MIAmS
MIAmS detects microsatellite instability (MSI) and concurrent tumor genome mutations from amplicon-based next-generation sequencing (NGS) of tumor samples to assess DNA mismatch repair deficiency.
Key Features:
- Amplicon NGS analysis: Analyzes amplicon panels derived from tumor samples using next-generation sequencing (NGS).
- MSI detection: Calls microsatellite instability (MSI) from amplicon NGS data as a marker of DNA mismatch repair deficiency.
- Concurrent mutation profiling: Identifies concurrent tumor genome mutations from the same amplicon data.
- No paired normal required: Operates without requiring paired normal tissue for comparison.
- Alternative to multiplex-PCR: Provides an NGS-based alternative to multiplex-PCR length distribution analysis of microsatellites.
- Accuracy and robustness: Reported to provide strong accuracy and robustness in determining MSI status.
- Scalability: Supports scalable analysis for high-throughput amplicon panels.
Scientific Applications:
- MSI testing in oncology: Determines MSI status as a molecular marker of DNA mismatch repair deficiency across cancer types.
- Integrated tumor profiling: Enables simultaneous MSI and somatic mutation detection for tumor genetic characterization.
- Prognostic and therapeutic biomarker: Provides MSI and mutation data that inform prognostic assessments and therapeutic decision-making in personalized cancer treatment.
- Research and clinical use: Applicable for both cancer genomics research and clinical MSI diagnostics.
Methodology:
Tags MSI status directly from amplicon NGS data of tumor samples and analyzes amplicon panels to determine microsatellite status and concurrent tumor genome mutations.
Topics
Details
- Tool Type:
- command-line tool
- Programming Languages:
- JavaScript, Python
- Added:
- 1/9/2020
- Last Updated:
- 12/28/2020
Operations
Publications
Escudié F, Van Goethem C, Grand D, Vendrell J, Vigier A, Brousset P, Evrard SM, Solassol J, Selves J. MIAmS: microsatellite instability detection on NGS amplicons data. Bioinformatics. 2019;36(6):1915-1916. doi:10.1093/bioinformatics/btz797. PMID:31647522.
PMID: 31647522