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Article

VCF2PCACluster: a simple, fast and memory-efficient tool for principal component analysis of tens of millions of SNPs.

BMC bioinformatics - 1 May 2024

He Weiming, Xu Lian, Wang JingXian, Yue Zhen, Jing Yi, Tai Shuaishuai, Yang Jian, Fang Xiaodong

Abstract excerpt

Principal component analysis (PCA) is an important and widely used unsupervised learning method that determines population structure based on genetic variation. Genome sequencing of thousands of individuals usually generate tens of millions of SNPs, making it challenging for PCA analysis and interpretation. Here we present VCF2PCACluster, a simple, fast and memory-efficient tool for Kinship estimation, PCA and...

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PMID: 38693489
DOI: 10.1186/s12859-024-05770-1
PMCID: PMC11064410

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