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.
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
Make sure to use the latest version of SCnorm by installing it from BioConductor or GitHub.
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
Rhonda Bacher firstname.lastname@example.org
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
Latest Update: v1.3.1
Package updated to use SingleCellExperiment class.