genAFold {ABSSeq} | R Documentation

## Calculate parameters for differential expression test base on absolute counts differences

### Description

Calculate aFold for each gene and general sd

### Usage

    genAFold(nncounts, cond, preval = 0.05, qforkappa = 0, priorgenesd)

### Arguments

`nncounts` | matrix for read count.
`cond` | factor for conditions. If provide only one condition, fold-change estimation will be suppressed.
`preval` | pre-defined scale control for variance normalization, default is 0.05, a large value generally increases the fold-changes (decreases penalty of variances) under low expression.
`qforkappa` | quantile for estimating kappa(>=qforkappa), default is 0 (without trimming of data). Please set up a value in [0,1) if you want to trim the low expressed data.
`priorgenesd` | prior value for general SD of fold change, if provided, the estimation of general SD will be replaced by this value.

### Details

shifted and calculate a set of parameters from normalized counts table before `callDEs`

### Value

A list with log2 foldchange, general SD for calculating pvalue, variance stabilized counts and expression level adjusted counts (used for PCA analysis).

### Note

This function should run after `normalFactors`.

### Examples

    data(simuN5)
    obj <- ABSDataSet(counts=simuN5$counts, groups=factor(simuN5$groups))
    mtx <- counts(obj,TRUE)
    aFold <- genAFold(mtx,factor(simuN5$groups))
    hist(aFold[[1]])

[Package ABSSeq version 1.32.3 Index]