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Analysis Tools Registry

Single-cell consensus clustering (SC3)

Martin Hemberg (SC3), Gene Expression Team (sc3-scripts)

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SC3 is an unsupervised clustering method for scRNA-seq data. SC3 also estimates the number of clusters and it provides features to aid the biological interpretation of the clusters. sc3-scripts provides a set of simple wrappers with robust argument parsing for individual components of the SC3 package.

Use

docker pull quay.io/biocontainers/bioconductor-sc3-scripts:0.0.3--r351_0

How to perform unsupervised clustering on scRNA-seq data (already QCed and normalised) in a SingleCellExperiment object

curl -L -o deng-reads.rds https://github.com/hemberg-lab/scRNA.seq.course/raw/master/deng/deng-reads.rds

curl -L -o  sc3-sc3.R https://raw.githubusercontent.com/ebi-gene-expression-group/bioconductor-sc3-scripts/develop/sc3-sc3.R

docker run -v ${PWD}:/data -w /data --rm quay.io/biocontainers/bioconductor-sc3-scripts:0.0.3--r351_0 Rscript sc3-sc3.R -i deng-reads.rds -o deng-sc3.rds 

Validate

Run this command to confirm your container produces correct reference output:

curl -L -o  sc3-sc3-validate.R https://raw.githubusercontent.com/ebi-gene-expression-group/bioconductor-sc3-scripts/develop/sc3-sc3-validate.R

docker run -v ${PWD}:/data -w /data --rm quay.io/biocontainers/bioconductor-sc3-scripts:0.0.3--r351_0 Rscript sc3-sc3-validate.R

Contact

Martin Hemberg, SC3 (mh26@sanger.ac.uk)
Gene Expression Team, sc3-scripts (gene-expression@ebi.ac.uk)

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