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# 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 []( #### 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]( ## Installation Make sure to use the latest version of SCnorm by installing it from BioConductor or GitHub. ```R if (!requireNamespace("BiocManager", quietly=TRUE)) install.packages("BiocManager") BiocManager::install("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: []( ## Author Rhonda Bacher <> ## 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. []( ## Latest Update: v1.5.7 Added additional warnings when using the useSpikes option and SCnorm now supports input data in the sparse matrix format. #### Previous updates: v1.5.4 Allow separate normalizations for different Conditions for very large dataset. See vignette for example.