Step 5 - QC Data

After submission, you will evaluate genomic data (ex. BAMs or CRAMS) for basic sequence yield and quality control (QC) metrics. These metrics ensure depth and breadth of coverage requirements are met for all data ingested into AnVIL.

AnVIL Data Processing Working Group has created a genomic evaluation tool for whole genome data (a whole exome QC tool is in development). You will collect quality control metrics for genome and exome sequencing data by running the tool - a workflow written in Workflow Description Language - in a sandbox workspace.

The WDL includes multiple software packages (Picard, VerifyBamID2, Samtools flagstat, bamUtil stats ) organized in a single, efficient tool that is compatible with AnVIL.

The current QC pass/fail status is based on three metrics: coverage, freemix, and sample contamination. QC metrics can be made available in the AnVIL workspace to aid users in sample selection.

QC processing results table

Below is the current output, generated by the workflow in a qc_results_sample data table.

Metric Name	Metric Description	Pass threshold	Purpose	Source Tool
`qc_results_sample_id`	Sample ID	NA	Identify sample	NA
`cram`	Cram google path	NA	Locate file	NA
`FREEMIX`	FREEMIX	< 0.01	Sample contamination	VerifyBamID2
`MEAN_COVERAGE`	Haploid Coverage	≥ 30	Coverage depth	Picard CollectWgs Metrics
`MEDIAN_ABSOLUTE_DEVIATION`	Library insert size mad	NA	Batch characteristics	Picard CollectInsertSize Metrics
`MEDIAN_INSERT_SIZE`	Library insert size median	NA	Batch characteristics	Picard CollectInsertSize Metrics
`PCT_10X`	% coverage at 10X	> 0.95	Coverage breadth	Picard CollectWgs Metrics
`PCT_20X`	% coverage at 20X	> 0.90	Coverage breadth	Picard CollectWgs Metrics
`PCT_30X`	% coverage at 30X	NA	Additional metadata	Picard CollectWgs Metrics
`PCT_CHIMERAS (PAIR)`	% Chimeras	< 0.05	Variant detection	Picard CollectAlignmentSummary Metrics
`Percent_duplication`	% duplication
`Q20_BASES`	Total bases with Q20 or higher	≥ 86x109	Sequence quality	Picard CollectQualityYield Metrics
`qc_status`	Reported status at the sample level	Pass/Fail/No QC	Overall quality assessment
`read1_pf_mismatch_rate`	Read1 base mismatch rate	< 0.05	Sequence quality	Picard Collect Alignment Summary Metrics
`read2_pf_mismatch_rate`	Read2 base mismatch rate	< 0.05	Sequence quality	Picard Collect Alignment Summary Metrics

5.1 Select QC status criteria

Data submitters should establish the specific metrics and thresholds for determining the pass/fail criteria on their dataset.

5.2 Run QC Processing

Data Submitters are responsible for running the WDL on their data to generate the QC metrics. AnVIL Data Processing Working Group has created QC aggregator Jupyter notebook. Once QC status criteria have been determined, the thresholds can be modified in the notebook. The criteria is used to assign QC status of pass or fail. If a sample fails multiple times, it is assigned No QC under QC status.

Video - Walkthrough of WGS QC Processing

5.3 Post QC Processing to AnVIL Workspaces

The output from the QC aggregator is a QC summary results TSV file. Data submitters will pass off the QC summary results file to AnVIL ingestion team. The AnVIL team will push the QC summary results to the workspaces, which will contain the QC status including those that fail QC or have no QC. The example below is the QC results table in 1000 Genomes workspace.

Sample QC Results Table

Additional Resources - Upcoming AnVIL Tools

AnVIL Data Processing Working Group is evaluating two tools to add to the submission process to estimate (genetic) sex and compare that to reported sex. The goal is to identify at a cohort level any major issues between the genomic data and the reported phenotype data. Variation in sex chromosome copy number (e.g., XXY, XO, somatic mosaicism) means that genetic sex prediction is not 100% accurate, although it is an excellent tool for detecting major cohort-level issues.

Exome QC Processing

Coming soon

Sex Check