Unlabelled: Analysis of the composition of heterogeneous tissue has been greatly enabled by recent developments in single-cell transcriptomics. We present SCell, an integrated software tool for quality filtering, normalization, feature selection, iterative dimensionality reduction, clustering and the estimation of gene-expression gradients from large ensembles of single-cell RNA-seq datasets. SCell is open source, and implemented with an intuitive graphical interface. Scripts and protocols for the high-throughput pre-processing of large ensembles of single-cell, RNA-seq datasets are provided as an additional resource.
Availability And Implementation: Binary executables for Windows, MacOS and Linux are available at http://sourceforge.net/projects/scell, source code and pre-processing scripts are available from https://github.com/diazlab/SCellSupplementary information: Supplementary data are available at Bioinformatics online.
Contact: aaron.diaz@ucsf.edu.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4937196 | PMC |
| http://dx.doi.org/10.1093/bioinformatics/btw201 | DOI Listing |
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