FAQs
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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:
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.
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.
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.
What is the LoD, and what does it indicate?
LoD stands for Limit of Detection. Each SOMAmer has an LoD for both Plasma and Serum. The LoD is a noise floor for that SOMAmer's fully normalized (MedNormExt) counts. In other words, normalized counts above the SOMAmer's LoD reflect the relative abundance of that SOMAmer's target protein, whereas normalized counts below its LoD may reflect assay uncertainty.
How should LoD be used to discern signal?
The normalized count of a given protein is considered signal if it is above the LoD for that protein for it's given sample type.
How do Somalogic and Illumina metrics compare?
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.
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
-
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?
Human
10326
Mouse
230
Gila monster
3
Hornet
3
Jellyfish
3
African clawed frog
3
Thermus thermophilus
3
European elder
2
Common eastern firefly
2
E. coli
1
HIV-1
1
HIV-2
1
Bacillus stearothermophilus
1
Ensifer meliloti
1
Red alga
1
