DIVIS

DIVIS implements an integrated, customizable pipeline using GPyFlow for cancer genome sequencing analysis, performing read preprocessing, alignment, multisource variant detection, and annotation to support identification and interpretation of mutations from WGS, WES, and gene-panel NGS data.

Key Features:

• GPyFlow-based Customizability: Built on GPyFlow to enable customizable workflows and integration of whole-genome sequencing (WGS), whole-exome sequencing (WES), and gene-panel sequencing strategies.
• Comprehensive Workflow Integration: Consolidates read preprocessing, alignment to a reference genome, variant detection, and annotation into a cohesive analysis workflow.
• Multicaller Variant Detection and Screening: Employs multiple variant callers to detect genetic variations across samples and generates a standard variant-detection format list that includes per-caller evidence.
• Statistical Reporting: Automatically produces detailed reports listing command lines executed, parameter settings, quality-control indicators, and summaries of detected mutations.

Scientific Applications:

• Cancer mutation identification: Supports detection and interpretation of somatic and germline mutations within cancer genomes from NGS data.
• Cross-strategy genomic analysis: Facilitates comparative analyses across WGS, WES, and gene-panel sequencing datasets.
• Standardized variant reporting for research and translation: Provides standardized variant outputs and reports to support basic and translational oncology studies.

Methodology:

DIVIS uses GPyFlow customizable workflows to perform read preprocessing, alignment to a reference genome, variant detection using multiple callers with output as a standard variant-detection format including per-caller evidence, annotation of detected variants, and automatic generation of statistical reports listing command lines, parameters, quality-control indicators, and mutation summaries.