qiuxiazhou / raceid3_stemid2

Algorithm for the inference of cell types and lineage trees from single-cell RNA-seq data. Please download the R package from the RaceID3_StemID2_package repository, which contains the current version as an R package. This repository will not be updated anymore.

PLEASE USE THE NEW RACEID PACKAGE on CRAN OR https://github.com/dgrun/RaceID3_StemID2_package ! THIS IS REPLACING THE RACEID SCRIPTS IN THIS REPOSITORY!

StemID2 and RaceID3 algorithms

RaceID3 is an advanced version of RaceID, an algorithm for the identification of rare and abundant cell types from single cell transcriptome data. The method is based on transcript counts obtained with unique molecular identifies.

StemID2 is an algorithm for the derivation of cell lineage trees based on RaceID3 results and predicts multipotent cell identites.

RaceID3 and StemID2 are written in the R computing language.

The following files are provided:

StemID2/RaceID3 class definition: RaceID3_StemID2_class.R StemID2/RaceID3 sample code: RaceID3_StemID2_sample.R StemID2/RaceID3 reference manual: Reference_manual_RaceID3_StemID2.pdf StemID2/RaceID3 sample data: transcript_counts_intestine_5days_YFP.xls

Reference RaceID3 and StemID2:

Herman, JS. et al. FateID infers cell fate bias in multipotent progenitors from single-cell RNA-seq data. Nature Methods 15(5):379-386 (2018).

Reference RaceID2 and StemID: Grün, D. et al. De Novo Prediction of Stem Cell Identity using Single-Cell Transcriptome Data. Cell Stem Cell 19, 266–277 (2016).

Reference RaceID: Grün, D. et al. Single-cell messenger RNA sequencing reveals rare intestinal cell types. Nature 525, 251–5 (2015).