Evidence map›Paper›PMID 27216439›Full record

ArticleBMC bioinformatics2016

Efficient analysis of large datasets and sex bias with ADMIXTURE.

Suyash S Shringarpure, Carlos D Bustamante, Kenneth Lange, David H Alexander

Abstract read
In one paragraph

Article in BMC bioinformatics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

30 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Suyash S ShringarpureDepartment of Genetics, Stanford University, Stanford, California, USA. suyashs@stanford.edu.
Carlos D BustamanteDepartment of Genetics, Stanford University, Stanford, California, USA.
Kenneth LangeDepartment of Biomathematics, UCLA, Los Angeles, California, USA.
David H AlexanderPacific Biosciences, Menlo Park, California, USA.

Funding

Clinically Relevant Genome Variation DatabaseU01HG007436 · NHGRI · STANFORD UNIVERSITY · PI BUSTAMANTE, CARLOS DANIEL, PLON, SHARON E. · 2013 to 2016
$10.5M
STATISTICAL METHODS FOR GENE MAPPINGR01GM053275 · NIGMS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI LANGE, KENNETH L · 1995 to 2019
$9.3M
Genomics, GPUs, and Next Generation Computational StatisticsR01HG006139 · NHGRI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI SOBEL, ERIC · 2011 to 2023
$5.1M
NHGRI NIH HHS HG006139NHGRI NIH HHS R01 HG006139NHGRI NIH HHS U01 HG007436NHGRI NIH HHS U01HG007436NIGMS NIH HHS GM053275NIGMS NIH HHS R01 GM053275
6 · The paper itself

Abstract

backgroundA number of large genomic datasets are being generated for studies of human ancestry and diseases. The ADMIXTURE program is commonly used to infer individual ancestry from genomic data.

resultsWe describe two improvements to the ADMIXTURE software. The first enables ADMIXTURE to infer ancestry for a new set of individuals using cluster allele frequencies from a reference set of individuals. Using data from the 1000 Genomes Project, we show that this allows ADMIXTURE to infer ancestry for 10,920 individuals in a few hours (a 5 × speedup). This mode also allows ADMIXTURE to correctly estimate individual ancestry and allele frequencies from a set of related individuals. The second modification allows ADMIXTURE to correctly handle X-chromosome (and other haploid) data from both males and females. We demonstrate increased power to detect sex-biased admixture in African-American individuals from the 1000 Genomes project using this extension.

conclusionsThese modifications make ADMIXTURE more efficient and versatile, allowing users to extract more information from large genomic datasets.

Indexed as

Genetics, PopulationSoftwareBlack or African AmericanFemaleGene FrequencyGenomicsHapMap ProjectHumansMaleSouthwestern United StatesAdmixtureAncestry inferencePedigreesReference panelsSex biasSex-chromosomeSupervised learning

Identifiers

PMID27216439
PMCPMC4877806

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.