estimateSeqDepth-methods {exomePeak2} | R Documentation

## Method estimateSeqDepth

### Description

`estimateSeqDepth` estimate sequencing depth size factors for each MeRIP-seq samples used in peak statistics quantification. Under default setting, the sequencing depth are estimated by the robust estimator defined in package `DESeq`. i.e. the median of the ratios to the geometric means of peak counts.

### Usage

    estimateSeqDepth(sep, from = c("Background", "Modification", "All"), ...)

    ## S4 method for signature 'SummarizedExomePeak'
    estimateSeqDepth(sep, from = c("Background", "Modification", "All"), ...)

### Arguments

`sep` | a `SummarizedExomePeak` object.
`from` | a `character` specify the subset of features for sequencing depth estimation, can be one of `c("Background", "Modification", "All")`. `Background` The sequencing depths are estimated from the background control regions. This method could make the IP/input LFC estimates become closer to the true modification proportion. `Modification` The sequencing depths are estimated from the modification peaks/sites. `All` The sequencing depths are estimated from both the background and the modification regions. Under the default settings, the sequencing depth size factors are estimated from the background control regions.
`...` | inherited from `estimateSizeFactorsForMatrix`.

### Details

The function takes the input of a `SummarizedExomePeak` object, and it estimates the sequencing depth size factors by the columns of its assay.

### Value

This function will return a `SummarizedExomePeak` object containing newly estimated sequencing depth size factors.

### See Also

`normalizeGC`

### Examples

    ### Load the example SummarizedExomPeak object
    f1 = system.file("extdata", "sep_ex_mod.rds", package="exomePeak2")

    sep <- readRDS(f1)

    ### Estimate the sequencing depth size factors
    sep <- estimateSeqDepth(sep)

    sep$sizeFactor

[Package exomePeak2 version 1.4.2 Index]