GTShark: Genotype compression in large projects

Sebastian Deorowicz; Agnieszka Danek

doi:10.1093/bioinformatics/btz508

GTShark: Genotype compression in large projects

Department of Algorithmics and Software (RAU/RAU5)

Research output: Contribution to journal › Article › peer-review

17 Citations (Scopus)

Abstract

Nowadays large sequencing projects handle tens of thousands of individuals. The huge files summarizing the findings definitely require compression. We propose a tool able to compress large collections of genotypes almost 30% better than the best tool to date, i.e. squeezing human genotype to less than 62 KB. Moreover, it can also compress single samples in reference to the existing database achieving comparable results.

Original language	English
Pages (from-to)	4791-4793
Number of pages	3
Journal	Bioinformatics
Volume	35
Issue number	22
DOIs	https://doi.org/10.1093/bioinformatics/btz508
Publication status	Published - 1 Nov 2019

ASJC Scopus subject areas

Statistics and Probability
Biochemistry
Molecular Biology
Computer Science Applications
Computational Theory and Mathematics
Computational Mathematics

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10.1093/bioinformatics/btz508

Cite this

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title = "GTShark: Genotype compression in large projects",

abstract = "Nowadays large sequencing projects handle tens of thousands of individuals. The huge files summarizing the findings definitely require compression. We propose a tool able to compress large collections of genotypes almost 30\% better than the best tool to date, i.e. squeezing human genotype to less than 62 KB. Moreover, it can also compress single samples in reference to the existing database achieving comparable results.",

author = "Sebastian Deorowicz and Agnieszka Danek",

year = "2019",

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AU - Danek, Agnieszka

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AB - Nowadays large sequencing projects handle tens of thousands of individuals. The huge files summarizing the findings definitely require compression. We propose a tool able to compress large collections of genotypes almost 30% better than the best tool to date, i.e. squeezing human genotype to less than 62 KB. Moreover, it can also compress single samples in reference to the existing database achieving comparable results.

UR - https://www.scopus.com/pages/publications/85074961936

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DO - 10.1093/bioinformatics/btz508

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JO - Bioinformatics

JF - Bioinformatics

IS - 22

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GTShark: Genotype compression in large projects

Abstract

ASJC Scopus subject areas

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