PEMer
PEMer detects structural variants in genomic sequences from paired-end sequencing reads to map and characterize genomic structural variation.
Key Features:
- PEMer workflow: Implements a sensitive workflow for detecting structural variants from paired-end sequence reads using a coverage-adjusted multi-cutoff scoring strategy.
- Simulation-based error models: Uses simulation-based error models to assign confidence values to each detected structural variant.
- Platform compatibility: Supports multiple next-generation sequencing platforms.
- Relative insensitivity to base-calling errors: Shows relative insensitivity to base-calling errors as assessed by simulation studies.
- Back-end database: Provides a back-end database for storage and retrieval of genomic data and structural-variant results.
Scientific Applications:
- Structural variant discovery: Detection and reconstruction of structural variants from paired-end sequencing data.
- Population genomics: Mapping genomic structural variation in population-scale projects such as the 1000 Genomes Project.
- Disease and phenotype studies: Identifying genetic variations that may contribute to disease susceptibility or phenotypic differences.
- Evolutionary biology: Characterizing structural variation to study genetic diversity and evolutionary processes.
Methodology:
Processes paired-end sequence reads, applies a coverage-adjusted multi-cutoff scoring strategy for structural-variant reconstruction, employs simulation-based error models to assign confidence values and evaluate base-calling error effects, and stores results in a back-end database.
Topics
Details
- Tool Type:
- workflow
- Operating Systems:
- Linux
- Programming Languages:
- Perl, Python
- Added:
- 1/13/2017
- Last Updated:
- 11/25/2024
Operations
Publications
Korbel JO, Abyzov A, Mu XJ, Carriero N, Cayting P, Zhang Z, Snyder M, Gerstein MB. PEMer: a computational framework with simulation-based error models for inferring genomic structural variants from massive paired-end sequencing data. Genome Biology. 2009;10(2). doi:10.1186/gb-2009-10-2-r23. PMID:19236709. PMCID:PMC2688268.