FermiKit: assembly-based variant calling for Illumina resequencing data.
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ABSTRACT:
SUBMITTER: Li H
PROVIDER: S-EPMC4757955 | biostudies-literature | 2015 Nov
REPOSITORIES: biostudies-literature
Publications
FermiKit: assembly-based variant calling for Illumina resequencing data.
Bioinformatics (Oxford, England) 20150727 22
<h4>Unlabelled</h4>FermiKit is a variant calling pipeline for Illumina whole-genome germline data. It de novo assembles short reads and then maps the assembly against a reference genome to call SNPs, short insertions/deletions and structural variations. FermiKit takes about one day to assemble 30-fold human whole-genome data on a modern 16-core server with 85 GB RAM at the peak, and calls variants in half an hour to an accuracy comparable to the current practice. FermiKit assembly is a reduced r ...[more]
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Project description:BackgroundAccurate genotype calling for high throughput Illumina data is an important step to extract more genetic information for a large scale genome wide association studies. Many popular calling algorithms use mixture models to infer genotypes of a large number of single nucleotide polymorphisms in a fast and efficient way. In practice, mixture models are mostly restricted to infer genotypes for common SNPs where their minor allele frequencies are quite large. However, it is still challenging to accurately genotype rare variants, especially for some rare variants where the boundaries of their genotypes are not clearly defined.ResultsTo further improve the call accuracy and the quality of genotypes on rare variants, a new model calling procedure, named M-D, is proposed to infer genotypes for the Illumina BeadArray data. In this calling procedure, a Gaussian Mixture Model and a Dirichlet Process Gaussian Mixture Model are integrated to infer genotypes.ConclusionsApplications to Illumina data illustrate that this new approach can improve calling performance compared to other popular genotyping algorithms.
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