QuasiSeq: Analyzing RNA Sequence Count Tables Using Quasi-likelihood. Identify differentially expressed genes in RNA-seq count data using quasi-Poisson or quasi-negative binomial models with QL, QLShrink and QLSpline methods (Lund, Nettleton, McCarthy, and Smyth, 2012).
Keywords for this software
References in zbMATH (referenced in 3 articles , 1 standard article )
Showing results 1 to 3 of 3.
- Nguyen, Yet; Nettleton, Dan; Liu, Haibo; Tuggle, Christopher K.: Detecting differentially expressed genes with RNA-seq data using backward selection to account for the effects of relevant covariates (2015)
- Ji, Tieming; Liu, Peng; Nettleton, Dan: Estimation and testing of gene expression heterosis (2014)
- Lund, Steven P.; Nettleton, Dan; McCarthy, Davis J.; Smyth, Gordon K.: Detecting differential expression in RNA-sequence data using quasi-likelihood with shrunken dispersion estimates (2012)