pcaMethods--a bioconductor package providing PCA methods for incomplete data

Bioinformatics. 2007 May 1;23(9):1164-7. doi: 10.1093/bioinformatics/btm069. Epub 2007 Mar 7.


pcaMethods is a Bioconductor compliant library for computing principal component analysis (PCA) on incomplete data sets. The results can be analyzed directly or used to estimate missing values to enable the use of missing value sensitive statistical methods. The package was mainly developed with microarray and metabolite data sets in mind, but can be applied to any other incomplete data set as well.

Availability: http://www.bioconductor.org

Publication types

  • Evaluation Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms*
  • Databases, Genetic*
  • Gene Expression Profiling / methods*
  • Information Storage and Retrieval / methods
  • Models, Genetic*
  • Models, Statistical
  • Oligonucleotide Array Sequence Analysis / methods*
  • Principal Component Analysis*
  • Sample Size
  • Software*