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Fast Principal Component Analysis of Large-Scale Genome-Wide Data

bioRxiv

Jan 30, 2014

Gad Abraham, Michael T Inouye

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Abstract

Principal component analysis (PCA) is routinely used to analyze genome-wide single-nucleotide polymorphism (SNP) data, for detecting population structure and potential outliers. However, the size of SNP datasets has increased immensely in recent years and PCA of large datasets has becom...read more

Mentioned in this Paper

Single Nucleotide Polymorphism
Genetic Polymorphism
Population Group
Randomization
Genome-Wide Association Study
Structure
Size
Familial Lichen Amyloidosis
Silo (Dataset)
Analysis
26
8
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  • Fast Principal Component Analysis of Large-Scale Genome-Wide Data

    bioRxiv

    Jan 30, 2014

    Gad Abraham, Michael T Inouye

    PMID: 990002238

    DOI: 10.1101/002238

    Abstract

    Principal component analysis (PCA) is routinely used to analyze genome-wide single-nucleotide polymorphism (SNP) data, for detecting population structure and potential outliers. However, the size of SNP datasets has increased immensely in recent years and PCA of large datasets has becom...read more

    Mentioned in this Paper

    Single Nucleotide Polymorphism
    Genetic Polymorphism
    Population Group
    Randomization
    Genome-Wide Association Study
    26
    8

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