gatk_indel_realigner
gatk_indel_realigner performs local realignment of sequencing reads around insertion-deletion (indel) polymorphisms to correct misalignments and improve the accuracy of downstream variant calling from next-generation sequencing data.
Key Features:
- Local Realignment Around Indels: Performs local realignment of reads around insertion-deletion (indel) polymorphisms to correct misalignments that can produce erroneous variant calls.
- Integration with GATK Pipeline: Integrates into the GATK workflow and is used alongside initial read mapping, base quality score recalibration (BQSR), SNP discovery and genotyping, and machine learning-based filtering.
- Compatibility with Sequencing Technologies: Operates on data from multiple next-generation sequencing platforms and experimental designs.
- Support for Multi-sample Analysis: Contributes to multi-sample discovery and genotyping workflows to increase sensitivity and specificity across samples.
Scientific Applications:
- Human Disease Research: Improves precision of indel calls to support identification of genetic variants associated with disease.
- Ancestry and Evolution Studies: Enhances accuracy of variant calls for population genetics, ancestry inference, and evolutionary analyses.
- Large-Scale Genomic Projects: Has been applied to large datasets such as the 1000 Genomes Project to support analysis of extensive genomic data.
Methodology:
Identifies regions around indels with suspected misalignments and performs local realignment of reads to reduce false-positive and false-negative variant calls in subsequent variant-calling steps.
Topics
Collections
Details
- Maturity:
- Mature
- Tool Type:
- web application
- Operating Systems:
- Linux, Windows, Mac
- Programming Languages:
- Java
- Added:
- 12/19/2016
- Last Updated:
- 11/24/2024
Operations
Publications
Mareuil F, Doppelt-Azeroual O, Ménager H. A public Galaxy platform at Pasteur used as an execution engine for web services. Unknown Journal. 2017. doi:10.7490/f1000research.1114334.1.
DePristo MA, Banks E, Poplin R, Garimella KV, Maguire JR, Hartl C, Philippakis AA, del Angel G, Rivas MA, Hanna M, McKenna A, Fennell TJ, Kernytsky AM, Sivachenko AY, Cibulskis K, Gabriel SB, Altshuler D, Daly MJ. A framework for variation discovery and genotyping using next-generation DNA sequencing data. Nature Genetics. 2011;43(5):491-498. doi:10.1038/ng.806. PMID:21478889. PMCID:PMC3083463.
Afgan E, Baker D, van den Beek M, Blankenberg D, Bouvier D, Čech M, Chilton J, Clements D, Coraor N, Eberhard C, Grüning B, Guerler A, Hillman-Jackson J, Von Kuster G, Rasche E, Soranzo N, Turaga N, Taylor J, Nekrutenko A, Goecks J. The Galaxy platform for accessible, reproducible and collaborative biomedical analyses: 2016 update. Nucleic Acids Research. 2016;44(W1):W3-W10. doi:10.1093/nar/gkw343. PMID:27137889. PMCID:PMC4987906.