args.big_normal | Normal mixture prior. Default 1 component. |
args.bimodal | bimodal prior |
args.flat_top | flat top prior |
args.near_normal | near normal prior |
args.spiky | spiky prior |
args.uni_natural | unimodal distribution with a non-zero mode |
args.uni_natural_pm_zero | bi-modal distribution, with a non-zero mode and point mass at... |
args.uni_natural_uni_zero | bi-modal distribution, with a non-zero mode and a mode at... |
args.uni_zero | unimodal distribution with mode at zero |
ashPoissonWrapper | ash-Poisson wrapper for evaluating different bimodality... |
dens_unimix | compute density for all components in the mixture prior |
dens_unimix_sing | compute density for a single component in the mixture prior |
filter.excludeAllZeros | Filter all-zero samples and features. |
filterFeatures.fractionExpressed | Filter genes by fraction of samples detected as expressed |
filterSamples.fractionExpressed | Filter samples by fraction of genes detected as expressed |
filter.Wrapper | Wrapper for all filtering steps |
gene_variation | Per gene variance component model |
getAUC | Compute AUC |
getROC | compute ROC related informatino using pROC package |
getROC.average | Plot ROC curve average |
getTPR | Compute sensitivity or true positive rate given fixed FDR |
getTPR.pROC | Compute sensitivity or true positive rate given fixed FDR... |
Implement | MAST |
make_normalmix | Generate beta (effects) from normal mixture prior |
makeSimCount2groups | Generate count matrix of all null genes |
makeSimCount2groups.filter | Generate count matrix of all null genes |
methodWrapper.bpsc | BPSC |
methodWrapper.DESeq2 | DESeq2 |
methodWrapper.edgeR | edgeR |
methodWrapper.limmaVoom | limma + voom |
methodWrapper.num_sv | Estimate number of surrogate variables |
methodWrapper.scde | SCDE |
methodWrapper.sva | Surrogate Variable Analysis |
negbin | Fit Negative binomial to gene expression counts (univariate) |
negbin_hurdle | Hurdle negative binomial |
negbin_zif | Zero-inflated negative binomial |
non_null_sim | Simulate count matrix |
normalize.census | census |
normalize.cpm | Counts per million |
normalize.lib | Library size normalization without adjustment |
normalize.rle | RLE (relative log expression) |
normalize.scnorm | SCnorm 1.1.0 |
normalize.scran | scran |
normalize.tmm | TMM |
pois_thinning | Poisson thinning |
query.evaluation | Evaluate multiple normalization methods and multiple DE... |
query.methodsMeanExpression | Runs multiple DE methods |
query.methodsNormalization | Run multiple normalization methods |
query.pipeline | Run multiple normalization methods and multiple DE methods |
sampleingene | Randomisation of sample at each gene |
simulationWrapper | Wrapper for simulating M datasets |
simulationWrapper.filter | Wrapper for simulating M datasets |
voom.controlPseudocount | limma + voom |
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