consDESeq2_M {exomePeak2} | R Documentation

## Calculate the index for across sample modification consistency in a DESeqDataSet object

### Description

Calculate the index for across sample modification consistency in a DESeqDataSet object

### Usage

    consDESeq2_M(
      dds,
      consistent_log2FC_cutoff = 1,
      consistent_fdr_cutoff = 0.05,
      p0 = 0.8,
      alpha = 0.05
    )

### Arguments

`dds` | a DESeqDataSet object.
`consistent_log2FC_cutoff` | a `numeric` for the modification log2 fold changes cutoff in the peak consisency calculation; default = 1.
`consistent_fdr_cutoff` | a `numeric` for the BH adjusted C-test p values cutoff in the peak consistency calculation; default = 0.05. Check `ctest`.
`p0` | a `numeric` for the binomial proportion parameter used in the consistent peak filter; default `= 0.8`. For a peak to be consistently methylated, the minimum number of significant enriched replicate pairs is defined as the 1 - alpha quantile of a binomial distribution with p = p0 and N = number of possible pairs between replicates. The consistency defined in this way is equivalent to the rejection of an exact binomial test with null hypothesis of p < p0 and N = replicates number of IP * replicates number of input.
`alpha` | a `numeric` for the binomial quantile used in the consitent peak filter; default`= 0.05`.

### Details

The minimum consistent number cutcoff is defined by 1-alpha quantile of a binomial distribution with probability of success = p, and number of trials = number of possible pairs between replicates. This is equivalent to the rejection of an exact binomial test with null hypothesis of p < 0.8 and N = number of possible pairs.

### Value

a logical index for the consistently modified rows in the DESeqDataSet.

[Package exomePeak2 version 1.2.0 Index]