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Citations per year

Number of citations per year for the bioinformatics software tool VariationHunter
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Tool usage distribution map

This map represents all the scientific publications referring to VariationHunter per scientific context
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Popular tool citations

chevron_left Structural variant detection Transposable element prediction Deletion detection Insertion detection Duplication detection Inversion detection chevron_right
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Protocols

VariationHunter specifications

Information


Unique identifier OMICS_00328
Name VariationHunter
Software type Package/Module
Interface Command line interface
Restrictions to use None
Input format DIVET
Biological technology Illumina
Operating system Unix/Linux
Programming languages C
Computer skills Advanced
Stability No
Maintained No

Versioning


No version available

Publication for VariationHunter

VariationHunter citations

 (10)
library_books

Allelic decomposition and exact genotyping of highly polymorphic and structurally variant genes

2018
Nat Commun
PMCID: 5826927
PMID: 29483503
DOI: 10.1038/s41467-018-03273-1

[…] date aim to address these issues.Existing structural variation discovery tools are based on the following general strategies: detection of variants using discordantly mapping paired-end reads (e.g., VariationHunter, and HYDRA which report only the rough loci of structural variants but not their sequence content); detection of variants using split-read mappings (e.g., Socrates); and detection of v […]

call_split

Population and clinical genetics of human transposable elements in the (post) genomic era

2017
Mob Genet Elements
PMCID: 5305044
PMID: 28228978
DOI: 10.1080/2159256X.2017.1280116
call_split See protocol

[…] tional TE insertion detection methods altogether. Figure 1. Two of the earliest computational methods developed specifically for the detection of TE insertions from next-generation sequence data are VariationHunter and the program Spanner, which was used for calling TE insertions in the first phase of the 1KGP. Subsequent phases of the 1KGP included additional refinement of next-generation sequen […]

library_books

Detection of Genomic Structural Variants from Next Generation Sequencing Data

2015
Front Bioeng Biotechnol
PMCID: 4479793
PMID: 26161383
DOI: 10.3389/fbioe.2015.00092

[…] s sequences” (Thung et al., ).Among WGS tools, Tangram (Wu et al., ), a tool developed using Mosaik (Lee et al., ) alignments (though it may use alignments produced by other mappers), Next-Generation VariationHunter (Hormozdiari et al., ), Tea (Lee et al., ), RetroSeq eKeane:2013kq, and Mobster (Thung et al., ) have been reported in the literature. […]

library_books

Toolbox for Mobile Element Insertion Detection on Cancer Genomes

2015
Cancer Inform
PMCID: 4338948
PMID: 25931804
DOI: 10.4137/CIN.S24657

[…] experiments by the 1000 Genomes Project Structural Variation Group (data not shown) indicates an FDR of 5.96%, a rate far better than which is much better than was achieved with RetroSeq (17.61%) and VariationHunter, (26.86%). However, a major limitation of TANGRAM is that is was originally designed to work only with the short-read mapper MOSAIK. Here, we enabled TANGRAM to work with other popular […]

library_books

PopAlu: population scale detection of Alu polymorphisms

2015
PeerJ
PMCID: 4582951
PMID: 26417547
DOI: 10.7717/peerj.1269

[…] encing data, such as SNPs and small indels, comparatively fewer methods have been developed for finding structural variation and in particular Alu polymorphisms. Notable exceptions are Alu-Detect (), VariationHunter (; ) RetroSeq (), Tangram (), and Mobster (). These methods focus mainly on the detection of Alu insertions, and generally follow a three-step analysis. First, they identify fragments […]

library_books

Whole genome sequencing of Turkish genomes reveals functional private alleles and impact of genetic interactions with Europe, Asia and Africa

2014
BMC Genomics
PMCID: 4236450
PMID: 25376095
DOI: 10.1186/1471-2164-15-963

[…] at 3,583 of the novel SNPs found were identified as non-synonymous mutations in protein coding sequence (Figure C). We also indentified a total of 1,765,584 short (<50 bp) indels. Additionally, using VariationHunter [] we identified 1,751 large (50 bp to 100 Kbp) deletions per individual on average (Table ).To estimate the false discovery and false negative rates (FDR and FNR) of our SNP calls, we […]


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VariationHunter institution(s)
School of Computing Science, Simon Fraser University, Burnaby, BC, Canada

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