The Journal of Open Source SoftwareBioinformaticsPeer-reviewed journal article
QuaC: A Pipeline Implementing Quality Control Best Practices for Genome Sequencing and Exome Sequencing Data
Manavalan GajapathyiD, Brandon M. WilkiD, Elizabeth A. WortheyiD
Abstract
Quality Control (QC) of human genome sequencing and exome sequencing data is necessary to ensure they are of sufficient quality for downstream analyses. While several QC tools are available to measure quality parameters at various levels post-sequencing, their output needs to be reviewed and interpreted in a very manual and time-consuming process. Such manual review is a major challenge towards standardization and consistency, as the process can be subjective depending on the reviewer. To address these difficulties, we have developed QuaC, which implements, integrates, and standardizes QC best practices at our Center. It performs three major steps: (1) runs several QC tools using data produced by the read alignment (BAM) and small variant calling (VCF) as input and optionally accepts QC output for raw sequencing reads (FASTQ); (2) executes QuaC-Watch to perform QC checkup based on the expected thresholds for quality metrics; and (3) aggregates QC metrics produced by all the QC tools as well as QuaC-Watch results into single, self-contained MultiQC report, both at the per-sample and across-project levels. This report provides aggregate summaries for all samples within a project/cohort for efficient comprehensive review while still allowing for granular review down to individual metrics for a single sample. Finally, we have developed a "Sample QC review system" schema to standardize QC reviewers logging of results and simplify downstream users interpretation of the reviewers finding.
- organism: human
- assay: whole-genome sequencing
- assay: whole-exome sequencing
- research focus: variant calling
- approach: statistical model
- Citations
- 4
- FWCI
- 0.36
- Field percentile
- 49th percentile
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