General Information
| Description | Integrated analysis of single-cell RNA-seq data |
| Homepage | http://sourceforge.net/projects/scell |
Publications
SCell: integrated analysis of single-cell RNA-seq data
Summary:
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/SCell.
Supplementary information:
Supplementary data are available at Bioinformatics online.
Contact:
aaron.diaz@ucsf.edu
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