Poisson scRNA Integration of Mixed Unknown Signals
PRIMUS is a holistic clustering approach that identifies phenotypic cell groups from the scRNA-seq data while accounting for date source (e.g. patient, sample, dataset) -specific components as well as technical noises.
PRIMUS uses a bilinear Poisson regression model to simultaneously factorize the expression data into the defined nuisance factors, undefined cellular phenotypes, and their corresponding transcriptomic profiles.
To run PRIMUS, open R and install PRIMUS from github:
devtools::install_github("KaiyangZ/PRIMUS")
As input PRIMUS takes raw counts from scRNA-seq experiments, a design matrix encoding the different nuisance factors, such as patient labels and technical factors, and a vector of size factors. Check out this vignette for a quick start tutorial.
Zhang K, Erkan EP, Jamalzadeh S, Dai J, Andersson N, Kaipio K, Lamminen T, Mansuri N, Huhtinen K, Carpén O, Hietanen S, Oikkonen J, Hynninen J, Virtanen A, Häkkinen A, Hautaniemi S, Vähärautio A. Longitudinal single-cell RNA-seq analysis reveals stress-promoted chemoresistance in metastatic ovarian cancer. Sci Adv. 2022 Feb 25;8(8):eabm1831. doi: 10.1126/sciadv.abm1831. Epub 2022 Feb 23. PMID: 35196078.