MAST
A logistic regression model is
used to test differentialexpression rate betweengroups while a Gaussiangeneralized linear model(GLM) describes expressionconditionally on non-zeroexpression estimates. Modelsare corrected for cellulardetection rateRequires normalized gene
expression estimates andprovides gene-specific P valuesfrom summing likelihood ratioor Wald tests from the twocomponentsFramework Command
lineUnix/
Linux,Mac OS,WindowsR[
90
]
D3EA tool for identifyingdifferentially expressed genes,based on single-cell RNA-seqdata. D3E consists of twomodules: one for identifyingdifferentially expressed(DE) genes and one for fittingthe parameters of a Poisson-Beta distributionD3E takes a read count table asan input, with rows andcolumns corresponding totranscripts and cells,respectively. The user shouldsplit the columns into two ormore groups by providing celllabels in the input file. If thereare more than two groups ofcells, they must be comparedone pair at a timePackageCommandlineUnix/LinuxPython[^91]scDDModels expressed counts as aDirichlet process mixture(DPM) of normals to test fordifferentially distributed(DD) genes associated withmultimodality in the expressedcomponent. Samples from theposterior further characterizethe gene-specificdistributional differencebetween two biologicalconditions to identify genesthat are differentiallyexpressed (DE), differ in theRequires normalized,log-transformed geneexpression estimates andprovides gene-specific P values(or a false discovery rate(FDR)-controlled list) of DDgenes between two biologicalconditions. Each DD gene isthen classified into a specifictype of distributionaldifferenceFramework,packageCommandlineUnix/Linux,Mac OS,WindowsR[92,^93](continued)Applications of Single-Cell Sequencing for Multiomics 341