This is a toolbox for processing raw sequencing output from Split-seq experiments into a digital gene expression matrix that will contain integer counts of the number of transcripts per single cell. It provides a bash script that serves as a wrapper for multiple analysis steps, including demultiplexing of the raw data by molecular (UMI) and cellular barcode, filtering cellular barcodes by a list of expected barcodes, alignment of reads to a reference genome, collecting basic QC metrics and counting UMIs per cell.

The pipeline uses some custom python scripts, and many tools from the Drop-seq toolbox (Mc Caroll lab, Harvard Medical school) as well as Picard (Broad institute), which are all included in this toolbox.

Please refer to the user manual for a description of how to use it.

This toolbox is provided by the Snijder lab formerly at ETH Zurich, now at Botnar Institute of Immune Engineering (BIIE).

If you have questions or find a bug, son't hesitate to contact Rebekka Wegmann: rebekka.wegmann@immune.engineering

This tool comes with no warranty and accurate function is not guaranteed. It laso does not exactly recapitulate the approach described in the SPLiT-seq paper. Currently, we use only the poly-T RT primers, therefore this tool does not collapse the random hexamer and polyT barcodes!