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Applying stability selection to consistently estimate sparse principal components in high-dimensional molecular data

Motivation: Principal component analysis (PCA) is a basic tool often used in bioinformatics for visualization and dimension reduction. However, it is known that PCA may not consistently estimate the true direction of maximal variability in high-dimensional, low sample size settings, which are typica...

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Shranjeno v:
Bibliografske podrobnosti
izdano v:Bioinformatics
Main Authors: Sill, Martin, Saadati, Maral, Benner, Axel
Format: Artigo
Jezik:Inglês
Izdano: Oxford University Press 2015
Teme:
Online dostop:https://ncbi.nlm.nih.gov/pmc/articles/PMC4528629/
https://ncbi.nlm.nih.gov/pubmed/25861969
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1093/bioinformatics/btv197
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