scMerge
is a R package for merging and normalising single-cell RNA-Seq datasets.
scMerge
is available on Bioconductor (https://bioconductor.org/packages/scMerge). You can install it using:
You can find the vignette at our website: https://sydneybiox.github.io/scMerge/index.html.
You can find a list of case studies here: https://sydneybiox.github.io/scMerge/articles/.
Stably expressed genes identified from this study can be extracted by
library(scMerge)
data(segList)
segList$human$human_scSEG # human SEG
segList$mouse$mouse_scSEG # mouse SEG
Or download csv files here (human SEG: link; mouse SEG: link)
For more detailed information and evaluation about SEG, please see our publication https://doi.org/10.1093/gigascience/giz106.
If you have any enquiries, especially about performing scMerge
integration on your own data, then please contact bioinformatics@maths.usyd.edu.au. You can also open an issue on GitHub.
scMerge leverages factor analysis, stable expression, and pseudoreplication to merge multiple single-cell RNA-seq datasets
Yingxin Lin, Shila Ghazanfar, Kevin Y.X. Wang, Johann A. Gagnon-Bartsch, Kitty K. Lo, Xianbin Su, Ze-Guang Han, John T. Ormerod, Terence P. Speed, Pengyi Yang, Jean Y. H. Yang
Our manuscript published at PNAS can be found here.