FAQs

Process FAQs

• How can I share data with a collaborator in BSSH?

  • See the following documentation: https://help.connected.illumina.com/basespace-sequence-hub/collaborate/share-with-collaborators

• I sequenced in manual mode/need to kick of autolaunch after sequencing is complete. How can I do this?

  • Use the BSSH CLI to upload the run folder to BSSH. Make sure the samplesheet is named "SampleSheet.csv" and you are using an up-to-date version of the tool - at least v1.6.1.

  • For additional information, see the following documentation:

    • https://help.connected.illumina.com/basespace-sequence-hub/cmd-line-interfaces/basespace-cli

• How do I download/export the samplesheet?

  • Go to the BSSH Run Planner:

    • Go to BSSH, select the intended workgroup on the top right, and then select the Runs tab

    • Additional information on the BSSH Run Planner: https://help.basespace.illumina.com/sequence/plan-runs

  

  • For a new run:

    • Select the "New Run" button on the right and plan a new run with the desired pipeline.

    • After ingesting the IPPAS output files in the BSSH Run Planner, the user will reach the following Run Review page:

    

    • Select the "Export" option on the bottom right to download the samplesheet created

    • Select the "Save as Draft" or "Save as Planned" options to save this run as a draft or planned run respectively

  • For an "Active" or "Planned" run:

    • Select the intended tab mentioned under the Runs header.

    • Select the required run from the list of runs:

    

    • Next, click File > Download > Sample Sheet:

    
• How can I requeue a run on BSSH with a new samplesheet/new version of the pipeline?

  • Go to the BSSH Run Planner tool and plan a new run with the desired pipeline.

  • Save the exported samplesheet (see the above step for additional information).

  • Go to the original run, and click Status > Requeue > Planned Run.

  

  • Select "Use a new Sample Sheet".

  • Upload the new sample sheet.

  • On the next page, click "requeue".

• Can multi-analysis by project split samples on the same plate?

  • No. All samples on the same plate must have the same project.

Metrics and Bioinformatics FAQs

• What is DRC_Level and why is this used?

  • DRC stands for Dynamic Range Compression. It is used to even out the SOMAmer concentrations from a 5-log dynamic range to 2-log. Without DRC, the most abundant SOMAmers would occupy the majority of sequencing readout capacity. Each sample would require extremely high sequencing depth to cover the unabundant SOMAmers and accurately quantify them. In using DRC, probes are grouped based on their observed abundances under no DRC condition, and each group is compressed by a different set ratio. The compression level of each SOMAmer is included in the DRC_Level row of SOMAmer metadata.

• How can I compare the outputs of DRAGEN Protein Quantification to SomaScan Array, and how do their metrics compare?

  • Unfortunately, it's not possible to directly compare the outputs of these two products due to the differing DRC strategies used.

  • Metrics and Normalization steps with different names between Somalogic's tool and Illumina's DRAGEN Protein Quantification. See the table below for the approximate mapping.

    Somalogic Normalization Steps

    Illumina Protein Prep Normalization Steps

    Notes

    Raw RFU

    Raw

    Hyb Normalization

    HybNorm

    medNormInt

    MedNormInt

    plateScale

    PlatformSpecificPlateScale

    Calibration

    PlatformSpecificCalibrate

    -

    CrossPlatformPlateScale

    Applied to normalize data across instruments

    -

    CrossPlatformCalibrate

    Applied to normalize data across instruments

    -

    MedNormExt

    anmlQC

    -

    qcCheck

    QCCheck

    anmlSMP

    -

    Filtered

    -

• What is Dilution and why is it used?

  • Each plate is split into multiple dilution groups, and SOMAmers are added to the plate based on that group. This is necessary because SOMAmers need to be more concentrated than proteins to facilitate binding. SOMAmers on catch0 beads have a physical concentration cap requiring the proteins to be diluted at different levels to achieve the concentration gaps to SOMAmers. The dilution group the SOMAmer is added to can be identified in the SOMAmer metadata.

• Do the counts in the ADAT represent the original absolute quantification of the sample?

  • No. Counts in the ADAT cover the relative SOMAmer quantification of the sample. Factors like DRC, Dilution, and PCR mean that counts are compressed by differing factors; these factors are not uncompressed in the final ADAT.

• How should signal and background be compared?

  • To identify background, blank samples on the plate (negative controls) can be used to obtain a per SOMAmer background.

    • Additionally, a global Limit of Detection (LoD) is computed for each SOMAmer for both plasma and serum using internal data. This is in the SOMAmer metadata section of the ADAT.

  • To identify signal, QC samples on the plate (positive controls) can be used to obtain a per SOMAmer signal.

  • When comparing signal to background, it's important to do so on a per SOMAmer level as background can vary from SOMAmer to SOMAmer.

• Where are the FASTQs?

  • DRAGEN Protein Quantification does not produce FASTQs. By utilizing DRAGEN Counting, the software uses BCL Convert to demultiplex and count proteins per sample at the same time. This reduces analysis time but also removes FASTQ as a pipeline output.

• What if the PF or Q30 values are lower than expected?

  • First, check secondary metrics. If secondary metrics are passing, it's acceptable to proceed with further analysis. If secondary metrics have warnings or failures, consider re-pooling or repeating the dilute and denature and sequencing of the saved pool. If the data still looks poor, reach out to tech support for further guidance.

• Why are there counts for blank samples, and non-human SOMAmer counts for human samples?

  • This is the background of the Illumina Protein Prep assay, which is due to non-specific binding of the SOMAmers. During library prep, all samples will experience SOMAMers sticking to beads or the side and bottom of the plate. These SOMAmers will then be brought through to sequencing. This is one of the reasons this is a relative abundance assay - the difference in SOMAmer counts is more important than the absolute value of the counts due to this background.

• Why are there SOMAmer counts in blank samples?

  • This is the background of the Illumina Protein Prep assay, which is due to non-specific binding of the SOMAmers. During library prep, all samples will experience SOMAMers sticking to beads or the side and bottom of the plate. These SOMAmers will then be brought through to sequencing.

• There are some proteins that multiple SOMAmers map to. Why is this and how does it impact analysis?

  • There are a handful of SOMAmers that map to the same protein. Some were created as Somalogic improved the SELEX process and a new SOMAmer’s affinity to the protein improved. Some may target different domains, isoforms, or cleavage products of a protein. They may or may not compete for the same epitope. Given the multiple reasons for multiple SOMAmers per protein, Illumina doesn't recommend any general methods for analysis that apply to all proteins.

• What organisms does the SOMAmer metadata cover in the 9.5k assay?