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Data Management and Summary Statistics with PLINK

Chang, Christopher C. (2020) Data Management and Summary Statistics with PLINK. In: Statistical Population Genomics. Methods in Molecular Biology. No.2090. Humana Press , New York, NY, pp. 49-65. ISBN 978-1-0716-0198-3. https://resolver.caltech.edu/CaltechAUTHORS:20200127-141801552

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Abstract

PLINK is a versatile program which supports data management, quality control, and common statistical computations on matrices of genomic variant calls, in a computationally efficient manner. In population genomics, it is frequently used to take care of the “basics,” so they do not need to be reimplemented when a new type of analysis needs to be performed on such a matrix. I describe several of these basic operations, and discuss uses and pitfalls.


Item Type:Book Section
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https://doi.org/10.1007/978-1-0716-0199-0_3DOIArticle
Additional Information:© 2020 The Author(s). This chapter is licensed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made. The images or other third party material in this chapter are included in the chapter's Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the chapter's Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. First Online: 24 January 2020.
Subject Keywords:Allele frequency; Hardy–Weinberg equilibrium; Linkage disequilibrium; Principal component analysis; Relationship inference; Sex inference; Variant call format
Series Name:Methods in Molecular Biology
Issue or Number:2090
Record Number:CaltechAUTHORS:20200127-141801552
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20200127-141801552
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:100952
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:28 Jan 2020 18:32
Last Modified:28 Jan 2020 18:32

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