DEsingle - DEsingle for detecting three types of differential expression in single-cell RNA-seq data
DEsingle is an R package for differential expression (DE) analysis of single-cell RNA-seq (scRNA-seq) data. It defines and detects 3 types of differentially expressed genes between two groups of single cells, with regard to different expression status (DEs), differential expression abundance (DEa), and general differential expression (DEg). DEsingle employs Zero-Inflated Negative Binomial model to estimate the proportion of real and dropout zeros and to define and detect the 3 types of DE genes. Results showed that DEsingle outperforms existing methods for scRNA-seq DE analysis, and can reveal different types of DE genes that are enriched in different biological functions.
Last updated 4 months ago
differentialexpressiongeneexpressionsinglecellimmunooncologyrnaseqtranscriptomicssequencingpreprocessingsoftware
30 stars 3.64 score 29 dependenciesscRecover - scRecover for imputation of single-cell RNA-seq data
scRecover is an R package for imputation of single-cell RNA-seq (scRNA-seq) data. It will detect and impute dropout values in a scRNA-seq raw read counts matrix while keeping the real zeros unchanged, since there are both dropout zeros and real zeros in scRNA-seq data. By combination with scImpute, SAVER and MAGIC, scRecover not only detects dropout and real zeros at higher accuracy, but also improve the downstream clustering and visualization results.
Last updated 4 months ago
geneexpressionsinglecellrnaseqtranscriptomicssequencingpreprocessingsoftware
8 stars 1.45 score 36 dependencies