callParameterwithoutReplicates {ABSSeq} | R Documentation

## Calculate parameters for differential expression test base on absolute counts differences without replicates

### Description

Calculate parameters for each gene (the moderating basemean and dispersions), without replicates

### Usage

    callParameterwithoutReplicates(object)

### Arguments

`object` | a `ABSDataSet` object.

### Details

buliding a pseudo group to esitimate parameter by mean difference. shifted and calculate a set of parameters from normalized counts table before `callDEs`

### Value

A ABSDataSet object with absolute differences, basemean, mean of each group, variance, log2 of foldchange, named as 'absD', 'baseMean', 'Amean', 'Bmean', 'Variance' and 'foldChange', respectively. Use the `results` to get access it

### Note

This function should run after `normalFactors` or providing size factors. This function firstly constructs an expression level depended fold-change cutoffs and then separate the data into two groups. The group with fold-change less than cutoffs is used to training the dispersion. However, the cutoff might be too small when applied on data set without or with less DEs. To avoid it, we set a prior value (0.5) to it.

### Examples

    data(simuN5)
    obj <- ABSDataSet(counts=(simuN5$counts)[,c(1,2)], groups=factor(c(1,2)))
    obj <- normalFactors(obj)
    obj <- callParameterwithoutReplicates(obj)
    obj <- callDEs(obj)
    head(results(obj))

[Package ABSSeq version 1.44.0 Index]