PedMiner
PedMiner performs linkage analysis and variant annotation to identify disease-associated genetic variants from family-based whole-exome sequencing (WES) data for studies of Mendelian inherited disorders, including autosomal recessive inheritance.
Key Features:
- Linkage Analysis: Performs linkage analysis on family-based whole-exome sequencing (WES) data.
- Integration of Analyses: Integrates linkage analysis with variant annotation and prioritization into an automated pipeline.
- Variant and Gene Annotation: Provides detailed annotation of variants and genes within linked genomic regions.
- Visualization of Linked Regions: Generates graphical visualization of linked genomic regions to support interpretation of linkage results.
- Default Filtration Process: Applies a default filtration process to prioritize candidate variants from WES datasets.
- Inheritance Model Support: Tailored for analyses under an autosomal recessive inheritance pattern.
Scientific Applications:
- Mendelian disease gene discovery: Identification of candidate disease-causing variants in studies of Mendelian inherited disorders using family-based WES.
- Autosomal recessive studies: Detection and prioritization of variants consistent with autosomal recessive inheritance.
- Candidate variant prioritization: Reduction of candidate variant lists from complex family WES datasets for downstream investigation.
- Support for functional follow-up: Provision of annotated variants and genes to inform subsequent functional analyses.
Methodology:
Performs linkage analysis on family-based WES data; integrates linkage results with variant annotation and prioritization in an automated pipeline; generates graphical visualizations of linked genomic regions; annotates variants and genes within linked regions; applies a default filtration process to prioritize candidate variants.
Topics
Details
- Added:
- 1/18/2021
- Last Updated:
- 11/24/2024
Operations
Publications
Zhou J, Gao J, Zhang H, Zhao D, Li A, Iqbal F, Shi Q, Zhang Y. PedMiner: a tool for linkage analysis-based identification of disease-associated variants using family based whole-exome sequencing data. Briefings in Bioinformatics. 2020;22(3). doi:10.1093/bib/bbaa077. PMID:32393981. PMCID:PMC8138824.