isma
isma integrates somatic mutation calls from multiple mutation-calling pipelines to produce a consensus mutation catalogue that improves reliability of somatic mutation detection in matched tumor–normal next-generation sequencing data.
Key Features:
- R package: Implemented in R and provides functions for integration and analysis of somatic mutation calls.
- Integration of multiple pipelines: Combines somatic mutation outputs from various callers applied to matched tumor–normal samples to address low concordance among tools.
- Quantification of concordance and variability: Computes agreement metrics between pipelines, estimates variability in mutation calls, and identifies outlier results.
- Integration with public mutation catalogues: Incorporates evidence from public resources such as The Cancer Genome Atlas (TCGA) to contextualize mutations.
- Filtering strategies: Provides functions to apply filtering criteria and reports common patterns and pipeline-specific variability to prioritize reliable mutation sites.
- Comprehensive reporting: Generates a unique mutation catalogue and detailed reports summarizing shared patterns, variability, and previously catalogued sites.
Scientific Applications:
- Cancer genomics: Supports accurate somatic mutation detection and comparative analysis across pipelines to aid interpretation of tumor genetic alterations and development of targeted therapies.
Methodology:
Integrates outputs from multiple mutation-calling pipelines applied to matched tumor–normal samples, quantifies agreement between pipelines, estimates variability, identifies outliers, incorporates TCGA evidence, applies filtering strategies, and generates a unique mutation catalogue with detailed reports.
Topics
Details
- Maturity:
- Mature
- Cost:
- Free of charge
- Tool Type:
- library
- Operating Systems:
- Linux, Windows, Mac
- Programming Languages:
- R
- Added:
- 6/21/2019
- Last Updated:
- 6/16/2020
Operations
Publications
Di Nanni N, Moscatelli M, Gnocchi M, Milanesi L, Mosca E. isma: an R package for the integrative analysis of mutations detected by multiple pipelines. BMC Bioinformatics. 2019;20(1). doi:10.1186/s12859-019-2701-0. PMID:30819096. PMCID:PMC6394085.