Overview

The altered gene function responsible for most tumor formation and evolution is caused by low-frequency events that are notoriously difficult to pinpoint in the genome. The Cancer Genome Analysis (CGA) Suite provides a complete set of integrated tools addressing key issues in getting reliable, accurate results from cancer genome NGS datasets.

Implement Pipelines Fast with Appistry’s NGS Analysis Scripts

Watch as CSO Dr. Rich Mazzarella explains what goes into Appistry’s NGS analysis scripts and how they can be used to streamline pipeline implementation. Length: 1:21

Components

  • The Genome Analysis Toolkit (GATK), the industry’s leading variant caller, prepares tumor/normal pair data for analysis
  • MuTect, the industry’s most validated toolkit for identifying somatic point mutations in tumor/normal pairs
  • ContEst for detecting cross-individual contamination levels to further improve the specificity of MuTect
  • Somatic Indel Detector, a former GATK walker now available only as part of the CGA Suite
  • A Perl script, test dataset, and results summary to connect, configure, and validate the workflow
  • Full documentation and one-on-one, user-centered help with implementing, deploying, and applying the tools

Key Features

As the foundation of the CGA Suite, MuTect provides a highly sensitive detection method that increases specificity through a series of advanced filters.

The four-step MuTect method:

  • Removes low-quality sequence data
  • Detects variants in tumor samples using a Bayesian classifier
  • Filters data to remove false positives produced by sequencing artifacts not captured by the error model
  • Employs a second Bayesian classifier to designate variants as somatic or germ-line

While other somatic mutation tools assume heterozygous, diploid events and thus provide a fixed allelic fraction, MuTect explicitly models the allelic fraction using a variant-detection statistical test that takes into account sequencing error and sequencing depth. This makes MuTect particularly sensitive to low-allelic fraction events (at or below 0.1), which is ideal for analyzing samples with low purity or complex subclonal structure.

In addition, MuTect’s specificity has been demonstrated in several collaborative studies that validated ~95% of MuTect’s calls in coding regions.

The CGA Suite complements MuTect with the Somatic Indel Detector to provide a complete picture of the potential disease-causing variants in a sample. The addition of ContEst further enhances the suite by providing a fractional contamination value to MuTect, which improves specificity. ContEst can also be used for general data quality control.