inGAP-family

inGAP-family detects and filters artificial variants to improve identification of DNA polymorphisms, structural variants (SVs), meiotic recombination loci, and causal mutations from short-read alignments.


Key Features:

  • Short-read alignment-based discovery: Discovers DNA polymorphisms and structural variants (SVs) through the alignment of short reads.
  • Artificial-variant filtering: Filters out artificial variants arising from genome complexities and large-scale structural variations that can confound analyses.
  • Non-allelic locus discrimination: Removes misinterpreted sequence differences between non-allelic loci to reduce false genotyping and incorrect estimation of allele frequencies.
  • Recombination and mutation localization: Facilitates precise identification of meiotic recombination points and causal mutations within mutant genomes and quantitative trait loci (QTL).
  • Evaluation of predicted variants: Enables further evaluation of predicted variants and identification of mutations related to specific genotypes.
  • Real-dataset validation: Demonstrated applicability on real datasets for high-confidence polymorphism and SV analysis.

Scientific Applications:

  • Meiotic recombination mapping: Mapping meiotic recombination loci with reduced confounding from structural variation-induced artifacts.
  • Causal mutation identification: Detecting causal mutations in mutant genomes for mutant analysis and positional cloning.
  • QTL and marker-assisted genetics: Supporting molecular marker-assisted genetic studies and QTL analysis by providing accurate polymorphism calls.
  • Accurate genotyping and allele-frequency estimation: Improving genotyping accuracy and allele frequency estimates by removing artificial variants.
  • Structural-variation-aware variant analysis: Analyzing the impact of large-scale structural variations on polymorphism detection in empirical datasets.

Methodology:

Discover DNA polymorphisms and structural variants (SVs) through alignment of short reads and filtering out artificial variants caused by genome complexities and large-scale structural variations.

Topics

Details

Tool Type:
command-line tool, desktop application
Programming Languages:
Java
Added:
9/28/2021
Last Updated:
11/24/2024

Operations

Publications

Lian Q, Chen Y, Chang F, Fu Y, Qi J. inGAP-Family: Accurate Detection of Meiotic Recombination Loci and Causal Mutations by Filtering Out Artificial Variants due to Genome Complexities. Genomics, Proteomics & Bioinformatics. 2021;20(3):524-535. doi:10.1016/j.gpb.2019.11.014. PMID:33711466. PMCID:PMC9801030.

PMID: 33711466
PMCID: PMC9801030
Funding: - National Natural Science Foundation of China: 31770244, 32070247