CancerMutationAnalysis

CancerMutationAnalysis analyzes somatic mutations in cancer genomes at gene and gene-set levels to identify driver genes and characterize mutational patterns, implemented as an open-source R package.

Key Features:

• Gene-Level Analysis: Identifies and distinguishes driver versus passenger mutations at the gene level using statistical criteria.
• Two-Stage Study Design: Employs a two-stage study design in gene-level analysis to enhance accuracy and reliability of driver gene calls.
• Gene-Set Level Analysis: Supports analysis of predefined gene sets to assess collective impacts of somatic mutations across genes.
• Patient-Oriented Approach: Calculates gene-set scores for each individual sample and aggregates these scores across samples for cohort-level inference.
• Gene-Oriented Approach with Wilcoxon Test: Performs gene-oriented comparisons using the Wilcoxon test to assess differences between groups.

Scientific Applications:

• Driver Mutation Identification: Identification and characterization of driver mutations that may inform biological mechanisms and therapeutic targeting.
• Mutational Landscape Analysis: Profiling the genetic landscape of cancers by analyzing somatic mutations at both gene and gene-set levels.
• Patient-Specific Profiling: Deriving per-sample mutational profiles to support development of personalized treatment strategies based on individual mutational patterns.

Methodology:

Uses a two-stage study design for gene-level driver identification, computes per-sample gene-set scores then aggregates across samples for the patient-oriented analysis, and applies a gene-oriented Wilcoxon test for comparative assessment; implemented in R.