qc-analysis-pipeline

Workflows used for QC of WGS or WES data

Single Sample QC

This WDL pipeline implements QC in human whole-genome or exome/targeted sequencing data.

For more on the metrics and aggregation of metrics from multiple workflow executions, please see the qc-metric-aggregator repository.

Background

As part of the AnVIL Data Processing Working Group, a Quality Control (QC) workflow was developed to harmonize and summarize the QC for all WGS and WES sequence data sets ingested and released on the AnVIL. The figure below shows the read-level data processing and ingestion process, including decisions regarding reprocessing when data is determined to be incompatible with the Functional Equivalance standard defined in this Nature Communications publication.

Summary

The following figure shows the steps of the workflow with approximate costs of executing each step in a cloud-hosted environment.

Requirements/expectations

Human paired-end sequencing data in aligned BAM or CRAM format
Input BAM/CRAM files must additionally comply with the following requirements:
- files must pass validation by ValidateSamFile
- reads are provided in query-sorted order
- all reads must have an RG tag
Reference genome must be Hg38 with ALT contigs
Coverage regions, either WGS or exome/targeted, must be in a compatible interval_list format

Outputs

BAM/CRAM Validation Report
Several QC Summary Reports
- All reads: Quality, Alignment, Insert Size, Artifact, GC Bias, Duplication, Contamination, and Coverage

Software version requirements :

Picard 2.21.7
samtools 1.3.1 using htslib 1.3.1
VerifyBamID2
Python 2.7 and 3
Cromwell version support
- Successfully tested on v48
- Does not work on versions < v23 due to output syntax

RxIdentifier

For sex estimation from WGS data, methods Ry (https://doi.org/10.1016/j.jas.2013.07.004) and Rx (https://doi.org/10.1371/journal.pone.0163019) were compared against 1kg data. The Ry method required adjustment of the default cutoffs on the 1kg data suggesting the type of sequence data, sample source/quality, coverage levels, and/or other experimental factors may impact the estimation of sex. The Rx method required no adjustments to the default cutoffs of 0.6 and 0.8. For a more detailed comparison of Rx and Ry methods, please see: https://doi.org/10.1038/s41598-020-68550-w For the Rx method, original R code is available: https://doi.org/10.1371/journal.pone.0163019.s003

Important Note :

The provided JSON is meant to be a ready to use example JSON template of the workflow. It is the user’s responsibility to correctly set the reference and resource input variables using the GATK Tool and Tutorial Documentations.
Relevant reference and resources bundles can be accessed in Resource Bundle.
Runtime parameters are optimized for Broad's Google Cloud Platform implementation.
For help running workflows on the Google Cloud Platform or locally please view the following tutorial (How to) Execute Workflows from the gatk-workflows Git Organization.
The following material is provided by the GATK Team. Please post any questions or concerns to one of these forum sites : GATK , FireCloud or Terra , WDL/Cromwell.
Please visit the User Guide site for further documentation on GATK workflows and tools.

LICENSING :

Copyright Broad Institute, 2019 | BSD-3 This script is released under the WDL open source code license (BSD-3) (full license text at https://github.com/openwdl/wdl/blob/master/LICENSE). Note however that the programs it calls may be subject to different licenses. Users are responsible for checking that they are authorized to run all programs before running this script.

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