# SCnorm: robust normalization of single-cell RNA-seq data SCnorm is an R package which can be used to normalize single-cell RNA-seq data. SCnorm is on Bioconductor and instructions for download may be found at [https://bioconductor.org/packages/release/bioc/html/SCnorm.html](https://bioconductor.org/packages/release/bioc/html/SCnorm.html). #### Can you use SCnorm on your 10X (or very sparse) dataset? SCnorm is not intended for datasets with more than ~80% zero counts, often K will not converge in these situations. Setting the FilterExpression parameter to 1 or 2 may help, but is not a guarantee. It may also be helpful to use the ditherCounts = TRUE parameter for sparse UMI based data which may contain numerous tied counts (counts of 1 and 2 for example). Additional details and a FAQ for SCnorm are described in the vignette: [SCnorm Vignette](https://bioconductor.org/packages/release/bioc/vignettes/SCnorm/inst/doc/SCnorm.pdf) ## Installation Make sure to use the latest version of SCnorm by installing it from BioConductor or GitHub. ```R source("https://bioconductor.org/biocLite.R") biocLite("SCnorm") ``` or ```R library(devtools) devtools::install_github("rhondabacher/SCnorm") ``` To access a version of SCnorm that does not require R version >= 3.4 you can download SCnorm from the development branch here: [https://github.com/rhondabacher/SCnorm/tree/devel](https://github.com/rhondabacher/SCnorm/tree/devel) ## Author Rhonda Bacher <rhonda.bacher@gmail.com> ## Cite Please cite SCnorm if you use it in your research: > Bacher R, Chu LF, Leng N, Gasch AP, Thomson JA, Stewart RM, Newton M, Kendziorski C. SCnorm: robust normalization of single-cell RNA-seq data. Nature Methods. 2017 Jun 1;14(6):584-6. [https://www.nature.com/nmeth/journal/v14/n6/full/nmeth.4263.html](https://www.nature.com/nmeth/journal/v14/n6/full/nmeth.4263.html) ## Latest Update: v1.3.1 Package updated to use SingleCellExperiment class.