Access Quality Control (v2)
MSK-ACCESS QC generation V2
MSK-ACCESS QC generation V2
  • MSK-ACCESS QC generation
  • Installation and Running
    • Requirements
    • Installation and Usage
    • Inputs Description
  • Interpretation
    • Sample meta information
    • Coverage vs GC bias
    • Insert size metrics
    • Target coverage distribution
    • Capture metrics
    • Duplex family metrics
    • Mean base quality
    • Duplex noise metrics
    • Contamination
    • Fingerprinting
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  • Introduction
  • Methods
  • Interpretation

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  1. Interpretation

Target coverage distribution

Ensure consistent coverage across ACCESS bait (or "probe") regions.

PreviousInsert size metricsNextCapture metrics

Last updated 3 years ago

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Introduction

This figure shows the density plot of coverage values from the ACCESS target regions. Each line is data from one sample. Each sample is normalized by the median coverage value of that sample to align all peaks with one another and correct for sample-level differences.

Methods

The data used to produce this figure are the values under the normalized_coverage column, which are in the *_per_target_coverage.txt output file from CollectHsMetrics. Then the gaussian_kde function from the python scipy package is used to produce the density plot.

Interpretation

Each distribution should be unimodal, apart from a second peak on the low end due to X chromosome mapping from male samples. Narrow peaks are indicative of evenly distributed coverage across all bait regions. Wider distributions indicate uneven read distribution, and may be correlated with a large GC bias. Note that the provided bed file lists start and stop coordinates of ACCESS design probes, not the actual genomic target regions.

Tool used: BAM type: Collapsed BAM Regions: Pool A

GATK-CollectHsMetrics
Example MultiQC report showing coverage distribution for 20 samples (10 plasma and 10 buffy coat samples).