PSIKO2: a fast and versatile tool to infer population stratification on various levels in GWAS

Andrei-Alin Popescu; Katharina Huber

doi:10.1093/bioinformatics/btv396

PSIKO2: a fast and versatile tool to infer population stratification on various levels in GWAS

Andrei-Alin Popescu, Katharina Huber

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Abstract

Genome-Wide Association Studies are an invaluable tool for identifying genotypic loci linked with agriculturally important traits or certain diseases. The signal on which such studies rely upon can however be obscured by population stratification making it necessary to account for it in some way. Population stratification is dependent on when admixture happend and thus can occur at various levels. To aid in its inference at the genome-level, we recently introduced PSIKO and comparison with leading methods indicate that it has attractive properties. However uptil now it could not be used for local ancestry inference (LAI) which is preferable in cases of recent admixture as the genome level tends to be too coarse to properly account for processes acting on small segments of a genome.To also bring the powerful ideas underpinning PSIKO to bear in such studies, we extended it to PSIKO2 which we introduce here.

Availability: Source code, binaries, and user manual are freely available at
\url{https://www.uea.ac.uk/computing/psiko}.

Original language	English
Pages (from-to)	3552-3554
Number of pages	13
Journal	Bioinformatics
Volume	31
Issue number	21
Early online date	2 Jul 2015
DOIs	https://doi.org/10.1093/bioinformatics/btv396
Publication status	Published - 1 Nov 2015

Keywords

Q-matrix
population stratification
Local Ancestry Inference
GWAS
Genome-Wide Association Studies

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10.1093/bioinformatics/btv396

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This is a pre-copyedited, author-produced PDF of an article accepted for publication in Bioinformatics following peer review. The version of record [insert complete citation information here] is available online at: xxxxxxx [insert URL that the author will receive upon publication here].
Accepted author manuscript, 120 KB

https://www.uea.ac.uk/computing/psiko

Katharina Huber
- K.Huberuea.acuk
- School of Computing Sciences - Associate Professor
- Computational Biology - Member
Person: Research Group Member, Academic, Teaching & Research

Cite this

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title = "PSIKO2: a fast and versatile tool to infer population stratification on various levels in GWAS",

abstract = "Genome-Wide Association Studies are an invaluable tool for identifying genotypic loci linked with agriculturally important traits or certain diseases. The signal on which such studies rely upon can however be obscured by population stratification making it necessary to account for it in some way. Population stratification is dependent on when admixture happend and thus can occur at various levels. To aid in its inference at the genome-level, we recently introduced PSIKO and comparison with leading methods indicate that it has attractive properties. However uptil now it could not be used for local ancestry inference (LAI) which is preferable in cases of recent admixture as the genome level tends to be too coarse to properly account for processes acting on small segments of a genome.To also bring the powerful ideas underpinning PSIKO to bear in such studies, we extended it to PSIKO2 which we introduce here. Availability: Source code, binaries, and user manual are freely available at\url{https://www.uea.ac.uk/computing/psiko}. ",

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author = "Andrei-Alin Popescu and Katharina Huber",

note = "This is a pre-copyedited, author-produced PDF of an article accepted for publication in Bioinformatics following peer review. The version of record, Popescu and Huber, Bioinformatics (2015) doi: 10.1093/bioinformatics/btv396, is available online at: http://bioinformatics.oxfordjournals.org/content/early/2015/07/24/bioinformatics.btv396.",

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N2 - Genome-Wide Association Studies are an invaluable tool for identifying genotypic loci linked with agriculturally important traits or certain diseases. The signal on which such studies rely upon can however be obscured by population stratification making it necessary to account for it in some way. Population stratification is dependent on when admixture happend and thus can occur at various levels. To aid in its inference at the genome-level, we recently introduced PSIKO and comparison with leading methods indicate that it has attractive properties. However uptil now it could not be used for local ancestry inference (LAI) which is preferable in cases of recent admixture as the genome level tends to be too coarse to properly account for processes acting on small segments of a genome.To also bring the powerful ideas underpinning PSIKO to bear in such studies, we extended it to PSIKO2 which we introduce here. Availability: Source code, binaries, and user manual are freely available at\url{https://www.uea.ac.uk/computing/psiko}.

AB - Genome-Wide Association Studies are an invaluable tool for identifying genotypic loci linked with agriculturally important traits or certain diseases. The signal on which such studies rely upon can however be obscured by population stratification making it necessary to account for it in some way. Population stratification is dependent on when admixture happend and thus can occur at various levels. To aid in its inference at the genome-level, we recently introduced PSIKO and comparison with leading methods indicate that it has attractive properties. However uptil now it could not be used for local ancestry inference (LAI) which is preferable in cases of recent admixture as the genome level tends to be too coarse to properly account for processes acting on small segments of a genome.To also bring the powerful ideas underpinning PSIKO to bear in such studies, we extended it to PSIKO2 which we introduce here. Availability: Source code, binaries, and user manual are freely available at\url{https://www.uea.ac.uk/computing/psiko}.

KW - Q-matrix

KW - population stratification

KW - Local Ancestry Inference

KW - GWAS

KW - Genome-Wide Association Studies

U2 - 10.1093/bioinformatics/btv396

DO - 10.1093/bioinformatics/btv396

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SP - 3552

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JO - Bioinformatics

JF - Bioinformatics

SN - 1367-4803

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ER -

PSIKO2: a fast and versatile tool to infer population stratification on various levels in GWAS

Abstract

Keywords

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Katharina Huber

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