angsd-wrapper: utilities for analysing next-generation sequencing data

Arun Durvasula; Paul J. Hoffman; Tyler V. Kent; Chaochih Liu; Thomas J.Y. Kono; Peter L. Morrell; Jeffrey Ross-Ibarra

doi:10.1111/1755-0998.12578

angsd-wrapper: utilities for analysing next-generation sequencing data

Arun Durvasula, Paul J. Hoffman, Tyler V. Kent, Chaochih Liu, Thomas J.Y. Kono, Peter L. Morrell, Jeffrey Ross-Ibarra

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

14 Scopus citations

Abstract

High-throughput sequencing has changed many aspects of population genetics, molecular ecology and related fields, affecting both experimental design and data analysis. The software package angsd allows users to perform a number of population genetic analyses on high-throughput sequencing data. angsd uses probabilistic approaches which can directly make use of genotype likelihoods; thus, SNP calling is not required for comparative analyses. This takes advantage of all the sequencing data and produces more accurate results for samples with low sequencing depth. Here, we present angsd-wrapper, a set of wrapper scripts that provides a user-friendly interface for running angsd and visualizing results. angsd-wrapper supports multiple types of analyses including estimates of nucleotide sequence diversity neutrality tests, principal component analysis, estimation of admixture proportions for individual samples and calculation of statistics that quantify recent introgression. angsd-wrapper also provides interactive graphing of angsd results to enhance data exploration. We demonstrate the usefulness of angsd-wrapper by analysing resequencing data from populations of wild and domesticated Zea. angsd-wrapper is freely available from https://github.com/mojaveazure/angsd-wrapper.

Original language	English (US)
Pages (from-to)	1449-1454
Number of pages	6
Journal	Molecular Ecology Resources
Volume	16
Issue number	6
DOIs	https://doi.org/10.1111/1755-0998.12578
State	Published - Nov 1 2016

Bibliographical note

Funding Information:
We acknowledge funding support from the US National Science Foundation (IOS-1238014 to JRI and IOS-1339393 to PLM), from a University of Minnesota Doctoral Dissertation Fellowship supporting TJYK, from USDA Hatch project CA-D-PLS-2066-H and from the University of California Davis Plant Sciences Department. Support was also provided by the Minnesota Agricultural Experiment Station Variety Development fund. We thank members of the Ross-Ibarra and Morrell Labs for discussion and software testing. We thank the authors of angsd and related programmes for answering questions, particularly Matteo Fumagalli and Filipe Vieira. Matteo Fumagalli and an anonymous reviewer provided comments that improved both the manuscript and the implementation of angsd-wrapper. Finally, we would like to thank Felix Andrews for statistical advice, although we did not follow it.

Publisher Copyright:
© 2016 John Wiley & Sons Ltd

Keywords

Zea
domestication
population genetics
software
visualization

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10.1111/1755-0998.12578

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title = "angsd-wrapper: utilities for analysing next-generation sequencing data",

abstract = "High-throughput sequencing has changed many aspects of population genetics, molecular ecology and related fields, affecting both experimental design and data analysis. The software package angsd allows users to perform a number of population genetic analyses on high-throughput sequencing data. angsd uses probabilistic approaches which can directly make use of genotype likelihoods; thus, SNP calling is not required for comparative analyses. This takes advantage of all the sequencing data and produces more accurate results for samples with low sequencing depth. Here, we present angsd-wrapper, a set of wrapper scripts that provides a user-friendly interface for running angsd and visualizing results. angsd-wrapper supports multiple types of analyses including estimates of nucleotide sequence diversity neutrality tests, principal component analysis, estimation of admixture proportions for individual samples and calculation of statistics that quantify recent introgression. angsd-wrapper also provides interactive graphing of angsd results to enhance data exploration. We demonstrate the usefulness of angsd-wrapper by analysing resequencing data from populations of wild and domesticated Zea. angsd-wrapper is freely available from https://github.com/mojaveazure/angsd-wrapper.",

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author = "Arun Durvasula and Hoffman, {Paul J.} and Kent, {Tyler V.} and Chaochih Liu and Kono, {Thomas J.Y.} and Morrell, {Peter L.} and Jeffrey Ross-Ibarra",

note = "Funding Information: We acknowledge funding support from the US National Science Foundation (IOS-1238014 to JRI and IOS-1339393 to PLM), from a University of Minnesota Doctoral Dissertation Fellowship supporting TJYK, from USDA Hatch project CA-D-PLS-2066-H and from the University of California Davis Plant Sciences Department. Support was also provided by the Minnesota Agricultural Experiment Station Variety Development fund. We thank members of the Ross-Ibarra and Morrell Labs for discussion and software testing. We thank the authors of angsd and related programmes for answering questions, particularly Matteo Fumagalli and Filipe Vieira. Matteo Fumagalli and an anonymous reviewer provided comments that improved both the manuscript and the implementation of angsd-wrapper. Finally, we would like to thank Felix Andrews for statistical advice, although we did not follow it. Publisher Copyright: {\textcopyright} 2016 John Wiley & Sons Ltd",

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AU - Morrell, Peter L.

AU - Ross-Ibarra, Jeffrey

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angsd-wrapper: utilities for analysing next-generation sequencing data

Abstract

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