ctest {exomePeak2} | R Documentation

## Exact poisson test on the ratio between IP and input counts.

### Description

Exact poisson test on the ratio between IP and input counts.

### Usage

    ctest(
      IP_count,
      input_count,
      IP_sizeFactor,
      input_sizeFactor,
      fold = 1,
      alpha = 0.05
    )

### Arguments

`IP_count` | a numeric vector for the counts of IP sample.
`input_count` | a numeric vector for the counts of input sample.
`IP_sizeFactor` | a numeric vector for the size factors of IP sample.
`input_sizeFactor` | a numeric vector for the size factors of input sample.
`fold` | the fold change under the null hypothesis; default = 1.
`alpha` | the alpha level used for determining the optimal independent filtering in `filtered_R`; default = 0.05.

### Details

C-tests will be conducted between each entries of the IP and input vector.

The following statistical model is assumed on the data:

IP ~ Poisson(mean_IP*IP_sizeFactor)

input ~ Poisson(mean_input*input_sizeFactor)

The one-sided statistical test (C-test) is conducted with the following hypothesis pair:

H_0: mean(IP)/mean(input) <= fold

H_1: mean(IP)/mean(input) > fold

The exact p-values will be generated using binomial test, check `poisson.test` for more details.

The p-values are adjusted with "BH" method with an independent filtering slected by function `filtered_R` in package `genefilter`;

the filter statistics used is the normalized read abundence.

### Value

A list include adjusted p values (with method fdr) and the corresponding log2 fold changes.

[Package exomePeak2 version 1.2.0 Index]