2

Uterine and Cervical

ERBB2, ESR1, FOXO1, NCOA3, PAX3, PAX7, SMARCA4, SUZ12, NTRK1, NTRK2, NTRK3, ALK, ATRX, BCOR, CDK4, DICER1, FGFR2, GREB1, KMT2C, MDM2, MYBL1, NCOA2, CD274, PGR, PHF1, PIK3CA, PLAG1, RAD51B, RB1, TERT, TFE3, TP53, YWHAE, PTEN, POLE, MLH1, MSH2, MSH6, PMS2

Lung

ALK, BRAF, EGFR, ERBB2, KRAS, MET, NUTM1, RET, ROS1, NTRK1, NTRK2, NTRK3, CD274

Breast

BRCA1, BRCA2, ERBB2, ESR1, PIK3CA, NTRK1, NTRK2, NTRK3, CD274, PALB2, RAD51D, RAD51C, ATM, STK11, TP53, NF1, NBN, PTEN

Thyroid

BRAF, HRAS, KRAS, NRAS, RET, TERT, NTRK1, NTRK2, NTRK3, PAX8, PPARG, PTEN

Ovarian

BRCA1, BRCA2, FOXL2, NTRK1, NTRK2, NTRK3, ATM, BRIP1, MLH1, MSH2, PALB2, RAD51C, RAD51D, NBN, STK11

Colorectal

BRAF, ERBB2, KRAS, NRAS, NTRK1, NTRK2, NTRK3, MLH1, MSH2, MSH6, PMS2

CNS

ATRX, BRAF, EGFR, H3F3A, HIST1H3B, IDH1, IDH2, PTCH1, TERT, TP53, NTRK1, NTRK2, NTRK3, MGMT, PTEN

Bone

EWSR1, EGFR, ERG, ETV1, ETV4, FLI1, IDH1, NTRK1, NTRK2, NTRK3, FEV, IDH2, FUS

Other Solid (as a default for any other cancertypes)

ALK, APC, BCOR, BRAF, BRCA1, BRCA2, CDK4, CIC, CTNNB1, DNAJB1, ERBB2, EPCAM, ERG, ETV1, ETV4, ETV6, EWSR1, FGFR2, FGFR3, FOXO3, GLI1, IDH1, KIT, KRAS, MDM2, MLH1, MSH2, MSH6, MYOD1, NAB2, NTRK1, NTRK2, NTRK3, PAX3, PAX7, PDGFRA, PMS2, RANBP2, SDHB, SMARCB1, TFE3, WT1, YAP1, RET, ROS1, MET, IDH2

The following resources can be used to identify other actionable genes to expand your key genes with:

Restore Disease Configuration to Default Settings

On the Configuration page, select the General tab.
Select Disease Configuration.
Select ....
Select Restore to Default.
To confirm the action, select Yes,Restore to Default.
To confirm the action, select Yes, Delete.

Variant Filters

The Variant Filters section describes how to add, configure, duplicate, or archive variant filters.

Add and Configure a Variant Filter

On the top toolbar, select Configuration.
Select the Test Components tab.
Navigate to Variant Filters and select New.
Navigate to the Condition Group section and enter the applicable genes in the Genes field.
[Optional] Select the Include genes from diseases check box.
Select Apply.
Select Include or Exclude from the drop-down list for each gene.
For Variant Category, select the field to open up a drop-down list of variants that can be included or excluded.
Select the check boxes next to the applicable variant types.
Select Add Criteria and select the applicable criteria from the drop-down list (for example, Cancer Hotspot Samples).
Select Include or Exclude from the drop-down list for the criteria.
To include or exclude additional criteria, repeat steps 10 and 11.
For AND or OR, select Add Condition Group to add any other applicable condition groups.
[Optional] Select Reset to undo the changes to the condition groups.
Select Save.

Edit a Variant Filter

On the top toolbar, select Configuration.
Select the Test Components tab.
For Variant Filters, select a filter.
Select Edit.
Select Save.

Duplicate a Variant Filter

On the top toolbar, select Configuration.
Select the Test Components tab.
For Variant Filters, select the applicable filter.
In the right-hand pane, select Duplicate.
Select Save.

Archive a Variant Filter

On the top toolbar, select Configuration.
Select the Test Components tab.
For Variant Filters, select the applicable filter.
In the right-hand pane, select Archive.
To confirm, select Yes, change.

Default Filters

Connected Insights provides the following default filters to assist in preliminary test implementation:

Filter

Description

Pre-configured Demo Filter

Filters for rare coding small variants, copy number variants, unidirectional gene-fusions, and splice variants.

Pre-configured Small Variant Demo Filter

Filters for rare coding small variants.

Pre-configured CNV Demo Filter

Filters for CNVs.

Pre-configured Focal CNV Demo Filter

Filters for CNVs that exhibit a focal (>=7 CN, >3.5 FC, <2 CN, or <=0.5 FC) copy number change.

Pre-configured SV Demo Filter

Filters for unidirectional gene-fusions called via DNA data.

Pre-configured RNA Demo Filter

Filters for RNA splice variants and unidirectional gene-fusions.

Pre-configured TSO 500 RNA Demo Filter

Filters for RNA splice variants in AR / MET / EGFR and undirectional gene-fusions.

Pre-configured OVS1 + OP4 Demo Filter

Filters for rare gene disrupting small variants or splice variants in a known tumor suppressor gene.

Pre-configured AML Demo Filter

Filters for rare coding small variants, unidirectional gene-fusions, splice variants, and large ( >= 5 Mbp) structural / copy number variants in genes known to be involved in AML.

Variant Flag Groups

Variant flag groups allow you to organize variants later in the case interpretation. You can add flags for common tasks such as follow-up or to track review statuses.

On the top toolbar, select Configuration.
Select the Test Components tab.
In the left-hand pane, next to the Variant Flag Groups accordion, select New.
In the right-hand pane, enter a Variant Flag Group Name.
Enter a Flag Name.
Choose a flag color.
Select Add.
Create additional flags as needed.
Use the drag handles to change the order that data are displayed in Connected Insights and the final report.
Select Save. The variant flag group appears on the left-hand accordion menu. Select through the flag groups to display previews.
- Select Duplicate to duplicate a flag group.
- Select Archive to make the flag group unavailable when you create a test definition.

Actionability Classifications

Custom actionability classifications can be set up in Configuration. Later, when you create therapeutic, prognostic, and diagnostic assertions, you can specify these classifications.

Create custom actionability classifications as follows.

On the top toolbar, select Configuration.
In the General tab, select Actionability Classification. The default actionability classifications are based on AMP/ASCO/CAP Li et al, 2017. If you want to specify your own, select I want to classify using my own classifications.
Provide a name for the actionability classifications (for example, ESMO ESCAT).
Select Add.
Add a classification name (eg, Level 1).
[Optional] Add a description.
Choose a color.
Select Save.
Repeat steps 4–8 until you have your classification created.
- Classifications can be deleted by selecting x on the created classification.
- Classifications can be edited by selecting the pencil icon on the created classification.
Use the drag handles to map your classifications to the AMP/ASCO/CAP Li et al., 2017 guideline on the right side of the window. Place your classifications in order of their significance. After you create assertions, this order is used to prioritize variants and evidence.
❗ Whenever you edit these classifications, it does not modify existing assertions in your knowledge base or reports. When you encounter assertions using older classifications, they can be edited to use the latest classification.

Report Templates

Connected Insights requires you to provide a report template for each test definition to ensure consistency of reports produced across cases. This section summarizes the actions that can be performed with report templates to customize the look and content of PDF reports to your specifications.

Create several report templates and use them in more than one test definition.
Use a default report template provided by Connected Insights or customize the report as needed. These customizations include: – Changing the logo of the laboratory. – Changing the report name. – Reformatting the page and date. – Removing parts of the report related to the Nothing Reported section. This modification might be needed if the laboratory prefers not to report pertinent negatives. – Adding sample information alongside case and subject information. – Changing text in the Supplemental Information section.

Create a Report Template

On the top toolbar, select Configuration, and then select the Test Components tab.
Navigate to Report Templates and select New.
Select Download the template.
Save the base ODT template.
Select Upload template to re-upload the template with the recently made changes. Uploaded files must in the ODT format.
Select Confirm Report Creation when the report preview displays. Download the original report in the ODT format at any time. You can also archive and unarchive report templates. Archiving a report template makes it unavailable for use when creating a test definition.

Download Report Template

On the top toolbar, select Configuration, and then select the Test Components tab.
Select Report Templates, and then select Pre-configured Demo Report Template or Pre-configured Demo Report Template (Version 2).
After the report loads, select Download as ODT.

Test Changes After Report Template Customization

On the top toolbar, select Configuration, and then select the Test Components tab.
Navigate to Report Templates and select New.
For Create your new report, select Upload template.
Using file explorer, navigate to the template with the changes and select Open.
Review the PDF preview to make sure that the modified report displays as intended.

Customizations

The following applications can be used to customize the report:

LibreOffice v7.5 or later
Carbone Studio Illumina recommends using LibreOffice to customize the report. For more information on the customizations that can be done with LibreOffice, refer to the writer guide on the LibreOffice website. Carbone studio and its documentation are updated regularly. Please ensure any command used in an ODT is compatible with Carbone version 4.22.4 or earlier.

Use LibreOffice or an equivalent ODT editor to do common report customizations, including:

Changing the logo in the header.
Changing the report name.
Updating the date and time format.
Adjusting the font size and color.
Reordering and removing sections.
Inserting or removing information, such as single or aggregate data and the Genomic biomarkers table asterisk.
Changing the paper size.
Update Methodology Description and Gene List.
Show Findings by Tier

Change the Logo

Prepare the image file that is going to be inserted into the template.
- Make sure that the image is between 200 and 600 pixels so that it can fit within the header.
- Make sure that the image file size is less than 50 KB to avoid a delay in report generation.
Open the template in the ODT editor.
Replace the Laboratory image in the header as follows. a. Select the Laboratory image within the header of the first page. b. Replace the image with the formatted image from step 1. If you are using LibreOffice, right-click and select Replace. For more information on LibreOffice functions, refer to the writer guide on the LibreOffice website. The location and size are adjustable after the image is placed in the header.
❗ The default template includes a different header style for the first page and subsequent pages.
c. Select the image in the header of the second page. d. Replace the image with the formatted image from step1. If you are using LibreOffice, right-click and select Replace.
For more information on LibreOffice functions, refer to the writer guide on the LibreOffice website. This replacement causes the header image to change in subsequent pages.

Change the Report Name

Open the template in the ODT editor.
At the top of the template of the first page, replace the following text with the new report name: {d.reportData.reportLabels.report:ifEM():show('Report'):upperCase()}
❗ The default template includes different report name text for the first page and subsequent pages.
Repeat step 2 for the second page. This replacement causes the report name to change in subsequent pages.

Change Date and Time Format

Open the template in the ODT editor.
At the top of the template, find the following code that generates the report updated time text: {d.subjects[0].reports[0].reportDetails.updateDate:formatD('YYYY-MM-DD HH:mm')}
Replace YYYY-MM-DD HH:mm with the desired format (for example,YYYY-MM-DD).

Localize Time and Date

Open the template in the ODT editor.
Find and replace every instance of (UTC) with {d.reportData.localDates.timezone.shortName}. This will replace "UTC" with the local time zone abbreviated name (for example, "PT" for Pacific Time).
Find the following code that generates the updated date and time text: d.subjects[0].reports[0].reportDetails.updateDate
Replace every instance with d.reportData.localDates.reportUpdateDate
Find the following code that generates the report approval date and time text: d.reportData.reportHistory[i].approvedDate
Replace every instance with d.reportData.reportHistory[i].approvedDateLocal

Change Font Color and Size

Open the template in the ODT editor.
Change the font color and style using the font characteristics function for an individual text section.
❗ Color and size are changeable, but the font style and type cannot be altered.
[Optional] If you must update the font color and size for the whole document, adjust the paragraph style.

Reorder Sections

Open template in the ODT editor.
Identify the sections that must be rearranged.
Select and copy all relevant text or tables in that section.
❗ The sections of the template primarily consist of tables. Make sure that the entire table is selected when reordering a section. If you do not,then formatting issues can occur.
Enter a paragraph break between the sections where the copied section is being placed.
Paste the copied section to the new location.
Make sure that all of the information is present and formatted correctly.
Delete the original section.
Repeat steps 1–7 for any other sections that must be reordered.

Remove a Section

Open the template in the ODT editor.
Select the section of the report that you want to remove.
❗ The sections of the template primarily consist of tables. To remove the section, make sure that the entire table is selected. If you do not, then formatting issues can occur.
Delete the section.

Insert Information

Insert single data (for example, Methodology) or aggregate data as follows.

Open the template in the ODT editor.
Place the cursor where you want the new information to appear.
Add the applicable code or text used to generate new content or enter free text that you want to appear in all of the generated reports. For example, enter {d.createdDate:formatD('YYYY-MM-DD')} for the date the report was created or {d.reportData.therapies[]:aggCount} to add a count for the number of therapy assertions included in the report.

Remove the Genomic Biomarkers Table Asterisk (Remove Pertinent Negative)

Open the template (version 1) in the ODT editor.
Search for and delete the following line (use Ctrl+F to search): {$lbl.gbTableFooter:ifEM():show('*Contains disease related genes only')}
Search for the following and delete only the asterisk (*): ('Nothing reported')}*

Remove the Nothing Reported genes list

Open the template (version 2) in the ODT editor.
Search for the following line (use Ctrl+F to search): {$lbl.nothingReportedV2:ifEM():show('Nothing Reported')}
Use the ODT editor delete the table row containing the searched for text above.

Change Supplemental Information Description

Open the template in the ODT editor.
Search for supplemental information in the search field at the bottom of the template. You can also select Ctrl+F to search.
Make the desired edits. For more information on complex edits, refer to the ODT editor help documentation. The following edits are common:
- Change an existing term heading or its definition by updating the text within the single quotation marks for a given term or definition. For example, {$lbl.geneList:ifEM():show('Gene List')} can be changed to the following: {$lbl.geneList:ifEM():show('Genes Included In This Test')}
- Add static text (for example, laboratory contact information) by placing the cursor outside of the braces ({ }) where the status text begins. Then, type the text. If needed, press Enter to start a new line. Refer to the following example:
- Before editing:\
  {d.dataSourceVersions}{d.dataSourceVersions:ifEM():showBegin()}{$lbl.notProvided:ifEM():show('Not provided')}{d.dataSourceVersions :showEnd()}
- After editing:
  {d.dataSourceVersions}{d.dataSourceVersions:ifEM():showBegin()}{$lbl.notProvided:ifEM():show('Not provided')}{d.dataSourceVersions :showEnd()} Contact Information Name of Laboratory +1 (123) 555-1234 Email@Email.com

Change Paper Size

Open the template in the ODT editor.
Select each paragraph style and adjust the page size to the required size needed for printing.

Change Methodology Description and Gene List

Open the template in the ODT editor.
Search for and delete the following line (use Ctrl+F to search):{d.reportData.methodology.assayDescription:convCRLF()}
Replace line with desired methodology text used for the specified workflow. Example text can be found in the default PDF generated from a case in ICI.
Search for and delete the following line (use Ctrl+F to search):{d.reportData.methodology.assayGeneListText:convCRLF()}
Replace line with desired gene list.

Show Findings by Tier

The version 2 template can conditionally display findings at the beginning of the report based on the Tier/Actionability level. The default shows all levels in this section. To only display Tier I and Tier II (or equivalent).
Open the template in the ODT editor.
Search for the following line (use Ctrl+F to search):classification.actionabilityOrder:ifGTE(7.0)
Change 7.0 to 5.0 in the instances of the line.
Search for the following line (use Ctrl+F to search):classification.actionabilityOrder>6.9999
Change 6.9999 to 4.9999 in all instances of the line.

Report Automation

User-defined automation can add assertions from your knowledge base and/or other knowledge bases automatically to a draft report.

Automation only applies to cases using test definitions with automation turned on during case ingestion. Cases that were ingested before automation was turned on will not have assertions automatically added to their reports.

Automated assertions can be added for all types of variants with assertions in the supported knowledge bases, including the genome-wide biomarkers TMB, MSI, and GIS. Automation configuration settings determine which biomarkers are included in automation and which assertions for those biomarkers are added to the report.

Prerequisites

Before enabling automation, make sure that the following information is set up:

Variant Selection

Select either of the following sets of variants to be reported:

Variants that appear in a default filter and key genes (i.e., Key Findings of the Overview page).
Variants that appear in a default filter.

The following are not reported:

Any variant with a likely benign, benign, or likely neutral biological classification in a knowledge base (including My Knowledge Base and ClinVar).
TMB, MSI, and GIS with an unknown status.

Max number of variants eligible for automated reporting:

If variant selection is Variants that appear in default filter and key genes, only the first 25 variants with assertions in your default filters that are in key genes are eligible for automated reporting.
If variant selection is Variants that appear in default filter, only the first 25 variants with assertions in your default filters are eligible for automated reporting.

Knowledge Base Selection

You can select KBs you want to report assertions from. The following KBs are selectable:

My Knowledge Base
OncoKB
CKB
CIViC

You can also reorder KBs to prioritize assertions. Select and hold the icon to the left of the KB and move it up or down to reorder the KB list. Connected Insights uses the following information to prioritize which KB is used to report findings:

Order in the KB list (for example, if you move My Knowledge Base above CKB in the KB list, then My Knowledge Base is prioritized)
Case disease and assertion disease match (for example, if CKB is below My Knowledge Base in the KB list, but the case disease matches the CKB assertion disease, then CKB is prioritized)

Report Automation Setup

On the Configuration page, select the General tab.
Select Report Automation, and then select Edit.
Select one of the following Report a biomarker when options:
- Appears in a default filter and Key Genes (Key Findings)
- Appears in a default filter
Select applicable knowledge sources from the following Report findings from options:
- My Knowledge Base
- OncoKB
- CKB
- CIViC
Select Yes or No for the following questions:
- Report assertions previously reported only?
- Report therapeutic assertions with highest classification only, skipping anything in a lower classification?
- Report therapeutic assertions that indicate response or resistance only?
Select Save.

Test Definitions

Test Definitions allow you to specify default parameters that apply to cases when they are ingested. Make sure you have test components created, then create a test definition as follows.

On the top toolbar, select Configuration.
Select the Test Definitions tab.
Select New.
In the right-hand pane, enter a test name in the Test Name field.
Choose a human reference genome.
[Optional] Select one or more custom annotations (must be compatible for the selected human reference genome).
[Optional] Enter version comments as applicable.
Select Save. The new test definition appears on the left-hand accordion menu. Select a test definition to preview and access the following actions:
- Select Edit to edit a test definition.
- Select Copy as New Test to copy the definition as a template for a new test definition.
- Select Archive to hide the test definition from the PDF report.

Default Tests

Connected Insights provides the following default tests to assist in preliminary test implementation:

Test

Description

Pre-configured GRCh37 Demo Test

GRCh37 test that applies filters for DNA and RNA variants.

Pre-configured GRCh37 DNA Demo Test

GRCh37 test that applies filters for DNA variants.

Pre-configured GRCh37 RNA Demo Test

GRCh37 test that applies filters for RNA variants.

Pre-configured GRCh38 Demo Test

GRCh38 test that applies filters for DNA and RNA variants.

Pre-configured GRCh38 DNA Demo Test

GRCh38 test that applies filters for DNA variants.

Pre-configured GRCh38 RNA Demo Test

GRCh38 test that applies filters for RNA variants.

Pre-configured TSO 500 Demo Test

GRCh37 test that applies filters for DNA and RNA variants (limiting splice variants to AR, MET, EGFR).

Data Upload

This section describes how to upload data with Connected Insights and includes setup instructions. Connected Insights requires the following data types:

Secondary analysis output data — Connected Insights is compatible with a broad range of analysis pipeline outputs. To configure the input file format, select a compatible pipeline (for example, DRAGEN TruSight Oncology 500 v2.5.2) or configure a custom pipeline.

Connected Insights - Cloud allows data upload from the following sources:

Before uploading, create the following items:

Custom case data (if applicable)
Test components

Data Upload from User Storage (Connected Insights - Cloud and Connected Insights - Local)

Connected Insights - Cloud Data Uploader tool supports uploading of VCF files and analysis output for user-provided machines and storage devices and can be downloaded from Configuration -> Data Upload section of the application.

The secondary analysis input logs can be found /ExternalStorageDriveMountPath>/d53e4b2d-0428-4b3e-92bf-955f7153c360/d53e4b2d-0428-4b3e-92bf-955f7153c360/upload-logs/<DataUploadConfiguredMonitoringLocation>/<SecondaryAnalysisRunFolder>/run_<Timestamp>.json

Setup (Connected Insights - Cloud Only)

This section identifies the requirements for uploading data from user storage, enabling ingestion from the network drive, and adding an existing pipeline. For Connected Insights - Cloud, this section also covers how to download and install the Data Uploader tool and has instructions for generating an API key.

Requirements

To upload data from user storage, the following requirements must be met:

Make sure you have Java 8 or a newer version installed on your computer. You can check by opening a terminal or command prompt and typing java -version. If you don't have it installed, you can download and install it from the official Java website.
Data Uploader with Java Virtual Machine (JVM) 8+ that is compatible with Mac, Windows, or Linux CentOS.
Administrator access on the computer where Data Uploader is installed.

Before you begin, perform the following actions:

Create custom case data.
Create test components.
Create test definitions.

Download and Install Data Uploader

Download and install the Data Uploader tool as follows.

In Connected Insights, select the gear at the top right of the page.
In the General tab, under Data Upload, select the From Local Storage tab.
Under Download and Launch the Data Uploader, select the storage device operating system from the drop-down list.
Select Download Data Uploader. A progress bar displays during the download.
Copy the installation directory of the storage device. Make sure that Data Uploader is in a location that has access to your secondary analysis output folder.
Use the following tar command to extract the files: Replace {ici uploader script} with the applicable file name. tar xvzf {ici uploader script}.tar.gz
❗ Extracting files can vary depending on the operating system. Most terminals support the tar command. For Windows, you can use a zip file extraction application (eg, 7-Zip) to extract the content of the tar folder.
Make sure that the files in the following table are in the unzipped Data Uploader file.
Install Data Uploader as follows:
a. [Windows] Start the command prompt as an administrator and run ici-uploader.exe install.
❗ For windows environment, user must be in the installation directory to install/uninstall the application. ici-uploader.exe start-daemon
b. [Mac and Linux] Run the following command on the terminal ./ici-uploader install
❗ If the installation fails, start the Connected Insights installation manually using ici-uploader start-daemon
c. Follow any prompts in Data Uploader. d. Enter your API key and press Enter.
e. Under Define and Monitor Data Uploads, make sure that your machine displays. Data Uploader is now set up for auto and manual ingestion. You can also change the name of the installed Data Uploader by selecting ... and Edit Server Name . If you must download any logs associated with the Data Uploader from the last 24 hours, select ... and Download Logs.
❗ If the user is not a system administrator, the daemon can be started with the ici-uploader start-daemon command for Mac/Linux or with the ici-uploader.exe start-daemon command for Windows. This command does not run the process as a system service and requires you to start and stop the service manually. To stop the daemon, run the command ici-uploader stop-daemon
After Data Uploader has been downloaded and installed on the user storage, you can set up configurations for the tool to upload data into Connected Insights automatically. Each configured pipeline monitors user storage for new molecular data.

Running Data Uploader as Service

If user has admin access, ici-uploader is installed as a system service. User can stop the ici-uploader (running as system service) using the following command ici-uploader stop-service command for Mac/Linux or with the ici-uploader.exe stop-service command for Windows. User can start the uploader via ici-uploader start-service.

❗If data-uploader is already running as system-service, and user also runs the uploader manually via ici-uploader start-daemon, it may cause issues. User must stop already running data-uploader with ici-uploader stop-service before starting uploader manually.

Installing newer version of Data Uploader

Before installing the new version of the Data Uploader, the user must first uninstall the existing version. If they attempt to install without uninstalling, they will encounter the following error.
❗ [ERROR ici_uploader] Unable to start ICI Data Uploader because a daemon is already running ...
To uninstall, run the following command:
a. [Windows] Start the command prompt as an administrator and run ici-uploader.exe uninstall.
❗ For windows environment, user must be in the installation directory to uninstall the application. When prompted with message this operation will remove all contents from the folder. Are you sure to proceed?, press Y.
b. [Mac and Linux] Run the following command on the terminal ./ici-uploader uninstall
❗ When prompted with message this operation will remove all contents from the folder. Are you sure to proceed?, press Y.

Enable Upload from Network Drive (Connected Insights - Cloud)

If you are using Linux, automatic case upload is already enabled and this section is not applicable. For Mac, contact Illumina Technical Support. For Windows, run the "illumina ICI Auto Launch Service" to make the network drive available for Data Uploader as follows:

When the Data Uploader is running, open the Services application from the Start menu and locate the "illumina ICI Auto Launch Service".
Right-click "illumina ICI Auto Launch Service" and select Properties from the drop-down menu.
In Properties, select the Log On tab and enter your account ID and password. Confirm the password.
Select the General tab.
Select Stop, then select Start to start the service. The network drive is available for ingestion for Data Uploader.

After completing these steps, the Data Uploader details are visible in Connected Insights.

Enable Ingestion from Proxy Server Setting

If the computer where the Data uploader is installed is behind a proxy server, then Uploader proxy setting must be enabled. Before you install the Data Uploader, run the following command on the terminal (Linux).

❗ export JDK_JAVA_OPTIONS='-Dhttps.proxyHost=<IP address of the proxy server e.g. 1.2.3.4> -Dhttps.proxyPort=<Port of the proxy server e.g. 8080>'

For Windows, it can be set via following command.

❗ setx JDK_JAVA_OPTIONS "-Dhttps.proxyHost=<IP Address of the proxy server e.g. 1.2.3.4> -Dhttps.proxyPort=<Port of the proxy server e.g. 8080>"

Remember to replace and with the actual values you need.

Select Compatible Pipeline

Select a pipeline from the drop-down list (for example, DRAGEN TruSight Oncology 500 Analysis Software v2.5.2).
❗ When running the DRAGEN Somatic Whole Genome pipeline in the Tumor-Only mode, you must set --output-file-prefix to match sample-id (the RGSM of the sample in the FASTQ list) of the run.
For Test Definition, select the applicable definition.
For Choose a folder to monitor for case metadata (optional), enter the path for the folder in the secondary analysis folder created by Data Uploader.
Select Save.

Generate an Api Key

If you are using Data Uploader for the first time, then you must generate a new API key. All Data Uploader operations require an API key for authentication. The Data Uploader bundle can be downloaded with an autogenerated API key. If the bundle includes an API key, skip this section.

❗ If you are installing Data Uploader on multiple machines, manually create and track your API key by running the following auto-updating and manual run command:

ici-uploader configure --api-key={apiKey} Make sure that the API key is within single quotation marks (for example,'{SYSTEM_API-KEY}')

In Connected Insights, select Manage API Keys from the Account drop-down menu.
Select Generate.
Enter a name for the API key.
To generate a global API key, select All workgroups and roles.
Select Generate.
In the API Key Generated window, select one of the following options:
- Show — Reveals the API key.
- Download API Key — Downloads the API key in .TXT file format.
Select Close after you have stored the API key.
❗ The API key cannot be viewed again after closing this window. Download the API key or save it in a secure location.
The API key is added to the Manage API keys list.
Perform any of the following actions in the Manage API Keys list:
- Select Regenerate to generate a new API with the existing API key name.
- Select Edit to edit the API key name or change the workgroups and roles selection.
- Select Delete to delete the API key.

Automation of Data Upload from User Storage ( Connected Insights - Cloud and Connected Insights - Local )

The following information is applicable to both Connected Insights - Local and Connected Insights - Cloud. Create each configuration as follows.

Input the {monitoring location} for secondary analysis output.
- The monitoring location is the full path to the location where secondary analysis output data is deposited in user's storage.
  - For example: /rest/of/storage path/{monitoring location}/{runFolder}/{sample folders, sample sheet, inputs, tumor_fastq_list.csv}
  - For DRAGEN server v4 standalone results: /rest/of/storage path/{monitoring location}/{sample name folders}/{sample sheet, inputs, VCFs, .bams}
Select Save to complete the configuration. If Data Uploader is running, it monitors this configuration for data upload.

Perform any of the following actions below:

Edit You can modify the pipeline configuration by clicking "Edit" against a configuration.

Note: The change in configuration does not impact the Case that are already ingested.

Delete You can delete the pipeline configuration by clicking "Delete" against a configuration.

Requeue (Connected Insights - Local) You can resume or reupload a secondary analysis output folder by clicking "Requeque" against a configuration. Upon clicking "Requeue", application will re-attempt to create the case from the run folders which previoulsy failed due to one of the below errors:

SampleSheet validation error
Case ingestion has stopped due to zero GEs balance
Case ingestion has stopped due to low space on external mounted storage or /staging

On-Demand Data Upload from User Storage (Connected Insights - Cloud Only)

Upload an analysis output by running the following command: ici-uploader analysis upload --folder={path-to-analysis} --pipeline-name={pipelineName}
- --folder {path-to-analysis} — The absolute path to the analysis output to upload into Connected Insights. This folder contains the sample sheet.
- --pipeline-name={pipelinename} — The name of the pipeline created in Connected Insights to apply to cases uploaded from this analysis. Pipeline names must include only letters, numbers, underscores, and dashes. The name cannot include spaces or special characters.
- [Optional] --runId={path-to-config} — The id of the run to be created in place of the run ID determined by the run folder name.
- [Optional] --pair-id={pair-id} — The pair-id of the analysis to upload from the Sample Sheet when limiting upload to a single analysis.
- [Optional] --case-display-id={case-display-id} — The id of the case to be created in place of the pair-id when uploading a single analysis with --pair-id={pair-id}.
- [Optional] ici-uploader logs show — Run to display the logs in ICI_Data_Upload_log.json.
- [Optional] Downloads > ici-uploader logs download — Download Data Uploader logs in a zipped folder by running the command prompt.
Upload the custom case data file associated to one or more cases by running the following command: ici-uploader case-data --filePath={absolute-path-of-csv-file}

Case Processing Performance (Connected Insights - Local Only)

The following table shows the approximate time it takes for example datasets to upload and receive the Ready for Interpretation status. The duration is evaluated by analyzing a batch of samples ingested through the Connected Insights tertiary analysis in conjunction with the DRAGEN secondary analysis performed on similar datasets on the DRAGEN server v4.

Data Upload from ICA or BSSH (Connected Insights - Cloud)

Connected Insights - Cloud supports data uploads from Connected Analytics (ICA) and BaseSpace Sequence Hub (BSSH) for defined workflows.

Requirements

ICA

BSSH

You must be a member of the workgroup to which the data is uploaded in both Connected Insights and BSSH. The user must have permission at the level of Has Access in BSSH to be accessible from Connected Insights.

Configure Auto-pickup for a Supported Illumina Connected Analytics Pipeline

This section provides instructions for adding a supported ICA pipeline.

In Connected Insights, select the gear in the top-right corner to open the Configuration page.
Select the General tab.
Select Data Upload.
Select the From Illumina Connected Analytics tab.
For Cloud Pipelines, select Add.
For Test Definition, select the applicable definition.
Select Save.

ℹ️ For the configured Illumina Connected Analytics Pipeline, Connected Insights will automatically upload new analyses in ICA for the specified workflow. When data is uploaded, the status to the right of the workflow name will show the last analysis upload date. If a new project is created or linked after the configuration is made, it will need to be refreshed by editing and saving the configuration before it will begin to pick-up data from that project.

Disable Auto-pickup for a Configured Illumina Connected Analytics Pipeline

Locate the pipeline, and then select ...
Select Delete.
When prompted, select Yes, Remove.

Manual Upload for a Supported Illumina Connected Analytics Pipeline

This section provides instructions for manually uploading a completed analysis for a supported ICA pipeline.

From the Case List, select + New Case.
Select the Import from Connected Analytics option and click the button for Import from Connected Analytics.
Ensure the correct project is selected under Select Project.
Select the desired analysis to upload and click the button to Continue.
Click Review.
Review the information and click Submit to begin processing the selected analysis.

❗ The user must first configure the pipeline in Data Upload Configuration, see above, before manually uploading analyses from ICA.

Upload Data from Illumina Connected Analytics with API

Manual Upload for a Supported BaseSpace Sequence Hub Pipeline

This section provides instructions for manually uploading a completed analysis for a supported BSSH pipeline.

From the Case List, select + New Case.
Select the Import from BaseSpace Sequence Hub option and click the button for Import from BaseSpace Sequence Hub.
Select the desired analysis to upload and click the button to Continue.
Select the desired test definition to apply to the selected analysis.
[Optional] Select a case metadata file to upload (up to five files may be uploaded at one time), refer to Custom Case Data Upload
Click Review.
Review the information and click Submit to begin processing the selected analysis.

Linking Data Between Projects in Illumina Connected Analytics

To use analysis data from one project (Project A) in another project (Project B), follow these steps:

Ensure that the workgroup has access to Project A.
Note down the folder ID or folder path of the data you want to access in Project B.
In Project B, click on "Data" in the side navigation.
Click on the "Link" menu.
Search by the folder ID or folder path, and click on "Link".

This process will take a few minutes. Once the job is complete, you will be able to access the data from Project A in Project B.

Supported Pipelines

Connected Insights directly supports the following pipelines:

Pipeline Name and YAML

Support (Local Storage / ICA)

Local Storage

Local Storage and ICA

Local Storage

Local Storage and ICA

Local Storage

Local Storage and ICA

Local Storage

Local Storage and ICA

Local Storage

For additional information about DRAGEN TruSight Oncology 500 and other DRAGEN Applications refer to:

DRAGEN TruSight Oncology 500 Analysis Software v2.6.0 (with HRD)

pipeline:
  type: TSO500
  successMarkerFile: Logs_Intermediates/MetricsOutput/MetricsOutput.tsv
  failureMarkerFile: ./failure.txt

sampleSheet:
  filePath: SampleSheet.csv

jointFiles:
  purityPloidyFiles: Logs_Intermediates/CombinedVariantOutput/{pairId}/{pairId}_CombinedVariantOutput.tsv, Optional
  gisFile: Logs_Intermediates/Gis/{sampleId.DNA}/{sampleId.DNA}.gis.json, Optional
  msiFile: Logs_Intermediates/DnaDragenCaller/{sampleId.DNA}/{sampleId.DNA}.microsat_output.json, Optional
  tmbFile: Logs_Intermediates/Tmb/{sampleId.DNA}/{sampleId.DNA}.tmb.metrics.csv, Optional
  lohFiles:
    - Logs_Intermediates/Gis/{sampleId.DNA}/{sampleId.DNA}.abcn_genes.tsv, Optional    
  snvFiles: Logs_Intermediates/DnaDragenCaller/{sampleId.DNA}/{sampleId.DNA}.hard-filtered.vcf.gz, Optional
  cnvFiles:
    - Logs_Intermediates/Gis/{sampleId.DNA}/{sampleId.DNA}.abcn_annotated.vcf, Optional
    - Logs_Intermediates/LrCalculator/{sampleId.DNA}/{sampleId.DNA}_DragenExonCNV.vcf, Optional
    - Logs_Intermediates/DnaDragenCaller/{sampleId.DNA}/{sampleId.DNA}.cnv.vcf.gz, Optional
  rnaSpliceFiles: Logs_Intermediates/RnaSpliceVariantCalling/{sampleId.RNA}/{sampleId.RNA}_SpliceVariants.vcf, Optional
  rnaFusionFiles:
    - Logs_Intermediates/RnaDragenCaller/{sampleId.RNA}/{sampleId.RNA}.fusion_candidates.vcf.gz, Optional
    - Logs_Intermediates/RnaFusion/{sampleId.RNA}/{sampleId.RNA}_AllFusions.csv, Optional
  metricsQCFile: Logs_Intermediates/MetricsOutput/MetricsOutput.tsv

sampleFiles:
  tumorPairId:
    visualizationFiles:
      coverageFiles: Logs_Intermediates/DnaDragenExonCnvCaller/{sampleId.DNA}/{sampleId.DNA}.target.counts.gc-corrected.gz, Optional
      ballelesFiles: Logs_Intermediates/Gis/{sampleId.DNA}/{sampleId.DNA}.baf.bedgraph.gz, Optional
    alignmentFiles:
      dnaBamFile: Logs_Intermediates/DnaDragenCaller/{sampleId.DNA}/{sampleId.DNA}.bam, Optional
      dnaBaiFile: Logs_Intermediates/DnaDragenCaller/{sampleId.DNA}/{sampleId.DNA}.bam.bai, Optional
      rnaBamFile: Logs_Intermediates/RnaDragenCaller/{sampleId.RNA}/{sampleId.RNA}.bam, Optional
      rnaBaiFile: Logs_Intermediates/RnaDragenCaller/{sampleId.RNA}/{sampleId.RNA}.bam.bai, Optional

DRAGEN TruSight Oncology 500 Analysis Software v2.6.0

DRAGEN TruSight Oncology 500 Analysis Software v2.5.3 (with HRD)

pipeline:
  type: TSO500
  successMarkerFile: Logs_Intermediates/MetricsOutput/MetricsOutput.tsv
  failureMarkerFile: ./failure.txt

sampleSheet:
  filePath: SampleSheet.csv

jointFiles:
  purityPloidyFiles: Logs_Intermediates/CombinedVariantOutput/{pairId}/{pairId}_CombinedVariantOutput.tsv, Optional
  gisFile: Logs_Intermediates/Gis/{sampleId.DNA}/{sampleId.DNA}.gis.json, Optional
  msiFile: Logs_Intermediates/DnaDragenCaller/{sampleId.DNA}/{sampleId.DNA}.microsat_output.json, Optional
  tmbFile: Logs_Intermediates/Tmb/{sampleId.DNA}/{sampleId.DNA}.tmb.metrics.csv, Optional
  lohFiles:
    - Logs_Intermediates/Gis/{sampleId.DNA}/{sampleId.DNA}.abcn_genes.tsv, Optional    
  snvFiles: Logs_Intermediates/DnaDragenCaller/{sampleId.DNA}/{sampleId.DNA}.hard-filtered.vcf.gz, Optional
  cnvFiles:
    - Logs_Intermediates/Gis/{sampleId.DNA}/{sampleId.DNA}.abcn_annotated.vcf, Optional
    - Logs_Intermediates/LrCalculator/{sampleId.DNA}/{sampleId.DNA}_DragenExonCNV.vcf, Optional
    - Logs_Intermediates/DnaDragenCaller/{sampleId.DNA}/{sampleId.DNA}.cnv.vcf.gz, Optional
  rnaSpliceFiles: Logs_Intermediates/RnaSpliceVariantCalling/{sampleId.RNA}/{sampleId.RNA}_SpliceVariants.vcf, Optional
  rnaFusionFiles:
    - Logs_Intermediates/RnaDragenCaller/{sampleId.RNA}/{sampleId.RNA}.fusion_candidates.vcf.gz, Optional
    - Logs_Intermediates/RnaFusion/{sampleId.RNA}/{sampleId.RNA}_AllFusions.csv, Optional
  metricsQCFile: Logs_Intermediates/MetricsOutput/MetricsOutput.tsv

sampleFiles:
  tumorPairId:
    visualizationFiles:
      coverageFiles: Logs_Intermediates/DnaDragenExonCnvCaller/{sampleId.DNA}/{sampleId.DNA}.target.counts.gc-corrected.gz, Optional
      ballelesFiles: Logs_Intermediates/Gis/{sampleId.DNA}/{sampleId.DNA}.baf.bedgraph.gz, Optional
    alignmentFiles:
      dnaBamFile: Logs_Intermediates/DnaDragenCaller/{sampleId.DNA}/{sampleId.DNA}.bam, Optional
      dnaBaiFile: Logs_Intermediates/DnaDragenCaller/{sampleId.DNA}/{sampleId.DNA}.bam.bai, Optional
      rnaBamFile: Logs_Intermediates/RnaDragenCaller/{sampleId.RNA}/{sampleId.RNA}.bam, Optional
      rnaBaiFile: Logs_Intermediates/RnaDragenCaller/{sampleId.RNA}/{sampleId.RNA}.bam.bai, Optional

DRAGEN TruSight Oncology 500 Analysis Software v2.5.3

DRAGEN TruSight Oncology 500 Analysis Software v2.1.1 (with HRD)

pipeline:
  type: TSO500
  successMarkerFile: Logs_Intermediates/MetricsOutput/MetricsOutput.tsv
  failureMarkerFile: ./failure.txt

sampleSheet:
  filePath: SampleSheet.csv

jointFiles:
  purityPloidyFiles: Logs_Intermediates/CombinedVariantOutput/{pairId}/{pairId}_CombinedVariantOutput.tsv, Optional
  gisFile: Logs_Intermediates/Gis/{sampleId.DNA}/{sampleId.DNA}.gis.json, Optional
  msiFile: Logs_Intermediates/DnaDragenCaller/{sampleId.DNA}/{sampleId.DNA}.microsat_output.json, Optional
  tmbFile: Logs_Intermediates/Tmb/{sampleId.DNA}/{sampleId.DNA}.tmb.metrics.csv, Optional
  snvFiles: Logs_Intermediates/DnaDragenCaller/{sampleId.DNA}/{sampleId.DNA}.hard-filtered.vcf.gz, Optional
  cnvFiles:
    - Logs_Intermediates/DnaDragenCaller/{sampleId.DNA}/{sampleId.DNA}.cnv.vcf.gz, Optional
    - Logs_Intermediates/LrCalculator/{sampleId.DNA}/{sampleId.DNA}_DragenExonCNV.vcf, Optional
  rnaSpliceFiles: Logs_Intermediates/RnaSpliceVariantCalling/{sampleId.RNA}/{sampleId.RNA}_SpliceVariants.vcf, Optional
  rnaFusionFiles:
    - Logs_Intermediates/RnaDragenCaller/{sampleId.RNA}/{sampleId.RNA}.fusion_candidates.vcf.gz, Optional
    - Logs_Intermediates/RnaFusion/{sampleId.RNA}/{sampleId.RNA}_AllFusions.csv, Optional
  metricsQCFile: Logs_Intermediates/MetricsOutput/MetricsOutput.tsv

sampleFiles:
  tumorPairId:
    visualizationFiles:
      coverageFiles: Logs_Intermediates/DnaDragenExonCnvCaller/{sampleId.DNA}/{sampleId.DNA}.target.counts.gc-corrected.gz, Optional
    alignmentFiles:
      dnaBamFile: Logs_Intermediates/DnaDragenCaller/{sampleId.DNA}/{sampleId.DNA}.bam, Optional
      dnaBaiFile: Logs_Intermediates/DnaDragenCaller/{sampleId.DNA}/{sampleId.DNA}.bam.bai, Optional
      rnaBamFile: Logs_Intermediates/RnaDragenCaller/{sampleId.RNA}/{sampleId.RNA}.bam, Optional
      rnaBaiFile: Logs_Intermediates/RnaDragenCaller/{sampleId.RNA}/{sampleId.RNA}.bam.bai, Optional

DRAGEN TruSight Oncology 500 ctDNA Analysis Software v2.5.0

Local Installation Guide

Manage cases

Interpret and report

Data Upload from User Storage (Connected Insights - Cloud and Connected Insights - Local)

Connected Insights - Local Connected Insights - Local includes the Data Uploader tool that is installed on the DRAGEN server v4 as part of the Connected Insights - Local installation and reads secondary analysis results from the external storage drive that is configured. The Data Uploader tool is detected and identified as Default-CLI-Installation in the Data Upload section of the Configuration page. If Default-CLI-Installation does not show as Online, refer to .

The Data Uploader logs can be found at /staging/ici/logs/tss-cli/. With Connected Insights - Local, these logs can also be downloaded from the Activity tab in the Case Details pane on the Cases page. For more information, refer to .

Setup (Connected Insights - Cloud Only)

Requirements

To upload data from user storage, the following requirements must be met:

Make sure you have Java 8 or a newer version installed on your computer. You can check by opening a terminal or command prompt and typing java -version. If you don't have it installed, you can download and install it from the official Java website.
Data Uploader with Java Virtual Machine (JVM) 8+ that is compatible with Mac, Windows, or Linux CentOS.
An API key and access to the workgroup to which the data is uploaded. The API key comes with the installer. To generate a newAPI key, refer to .
Administrator access on the computer where Data Uploader is installed.

Before you begin, perform the following actions:

Create custom case data.
Create test components.
Create test definitions.

For more information, refer to .

Download and Install Data Uploader

Download and install the Data Uploader tool as follows.

In Connected Insights, select the gear at the top right of the page.
In the General tab, under Data Upload, select the From Local Storage tab.
Under Download and Launch the Data Uploader, select the storage device operating system from the drop-down list.
Select Download Data Uploader. A progress bar displays during the download.
Copy the installation directory of the storage device. Make sure that Data Uploader is in a location that has access to your secondary analysis output folder.
Use the following tar command to extract the files: Replace {ici uploader script} with the applicable file name. tar xvzf {ici uploader script}.tar.gz
❗ Extracting files can vary depending on the operating system. Most terminals support the tar command. For Windows, you can use a zip file extraction application (eg, 7-Zip) to extract the content of the tar folder.
Make sure that the files in the following table are in the unzipped Data Uploader file.
Install Data Uploader as follows:
a. [Windows] Start the command prompt as an administrator and run ici-uploader.exe install.
❗ For windows environment, user must be in the installation directory to install/uninstall the application. ici-uploader.exe start-daemon
b. [Mac and Linux] Run the following command on the terminal ./ici-uploader install
❗ If the installation fails, start the Connected Insights installation manually using ici-uploader start-daemon
c. Follow any prompts in Data Uploader. d. Enter your API key and press Enter.
❗ If you did not download with an auto-generated API key, provide one to the installer when prompted. If you are installing Data Uploader for the first time, you must generate an API key. For more information, refer to .
e. Under Define and Monitor Data Uploads, make sure that your machine displays. Data Uploader is now set up for auto and manual ingestion. You can also change the name of the installed Data Uploader by selecting ... and Edit Server Name . If you must download any logs associated with the Data Uploader from the last 24 hours, select ... and Download Logs.
❗ If the user is not a system administrator, the daemon can be started with the ici-uploader start-daemon command for Mac/Linux or with the ici-uploader.exe start-daemon command for Windows. This command does not run the process as a system service and requires you to start and stop the service manually. To stop the daemon, run the command ici-uploader stop-daemon
After Data Uploader has been downloaded and installed on the user storage, you can set up configurations for the tool to upload data into Connected Insights automatically. Each configured pipeline monitors user storage for new molecular data.

Running Data Uploader as Service

❗If data-uploader is already running as system-service, and user also runs the uploader manually via ici-uploader start-daemon, it may cause issues. User must stop already running data-uploader with ici-uploader stop-service before starting uploader manually.

Installing newer version of Data Uploader

Before installing the new version of the Data Uploader, the user must first uninstall the existing version. If they attempt to install without uninstalling, they will encounter the following error.
❗ [ERROR ici_uploader] Unable to start ICI Data Uploader because a daemon is already running ...
To uninstall, run the following command:
a. [Windows] Start the command prompt as an administrator and run ici-uploader.exe uninstall.
❗ For windows environment, user must be in the installation directory to uninstall the application. When prompted with message this operation will remove all contents from the folder. Are you sure to proceed?, press Y.
b. [Mac and Linux] Run the following command on the terminal ./ici-uploader uninstall
❗ When prompted with message this operation will remove all contents from the folder. Are you sure to proceed?, press Y.
Download the latest version of the Data Uploader.

Enable Upload from Network Drive (Connected Insights - Cloud)

When the Data Uploader is running, open the Services application from the Start menu and locate the "illumina ICI Auto Launch Service".
Right-click "illumina ICI Auto Launch Service" and select Properties from the drop-down menu.
In Properties, select the Log On tab and enter your account ID and password. Confirm the password.
Select the General tab.
Select Stop, then select Start to start the service. The network drive is available for ingestion for Data Uploader.

After completing these steps, the Data Uploader details are visible in Connected Insights.

Enable Ingestion from Proxy Server Setting

❗ export JDK_JAVA_OPTIONS='-Dhttps.proxyHost=<IP address of the proxy server e.g. 1.2.3.4> -Dhttps.proxyPort=<Port of the proxy server e.g. 8080>'

For Windows, it can be set via following command.

❗ setx JDK_JAVA_OPTIONS "-Dhttps.proxyHost=<IP Address of the proxy server e.g. 1.2.3.4> -Dhttps.proxyPort=<Port of the proxy server e.g. 8080>"

Remember to replace and with the actual values you need.

Select Compatible Pipeline

In Configuration Settings, select the radio button next to Choose compatible pipeline from catalog, refer to .
Select a pipeline from the drop-down list (for example, DRAGEN TruSight Oncology 500 Analysis Software v2.5.2).
❗ When running the DRAGEN Somatic Whole Genome pipeline in the Tumor-Only mode, you must set --output-file-prefix to match sample-id (the RGSM of the sample in the FASTQ list) of the run.
For Test Definition, select the applicable definition.
For Choose a folder to monitor for case metadata (optional), enter the path for the folder in the secondary analysis folder created by Data Uploader.
Select Save.

Generate an Api Key

❗ If you are installing Data Uploader on multiple machines, manually create and track your API key by running the following auto-updating and manual run command:

ici-uploader configure --api-key={apiKey} Make sure that the API key is within single quotation marks (for example,'{SYSTEM_API-KEY}')

In Connected Insights, select Manage API Keys from the Account drop-down menu.
Select Generate.
Enter a name for the API key.
To generate a global API key, select All workgroups and roles.
Select Generate.
In the API Key Generated window, select one of the following options:
- Show — Reveals the API key.
- Download API Key — Downloads the API key in .TXT file format.
Select Close after you have stored the API key.
❗ The API key cannot be viewed again after closing this window. Download the API key or save it in a secure location.
The API key is added to the Manage API keys list.
Perform any of the following actions in the Manage API Keys list:
- Select Regenerate to generate a new API with the existing API key name.
- Select Edit to edit the API key name or change the workgroups and roles selection.
- Select Delete to delete the API key.

Automation of Data Upload from User Storage ( Connected Insights - Cloud and Connected Insights - Local )

The following information is applicable to both Connected Insights - Local and Connected Insights - Cloud. Create each configuration as follows.

Input the {monitoring location} for secondary analysis output.
- The monitoring location is the full path to the location where secondary analysis output data is deposited in user's storage.
  - For example: /rest/of/storage path/{monitoring location}/{runFolder}/{sample folders, sample sheet, inputs, tumor_fastq_list.csv}
  - For DRAGEN server v4 standalone results: /rest/of/storage path/{monitoring location}/{sample name folders}/{sample sheet, inputs, VCFs, .bams}
Associate the workflow schema for this pipeline. a. Under Choose compatible pipeline from the catalog, select the applicable pipeline from the drop-down list (for example, DRAGEN WGS Somatic v4.2). b. If you are running a custom workflow, then upload a workflow schema that corresponds to the data that the configuration uploads. For more information, refer to .
Select the test definition to be associated with cases created by this configuration. For more information, refer to .
[Optional] Input the location where custom case data is stored. This location is the full path to where custom case data is deposited in user storage. For more information, refer to .
Select Save to complete the configuration. If Data Uploader is running, it monitors this configuration for data upload.

Perform any of the following actions below:

Edit You can modify the pipeline configuration by clicking "Edit" against a configuration.

Note: The change in configuration does not impact the Case that are already ingested.

Delete You can delete the pipeline configuration by clicking "Delete" against a configuration.

SampleSheet validation error
Case ingestion has stopped due to zero GEs balance
Case ingestion has stopped due to low space on external mounted storage or /staging

On-Demand Data Upload from User Storage (Connected Insights - Cloud Only)

Upload an analysis output by running the following command: ici-uploader analysis upload --folder={path-to-analysis} --pipeline-name={pipelineName}
- --folder {path-to-analysis} — The absolute path to the analysis output to upload into Connected Insights. This folder contains the sample sheet.
- --pipeline-name={pipelinename} — The name of the pipeline created in Connected Insights to apply to cases uploaded from this analysis. Pipeline names must include only letters, numbers, underscores, and dashes. The name cannot include spaces or special characters.
- [Optional] --runId={path-to-config} — The id of the run to be created in place of the run ID determined by the run folder name.
- [Optional] --pair-id={pair-id} — The pair-id of the analysis to upload from the Sample Sheet when limiting upload to a single analysis.
- [Optional] --case-display-id={case-display-id} — The id of the case to be created in place of the pair-id when uploading a single analysis with --pair-id={pair-id}.
- [Optional] ici-uploader logs show — Run to display the logs in ICI_Data_Upload_log.json.
- [Optional] Downloads > ici-uploader logs download — Download Data Uploader logs in a zipped folder by running the command prompt.
Upload the custom case data file associated to one or more cases by running the following command: ici-uploader case-data --filePath={absolute-path-of-csv-file}

For more information on custom case data files, refer to .

Case Processing Performance (Connected Insights - Local Only)

Classification & Risk Stratification Prediction

Classification & Risk Stratification Prediction is available for cases created using Connected Insights v5.1+.

Overview

If the case disease is Acute Myeloid Leukemia or a subtype, Classification & Risk Stratification Prediction is provided on the Overview Tab.

Reporting

The report interpretation summary can be generated from the prediction results by clicking Report.

Decision Trees

All variants described below must pass secondary analysis filters (VCF Filter = PASS).

APL with PML::RARA fusion

Classification

Blast count % ≥ 10
History of cytotoxic therapy exposure = No
Any of the following:
- Detection of PML::RARA fusion in the Variants Tab
- Detection of t(15;17)(q24;q21) in the User Determined Karyotype

If the above is met, the classification is predicted to be APL with PML::RARA fusion.

Risk Stratification

Detection of TP53 variant in the Variants Tab with the following characteristics:
- Small variant
- Somatic origin (origin = somatic or unknown)
- VAF ≥ 0.10 (10%)

If the above is met, the risk stratification is predicted to be Adverse. If not, then Intermediate.

AML with RUNX1::RUNX1T1 fusion

Classification

Blast count % ≥ 10
History of cytotoxic therapy exposure = No
Any of the following:
- Detection of RUNX1::RUNX1T1 fusion in the Variants Tab
- Detection of t(8;21)(q21.3;q22.1) in the User Determined Karyotype

The guideline specifies an outdated band 8q22 for RUNX1T1. It is now 8q21.3.

If the above is met, the classification is predicted to be AML with RUNX1::RUNX1T1 fusion.

Risk Stratification

Detection of TP53 variant in the Variants Tab with the following characteristics:
- Small variant
- Somatic origin (origin = somatic or unknown)
- VAF ≥ 0.10 (10%)

If the above is met, the risk stratification is predicted to be Adverse. If not, then Favorable.

AML with CBFB::MYH11 fusion

Classification

Blast count % ≥ 10
History of cytotoxic therapy exposure = No
Any of the following:
- Detection of CBFB::MYH11 fusion in the Variants Tab
- Detection of inv(16)(p13.1q22.1) in the User Determined Karyotype
- Detection of t(16;16)(p13.1;q22.1) in the User Determined Karyotype

If the above is met, the classification is predicted to be AML with CBFB::MYH11 fusion.

Risk Stratification

Detection of TP53 variant in the Variants Tab with the following characteristics:
- Small variant
- Somatic origin (origin = somatic or unknown)
- VAF ≥ 0.10 (10%)

If the above is met, the risk stratification is predicted to be Adverse. If not, then Favorable.

AML with DEK::NUP214 fusion

Classification

Blast count % ≥ 10
History of cytotoxic therapy exposure = No
Any of the following:
- Detection of DEK::NUP214 fusion in the Variants Tab
- Detection of t(6;9)(p22.3;q34.1) in the User Determined Karyotype

If the above is met, the classification is predicted to be AML with DEK::NUP214 fusion.

Risk Stratification

Adverse

AML with RBM15::MRTFA fusion

Classification

Blast count % ≥ 10
History of cytotoxic therapy exposure = No
Any of the following:
- Detection of RBM15::MRTFA fusion in the Variants Tab
- Detection of t(1;22)(p13.3;q13.1) in the User Determined Karyotype

If the above is met, the classification is predicted to be AML with RBM15::MRTFA fusion.

Risk Stratification

Detection of TP53 variant in the Variants Tab with the following characteristics:
- Small variant
- Somatic origin (origin = somatic or unknown)
- VAF ≥ 0.10 (10%)

If the above is met, the risk stratification is predicted to be Adverse. If not, then Intermediate.

AML with BCR::ABL1 fusion

Classification

Blast count % ≥ 20
History of cytotoxic therapy exposure = No
Any of the following:
- Detection of BCR::ABL1 fusion in the Variants Tab
- Detection of t(9;22)(q34.1;q11.2) in the User Determined Karyotype

If the above is met, the classification is predicted to be AML with BCR::ABL1 fusion.

Risk Stratification

Adverse

AML with KMT2A rearrangement

Classification

Blast count % ≥ 10
History of cytotoxic therapy exposure = No
Detection of KMT2A structural variant in the Variants Tab

If the above is met, the classification is predicted to be AML with KMT2A rearrangement.

Risk Stratification

Detection of TP53 variant in the Variants Tab with the following characteristics:
- Small variant
- Somatic origin (origin = somatic or unknown)
- VAF ≥ 0.10 (10%)

If the above is met, the risk stratification is predicted to be Adverse. If not, then continue below.

Any of the following:
- Detection of MLLT3::KMT2A in the Variants Tab
- Detection of t(9;11)(p21.3;q23.3) in the User Determined Karyotype
- Detection of KMT2A partial tandem duplication in the Variants Tab

If the above is met, the risk stratification is predicted to be Intermediate. If not, then Adverse.

AML with MECOM rearrangement

Classification

Blast count % ≥ 10
History of cytotoxic therapy exposure = No
Any of the following:
- Detection of MECOM structural variant in the Variants Tab
- Detection of inv(3)(q21.3q26.2) in the User Determined Karyotype
- Detection of t(3;3)(q21;q26) in the User Determined Karyotype
- Detection of t(3;21)(q26.2;q22) in the User Determined Karyotype
- Detection of t(3;12)(q26.2;p13) in the User Determined Karyotype

If the above is met, the classification is predicted to be AML with MECOM rearragement.

Risk Stratification

Adverse

AML with NUP98 rearrangement

Classification

Blast count % ≥ 10
History of cytotoxic therapy exposure = No
Any of the following:
- Detection of NUP98 structural variant in the Variants Tab
- Detection of t(5;11)(q35.2;p15.4) in the User Determined Karyotype
- Detection of t(11;12)(p15.4;p13.3) in the User Determined Karyotype

If the above is met, the classification is predicted to be AML with NUP98 rearrangement.

Risk Stratification

Detection of TP53 variant in the Variants Tab with the following characteristics:
- Small variant
- Somatic origin (origin = somatic or unknown)
- VAF ≥ 0.10 (10%)

If the above is met, the risk stratification is predicted to be Adverse. If not, then Intermediate.

AML with NPM1 mutation

Classification

Blast count % ≥ 10
History of cytotoxic therapy exposure = No
Detection of NPM1 variant in the Variants Tab with the following characteristics:
- Small variant

If the above is met, the classification is predicted to be AML with NPM1 mutation.

Risk Stratification

Any of the following:
- Detection of TP53 variant in the Variants Tab with the following characteristics:
  - Small variant
  - Somatic origin (origin = somatic or unknown)
  - Oncogenic or likely oncogenic (as indicated by a knowledge base biological classification or oncogenicity prediction)
  - VAF ≥ 0.10 (10%)
- Detection of DEK::NUP214 fusion in the Variants Tab
- Detection of t(6;9)(p22.3;q34.1) in the User Determined Karyotype
- Detection of KMT2A structural variant without MLLT3 fusion partner in the Variants Tab
- Detection of BCR::ABL1 fusion in the Variants Tab
- Detection of t(9;22)(q34.1;q11.2) in the User Determined Karyotype
- Detection of KAT6A::CREBBP fusion in the Variants Tab
- Detection of t(8;16)(p11.2;p13.3) in the User Determined Karyotype
- Detection of MECOM structural variant in the Variants Tab
- Detection of inv(3)(q21.3q26.2) in the User Determined Karyotype
- Detection of t(3;3)(q21;q26) in the User Determined Karyotype
- Detection of t(3;21)(q26.2;q22) in the User Determined Karyotype
- Detection of t(3;12)(q26.2;p13) in the User Determined Karyotype
- Detection of monosomy 5 in the User Determined Karyotype or Variants Tab
- Detection of 5q deletion in the User Determined Karyotype, or Variants Tab with length ≥ 5 Mbp
- Detection of monosomy 7 in the User Determined Karyotype or Variants Tab
- Detection of monosomy 17 in the User Determined Karyotype or Variants Tab
- Detection of 17p deletion in the User Determined Karyotype, or Variants Tab with length ≥ 5 Mbp

If the above is met, the risk stratification is predicted to be Adverse. If not, then continue below.

Detection of FLT3 internal tandem duplication in the Variants Tab

If the above is met, the risk stratification is predicted to be Intermediate. If not, then Favorable.

AML with CEBPA mutation

Classification

None of the classifications above should be met.
Blast count % ≥ 20
History of cytotoxic therapy exposure = No
Any of the following:
- Detection of 2 CEBPA variants in the Variants Tab with the following characteristics:
  - Small variant
- Detection of CEBPA variant in the Variants Tab with the following characteristics:
  - Small variant
  - Located in the bZIP domain

The guideline requires biallelic mutations, whereas the evaluation simply checks for 2 due to lack of cis/trans information.

If the above is met, the classification is predicted to be AML with CEBPA mutation.

Risk Stratification

Detection of TP53 variant in the Variants Tab with the following characteristics:
- Small variant
- Somatic origin (origin = somatic or unknown)
- VAF ≥ 0.10 (10%)

If the above is met, the risk stratification is predicted to be Adverse. If not, then continue below.

Detection of CEBPA variant in the Variants Tab with the following characteristics:
- Small variant
- In-frame (not a frameshift variant)

If the above is met, the risk stratification is predicted to be Favorable. If not, then Intermediate.

AML with other defined genetic alterations

Classification

None of the classifications above should be met.
Blast count % ≥ 20
History of cytotoxic therapy exposure = No
Any of the following:
- Detection of CBFA2T3::GLIS2 fusion in the Variants Tab
- Detection of inv(16)(p13q24) in the User Determined Karyotype
- Detection of KAT6A::CREBBP fusion in the Variants Tab
- Detection of t(8;16)(p11.2;p13.3) in the User Determined Karyotype
- Detection of FUS::ERG fusion in the Variants Tab
- Detection of t(16;21)(p11;q22) in the User Determined Karyotype
- Detection of MNX1::ETV6 fusion in the Variants Tab
- Detection of t(7;12)(q36;p13) in the User Determined Karyotype
- Detection of NPM1::MLF1 fusion in the Variants Tab
- Detection of t(3;5)(q25;q35) in the User Determined Karyotype

If the above is met, the classification is predicted to be AML with other defined genetic alterations.

Risk Stratification

Detection of TP53 variant in the Variants Tab with the following characteristics:
- Small variant
- Somatic origin (origin = somatic or unknown)
- VAF ≥ 0.10 (10%)

If the above is met, the risk stratification is predicted to be Adverse. If not, then continue below.

Any of the following:
- Detection of KAT6A::CREBBP fusion in the Variants Tab
- Detection of t(8;16)(p11.2;p13.3) in the User Determined Karyotype

If the above is met, the risk stratification is predicted to be Adverse. If not, then Intermediate.

Classification

None of the classifications above should be met.
Blast count % ≥ 20
History of cytotoxic therapy exposure = No
Any of the following:
- History of myelodysplastic syndrome = Yes
- Both of the following:
  - History of myelodysplastic syndrome = Yes
  - History of myeloproliferative neoplasm = Yes
- Detection of 5q deletion in the User Determined Karyotype, or Variants Tab with length ≥ 5 Mbp
- Detection of monosomy 7 in the User Determined Karyotype or Variants Tab
- Detection of 11q deletion in the User Determined Karyotype, or Variants Tab with length ≥ 5 Mbp
- Detection of 12p deletion in the User Determined Karyotype, or Variants Tab with length ≥ 5 Mbp
- Detection of monosomy 13 in the User Determined Karyotype or Variants Tab
- Detection of 17p deletion in the User Determined Karyotype, or Variants Tab with length ≥ 5 Mbp
- Detection of isochromosome 17q in the User Determined Karyotype
- Detection of idic(X)(q13) in the User Determined Karyotype
- Detection of ASXL1 variant in the Variants Tab with the following characteristics:
  - Small variant
- Detection of BCOR variant in the Variants Tab with the following characteristics:
  - Small variant
- Detection of EZH2 variant in the Variants Tab with the following characteristics:
  - Small variant
- Detection of SF3B1 variant in the Variants Tab with the following characteristics:
  - Small variant
- Detection of SRSF2 variant in the Variants Tab with the following characteristics:
  - Small variant
- Detection of STAG2 variant in the Variants Tab with the following characteristics:
  - Small variant
- Detection of U2AF1 variant in the Variants Tab with the following characteristics:
  - Small variant
- Detection of ZRSR2 variant in the Variants Tab with the following characteristics:
  - Small variant

If the above is met, the classification is predicted to be AML, myelodysplasia-related.

Risk Stratification

Any of the following:

Detection of TP53 variant in the Variants Tab with the following characteristics:
- Small variant
- Somatic origin (origin = somatic or unknown)
- VAF ≥ 0.10 (10%)
Detection of monosomy 5 in the User Determined Karyotype or Variants Tab
Detection of 5q deletion in the User Determined Karyotype, or Variants Tab with length ≥ 5 Mbp
Detection of monosomy 7 in the User Determined Karyotype or Variants Tab
Detection of monosomy 17 in the User Determined Karyotype or Variants Tab
Detection of 17p deletion in the User Determined Karyotype, or Variants Tab with length ≥ 5 Mbp
Detection of ASXL1 variant in the Variants Tab with the following characteristics:
- Small variant
Detection of BCOR variant in the Variants Tab with the following characteristics:
- Small variant
Detection of EZH2 variant in the Variants Tab with the following characteristics:
- Small variant
Detection of SF3B1 variant in the Variants Tab with the following characteristics:
- Small variant
Detection of SRSF2 variant in the Variants Tab with the following characteristics:
- Small variant
Detection of STAG2 variant in the Variants Tab with the following characteristics:
- Small variant
Detection of U2AF1 variant in the Variants Tab with the following characteristics:
- Small variant
Detection of ZRSR2 variant in the Variants Tab with the following characteristics:
- Small variant

If the above is met, the risk stratification is predicted to be Adverse. If not, then Intermediate.

Definitions

Complex Karyotype

According to WHO/ISCN: ≥ 3 abnormalities, where abnormalities are counted as follows:

Only clonal abnormalities are counted; abnormalities present in only 1 metaphase are ignored.
Numerical gains and losses, simple and complex balanced translocations, unbalanced aberrations involving one chromosome, as well as multiplication of a complete chromosome set are counted as one abnormality.
Unbalanced aberrations involving two or more chromosomes, tetrasomy of same chromosome, triplication or quadruplication, as well as isoderivative chromosomes, are counted as 2 abnormalities.
Constitutional abnormalities are not counted.
In case of multiple clones (subclones or independent clones), chromosome abnormalities in each clone/subclone are counted separately and the number of chromosomal abnormalities is defined by the clone with the highest abnormalities.
For composite karyotypes, clonal chromosomal aberrations are counted in metaphases with the highest number of abnormalities.

Monosomal Karyotype

According to ELN: Presence of two or more distinct monosomies (excluding loss of X or Y), or one single autosomal monosomy in combination with at least one structural chromosome abnormality.