ANGSD: analysis of next generation sequencing data

Thorfinn Sand Korneliussen; Anders Albrechtsen; Rasmus Nielsen

doi:10.1186/s12859-014-0356-4

ANGSD: analysis of next generation sequencing data

Thorfinn Sand Korneliussen, Anders Albrechtsen, Rasmus Nielsen

Computational and RNA Biology

670 Citations (Scopus)

1817 Downloads (Pure)

Abstract

Background: High-throughput DNA sequencing technologies are generating vast amounts of data. Fast, flexible and memory efficient implementations are needed in order to facilitate analyses of thousands of samples simultaneously. Results: We present a multithreaded program suite called ANGSD. This program can calculate various summary statistics, and perform association mapping and population genetic analyses utilizing the full information in next generation sequencing data by working directly on the raw sequencing data or by using genotype likelihoods. Conclusions: The open source c/c++ program ANGSD is available at . The program is tested and validated on GNU/Linux systems. The program facilitates multiple input formats including BAM and imputed beagle genotype probability files. The program allow the user to choose between combinations of existing methods and can perform analysis that is not implemented elsewhere.

Original language	English
Article number	356
Journal	B M C Bioinformatics
Volume	15
Number of pages	13
ISSN	1471-2105
DOIs	https://doi.org/10.1186/s12859-014-0356-4
Publication status	Published - 25 Nov 2014

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ANGSD: Analysis of Next Generation Sequencing DataFinal published version, 1.19 MBLicence: CC BY

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title = "ANGSD: analysis of next generation sequencing data",

abstract = "Background: High-throughput DNA sequencing technologies are generating vast amounts of data. Fast, flexible and memory efficient implementations are needed in order to facilitate analyses of thousands of samples simultaneously. Results: We present a multithreaded program suite called ANGSD. This program can calculate various summary statistics, and perform association mapping and population genetic analyses utilizing the full information in next generation sequencing data by working directly on the raw sequencing data or by using genotype likelihoods. Conclusions: The open source c/c++ program ANGSD is available at . The program is tested and validated on GNU/Linux systems. The program facilitates multiple input formats including BAM and imputed beagle genotype probability files. The program allow the user to choose between combinations of existing methods and can perform analysis that is not implemented elsewhere.",

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T2 - analysis of next generation sequencing data

AU - Korneliussen, Thorfinn Sand

AU - Albrechtsen, Anders

AU - Nielsen, Rasmus

PY - 2014/11/25

Y1 - 2014/11/25

N2 - Background: High-throughput DNA sequencing technologies are generating vast amounts of data. Fast, flexible and memory efficient implementations are needed in order to facilitate analyses of thousands of samples simultaneously. Results: We present a multithreaded program suite called ANGSD. This program can calculate various summary statistics, and perform association mapping and population genetic analyses utilizing the full information in next generation sequencing data by working directly on the raw sequencing data or by using genotype likelihoods. Conclusions: The open source c/c++ program ANGSD is available at . The program is tested and validated on GNU/Linux systems. The program facilitates multiple input formats including BAM and imputed beagle genotype probability files. The program allow the user to choose between combinations of existing methods and can perform analysis that is not implemented elsewhere.

AB - Background: High-throughput DNA sequencing technologies are generating vast amounts of data. Fast, flexible and memory efficient implementations are needed in order to facilitate analyses of thousands of samples simultaneously. Results: We present a multithreaded program suite called ANGSD. This program can calculate various summary statistics, and perform association mapping and population genetic analyses utilizing the full information in next generation sequencing data by working directly on the raw sequencing data or by using genotype likelihoods. Conclusions: The open source c/c++ program ANGSD is available at . The program is tested and validated on GNU/Linux systems. The program facilitates multiple input formats including BAM and imputed beagle genotype probability files. The program allow the user to choose between combinations of existing methods and can perform analysis that is not implemented elsewhere.

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DO - 10.1186/s12859-014-0356-4

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JO - B M C Bioinformatics

JF - B M C Bioinformatics

M1 - 356

ER -

ANGSD: analysis of next generation sequencing data

Abstract

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