scPCA: A toolbox for sparse contrastive principal component analysis in R

R Submitted 28 January 2020Published 25 February 2020
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Editor: @csoneson (all papers)
Reviewers: @fabian-s (all reviews), @LTLA (all reviews)

Authors

Philippe Boileau (0000-0002-4850-2507), Nima S. Hejazi (0000-0002-7127-2789), Sandrine Dudoit (0000-0002-6069-8629)

Citation

Boileau et al., (2020). scPCA: A toolbox for sparse contrastive principal component analysis in R. Journal of Open Source Software, 5(46), 2079, https://doi.org/10.21105/joss.02079

@article{Boileau2020, doi = {10.21105/joss.02079}, url = {https://doi.org/10.21105/joss.02079}, year = {2020}, publisher = {The Open Journal}, volume = {5}, number = {46}, pages = {2079}, author = {Philippe Boileau and Nima S. Hejazi and Sandrine Dudoit}, title = {`scPCA`: A toolbox for sparse contrastive principal component analysis in `R`}, journal = {Journal of Open Source Software} }
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dimensionality reduction principal component analysis computational biology unwanted variation sparsity

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ISSN 2475-9066