R: Shrinkage estimation of dispersion in Negative Binomial models for RNA-seq experiments with small sample size

# Shrinkage estimation of dispersion in Negative Binomial models for RNA-seq experiments with small sample size

## Documentation for package ‘sSeq’ version 1.50.0

- DESCRIPTION file
- User guides, package vignettes and other documentation

## Help Pages

sSeq-package | Shrinkage estimation of dispersion in Negative Binomial models for RNA-seq experiments with small sample size
countsTable | An Example Simulation Data
drawMA_vol | Draw MA Plot and Volcano Plot
ecdfAUC | Draw Empirical Cumulative Density Function (ECDF) plot
equalSpace | Calculate Grouped Shrinkage Estimates
exactNBtest1 | Perform only one exact test under the Negative Binomial modeling.
getAdjustDisp | Calculate Shrinkage (SH) Estimates for Dispersion
getNormFactor | Estimate size factors
getQ | Estimate the shrinkage target based on the quantiles of initial targets
getT | Estimate the shrinkage target based on the initial estimates
getTgroup | This is an internal function used to calculate the shrinkage estimation when multiple shrinkage targets are considered.
Hammer2months | An example of real experiment.
nbinomTestForMatricesSH | Exact test under Negative Binomial Test with Shrinkage Estimates on Dispersions
nbTestSH | Differential Analysis based on RNA-seq experiments using Negative Binomial (NB) Model with Shrinkage Approach of Dispersion Estimation.
plotDispersion | Drawing Dispersion-Mean plot.
rnbinomMV | Randomly Generate Negative Binomial Variable with parameters mean and variance.
rowVars | Calculating the sample variance within each row of A matrix
sim | Generating Simulated Data
sSeq | Shrinkage estimation of dispersion in Negative Binomial models for RNA-seq experiments with small sample size
Sultan | An example of real experiment.
Tuch | An example of real experiment.