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HomSI / Homozygous Stretch Identifier from next-generation sequencing data
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Identifies homozygous stretches using new generation sequencing (NGS) data. HomSI was designed to define homozygous stretches in consanguineous families from NGS data. To identify and visualize the homozygous stretches, the software processes each variant and generates several graphs. It was evaluated using both a simulated dataset generated and a real dataset of three disease genes within the homozygous regions, which have been previously identified using a combination of exome and single-nucleotide polymorphism (SNP) microarray data.
A web-based application aimed at autozygosity mapping. HomozygosityMapper is independent of parameters like family structure or allele frequencies, the ‘homozygosity score’ is calculated simply from the observed homozygosity and it is robust against genotyping errors. HomozygosityMapper is much faster than conventional linkage software. The integration with GeneDistiller greatly facilitates the search for promising candidate genes compared to the conventional approach. We also encourage geneticists to consider HomozygosityMapper as a public repository for genotypes and results when publishing their homozygosity mappings. Due to its user-friendly intuitive interface and the lack of any local hardware requirements, it can be used by the geneticists themselves without the need for computer specialists.
An extension to the BCFtools software package that detects regions of autozygosity in sequencing data, in particular exome data. BCFtools/RoH uses a hidden Markov model (HMM) to identify ROHs. The HMM is applied to genetic variation data for the population containing the sample, with positions in the chain corresponding to segregating sites in the population, and using either genotype calls or genotype likelihoods. By applying it to simulated data and real data from the 1000 Genomes Project we estimate its accuracy and show that it has higher sensitivity and specificity than existing methods under a range of sequencing error rates and levels of autozygosity.
A standalone tool for working with annotated variant files, e.g. when searching for variants causing Mendelian disease. Very flexible in terms of input file formats, FILTUS offers efficient filtering and a range of downstream utilities, including statistical analysis of gene sharing patterns, detection of de novo mutations in trios, QC plots and autozygosity mapping. The autozygosity mapping is based on a hidden Markov model and enables accurate detection of autozygous regions directly from exome-scale variant files. FILTUS is primarily intended for WES-scale data, whole-genome data can be analysed by using the built-in prefiltering functionality.
GARLIC / Genomic Autozygosity Regions Likelihood-based Inference and Classification
Assists in calling runs of homozygosity in genotype data. GARLIC provides a model-based method for inferring runs of homozygosity (ROH) in genome-wide single nucleotide polymorphisms (SNPs) datasets. It works in four steps: (i) the window-based logarithm of the odds (LOD) score calculation, (ii) the kernel density estimation of LOD score distribution, (iii) the assembly of ROH, and (iv) gaussian mixture modeling of ROH size distribution.
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