GATK

GATK performs analysis of high-throughput sequencing (HTS) and variant call format (VCF) data from next-generation DNA sequencing (NGS) to enable discovery and genotyping of germline and somatic variants and copy-number events.

Key Features:

• Data types: Processes high-throughput sequencing (HTS) reads and variant call format (VCF) files from NGS experiments.
• Structured programming framework: Provides a programming framework that facilitates efficient and robust development of analysis tools.
• MapReduce architecture: Built on a MapReduce functional programming philosophy to streamline data access patterns across sequencing analyses.
• Modular separation: Separates specific analysis calculations from common data management infrastructure to improve correctness and stability.
• Performance optimization: Optimized for CPU and memory efficiency.
• Parallelization: Supports distributed and shared-memory parallelization for large-scale genomic datasets.
• Germline variant discovery: Performs germline short variant discovery from whole-genome and exome sequencing data.
• Copy-number and somatic analyses: GATK4 includes expanded functionality for copy-number and somatic variant analysis.
• Workflow pipelines: Provides pipeline scripts to implement comprehensive sequencing analysis workflows.

Scientific Applications:

• Population-scale variant discovery: Used for germline short variant discovery in whole-genome and exome studies such as the 1000 Genomes Project.
• Cancer genomics: Applied to somatic variant detection and copy-number analysis in projects such as The Cancer Genome Atlas.
• NGS tool development: Serves as a framework for developers and analysts to build and deploy NGS analysis tools and workflows.

Methodology:

Built on a MapReduce functional programming model that separates analysis calculations from data management and supports distributed and shared-memory parallelization.