title: pcaMethods--a bioconductor package providing PCA methods for incomplete data.
abstract: 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.
  
  
  BACKGROUND
  http://www.bioconductor.org
authors.affiliation: CAS-MPG Partner Institute for Comp. Biology, Shanghai, China.
authors.forename: Wolfram
authors.initials: W
authors.lastname: Stacklies
authors.forename: Henning
authors.initials: H
authors.lastname: Redestig
authors.forename: Matthias
authors.initials: M
authors.lastname: Scholz
authors.forename: Dirk
authors.initials: D
authors.lastname: Walther
authors.forename: Joachim
authors.initials: J
authors.lastname: Selbig
mesh_terms: D000465:Algorithms; D030541:Databases, Genetic; D020869:Gene Expression Profiling / Q000379:methods*; D016247:Information Storage and Retrieval / Q000379:methods; D008957:Models, Genetic; D015233:Models, Statistical; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D025341:Principal Component Analysis; D018401:Sample Size; D012984:Software