Man pages for jhsiao999/ashbun
Methods and evaluation tools for single cell RNA-seq count data

args.big_normalNormal mixture prior. Default 1 component.
args.bimodalbimodal prior
args.flat_topflat top prior
args.near_normalnear normal prior
args.spikyspiky prior
args.uni_naturalunimodal distribution with a non-zero mode
args.uni_natural_pm_zerobi-modal distribution, with a non-zero mode and point mass at...
args.uni_natural_uni_zerobi-modal distribution, with a non-zero mode and a mode at...
args.uni_zerounimodal distribution with mode at zero
ashPoissonWrapperash-Poisson wrapper for evaluating different bimodality...
dens_unimixcompute density for all components in the mixture prior
dens_unimix_singcompute density for a single component in the mixture prior
filter.excludeAllZerosFilter all-zero samples and features.
filterFeatures.fractionExpressedFilter genes by fraction of samples detected as expressed
filterSamples.fractionExpressedFilter samples by fraction of genes detected as expressed
filter.WrapperWrapper for all filtering steps
gene_variationPer gene variance component model
getAUCCompute AUC
getROCcompute ROC related informatino using pROC package
getROC.averagePlot ROC curve average
getTPRCompute sensitivity or true positive rate given fixed FDR
getTPR.pROCCompute sensitivity or true positive rate given fixed FDR...
ImplementMAST
make_normalmixGenerate beta (effects) from normal mixture prior
makeSimCount2groupsGenerate count matrix of all null genes
makeSimCount2groups.filterGenerate count matrix of all null genes
methodWrapper.bpscBPSC
methodWrapper.DESeq2DESeq2
methodWrapper.edgeRedgeR
methodWrapper.limmaVoomlimma + voom
methodWrapper.num_svEstimate number of surrogate variables
methodWrapper.scdeSCDE
methodWrapper.svaSurrogate Variable Analysis
negbinFit Negative binomial to gene expression counts (univariate)
negbin_hurdleHurdle negative binomial
negbin_zifZero-inflated negative binomial
non_null_simSimulate count matrix
normalize.censuscensus
normalize.cpmCounts per million
normalize.libLibrary size normalization without adjustment
normalize.rleRLE (relative log expression)
normalize.scnormSCnorm 1.1.0
normalize.scranscran
normalize.tmmTMM
pois_thinningPoisson thinning
query.evaluationEvaluate multiple normalization methods and multiple DE...
query.methodsMeanExpressionRuns multiple DE methods
query.methodsNormalizationRun multiple normalization methods
query.pipelineRun multiple normalization methods and multiple DE methods
sampleingeneRandomisation of sample at each gene
simulationWrapperWrapper for simulating M datasets
simulationWrapper.filterWrapper for simulating M datasets
voom.controlPseudocountlimma + voom
jhsiao999/ashbun documentation built on Feb. 17, 2018, 4:25 a.m.