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

bioRxiv

Jan 30, 2014

Gad Abraham, Michael Inouye

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

Silo (Dataset)
Familial Lichen Amyloidosis
Nucleotides
Genetic Polymorphism
Genome-Wide Association Study
Randomization
Malpighian Tubule Principal Cell Differentiation
Size
Structure
Single Nucleotide Polymorphism
26
8
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Fast Principal Component Analysis of Large-Scale Genome-Wide Data

bioRxiv

Jan 30, 2014

Gad Abraham, Michael 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

Silo (Dataset)
Familial Lichen Amyloidosis
Nucleotides
Genetic Polymorphism
Genome-Wide Association Study
Randomization
Malpighian Tubule Principal Cell Differentiation
Size
Structure
Single Nucleotide Polymorphism
26
8

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