Learn R Programming

sSeq (version 1.10.0)

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

Description

The purpose of this package is to discover the genes that are differentially expressed between two conditions in RNA-seq experiments. Gene expression is measured in counts of transcripts and modeled with the Negative Binomial (NB) distribution using a shrinkage approach for dispersion estimation. The method of moment (MM) estimates for dispersion are shrunk towards an estimated target, which minimizes the average squared difference between the shrinkage estimates and the initial estimates. The exact per-gene probability under the NB model is calculated, and used to test the hypothesis that the expected expression of a gene in two conditions identically follow a NB distribution.

Copy Link

Version

Version

1.10.0

License

GPL (>= 3)

Maintainer

Danni Yu

Last Published

February 15th, 2017

Functions in sSeq (1.10.0)

sim

Generating Simulated Data
nbinomTestForMatricesSH

Exact test under Negative Binomial Test with Shrinkage Estimates on Dispersions
getT

Estimate the shrinkage target based on the initial estimates
ecdfAUC

Draw Empirical Cumulative Density Function (ECDF) plot
equalSpace

Calculate Grouped Shrinkage Estimates
getTgroup

This is an internal function used to calculate the shrinkage estimation when multiple shrinkage targets are considered.
countsTable

An Example Simulation Data
getQ

Estimate the shrinkage target based on the quantiles of initial targets
getAdjustDisp

Calculate Shrinkage (SH) Estimates for Dispersion
Sultan

An example of real experiment.
getNormFactor

Estimate size factors
nbTestSH

Differential Analysis based on RNA-seq experiments using Negative Binomial (NB) Model with Shrinkage Approach of Dispersion Estimation.
Tuch

An example of real experiment.
exactNBtest1

Perform only one exact test under the Negative Binomial modeling.
drawMA_vol

Draw MA Plot and Volcano Plot
rowVars

Calculating the sample variance within each row of A matrix
plotDispersion

Drawing Dispersion-Mean plot.
sSeq-package

Shrinkage estimation of dispersion in Negative Binomial models for RNA-seq experiments with small sample size
Hammer2months

An example of real experiment.
rnbinomMV

Randomly Generate Negative Binomial Variable with parameters mean and variance.