Open AccessEigen-R2 for dissecting variation in high-dimensional studies
Author(s) -
Lin Chen,
John D. Storey
Publication year - 2008
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btn411
Subject(s) - bioconductor , r package , variation (astronomy) , computer science , software , software package , algorithm , data mining , computational science , biology , programming language , physics , gene , astrophysics , biochemistry
We provide a new statistical algorithm and software package called 'eigen-R(2)' for dissecting the variation of a high-dimensional biological dataset with respect to other measured variables of interest. We apply eigen-R(2) to two real-life examples and compare it with simply averaging R(2) over many features.
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