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bioc
SingleR:Reference-Based Single-Cell RNA-Seq Annotation
Performs unbiased cell type recognition from single-cell RNA sequencing data, by leveraging reference transcriptomic datasets of pure cell types to infer the cell of origin of each single cell independently.
Maintained by Aaron Lun. Last updated 1 months ago.
softwaresinglecellgeneexpressiontranscriptomicsclassificationclusteringannotationbioconductorsinglercpp
184 stars 12.83 score 2.1k scripts 2 dependents
welch-lab
rliger:Linked Inference of Genomic Experimental Relationships
Uses an extension of nonnegative matrix factorization to identify shared and dataset-specific factors. See Welch J, Kozareva V, et al (2019) <doi:10.1016/j.cell.2019.05.006>, and Liu J, Gao C, Sodicoff J, et al (2020) <doi:10.1038/s41596-020-0391-8> for more details.
Maintained by Yichen Wang. Last updated 2 months ago.
nonnegative-matrix-factorizationsingle-cellopenblascpp
408 stars 10.77 score 334 scripts 1 dependentsbioc
celda:CEllular Latent Dirichlet Allocation
Celda is a suite of Bayesian hierarchical models for clustering single-cell RNA-sequencing (scRNA-seq) data. It is able to perform "bi-clustering" and simultaneously cluster genes into gene modules and cells into cell subpopulations. It also contains DecontX, a novel Bayesian method to computationally estimate and remove RNA contamination in individual cells without empty droplet information. A variety of scRNA-seq data visualization functions is also included.
Maintained by Joshua Campbell. Last updated 1 months ago.
singlecellgeneexpressionclusteringsequencingbayesianimmunooncologydataimportcppopenmp
147 stars 10.47 score 256 scripts 2 dependents