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pcaMethods—a bioconductor package providing PCA methods for incomplete data
Open accessAbstract
Summary: 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 Contact: selbig@mpimp-golm.mpg.de Supplementary information: Please visit our webpage at http://bioinformatics.mpimp-golm.mpg.de/
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“A uthor M anuscript A uthor M anuscript A uthor M anuscript A uthor M anuscript REAGENT or RESOURCE SOURCE IDENTIFIER MaxQuant Cox lab, Max Planck Institute of Biochemistry, Germany https://www.maxquant.org Perseus Cox lab, Max Planck Institute of Biochemistry, Germany https://maxquant.net/perseus/ R version (3.5.2) R…”
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Metadata
- Authors
- Stacklies, W., Redestig, H., Scholz, M., Walther, D., & Selbig, J.
- Venue
- Bioinformatics
- Publisher
- Oxford University Press (OUP)
- Published
- 2007-03-07
- Volume
- 23
- Issue
- 9
- Pages
- 1164-1167
- ISSN
- 1367-4803 (ISSN-L)
- 1367-4811
- OpenAlex
- W2167942713
- Cited by
- 1,151
- References
- 0
- FWCI
- 2.63
- Type
- journal article
- Language
- en
- Open access
- hybrid
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- Stacklies, W., Redestig, H., Scholz, M., Walther, D., & Selbig, J. (2007). pcaMethods—a bioconductor package providing PCA methods for incomplete data. Bioinformatics. https://doi.org/10.1093/bioinformatics/btm069
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