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findPC: An R package to automatically select the number of principal components in single-cell analysis
Ist Teil von
Bioinformatics, 2022-05, Vol.38 (10), p.2949-2951
Ort / Verlag
England: Oxford University Press
Erscheinungsjahr
2022
Quelle
EZB Electronic Journals Library
Beschreibungen/Notizen
Abstract
Summary
Principal component analysis is widely used in analyzing single-cell genomic data. Selecting the optimal number of principal components (PCs) is a crucial step for downstream analyses. The elbow method is most commonly used for this task, but it requires one to visually inspect the elbow plot and manually choose the elbow point. To address this limitation, we developed six methods to automatically select the optimal number of PCs based on the elbow method. We evaluated the performance of these methods on real single-cell RNA-seq data from multiple human and mouse tissues and cell types. The perpendicular line method with 30 PCs has the best overall performance, and its results are highly consistent with the numbers of PCs identified manually. We implemented the six methods in an R package, findPC, that objectively selects the number of PCs and can be easily incorporated into any automatic analysis pipeline.
Availability and Implementation
findPC R package is freely available at https://github.com/haotian-zhuang/findPC.
Supplementary information
Supplementary data are available at Bioinformatics online.
Sprache
Englisch
Identifikatoren
ISSN: 1367-4803
eISSN: 1460-2059, 1367-4811
DOI: 10.1093/bioinformatics/btac235
Titel-ID: cdi_proquest_miscellaneous_2664800237
Format
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