dataBinning {RiboDiPA} | R Documentation

## Data binning

### Description

This function bins a mapped P-site data matrix for a given gene into a binned matrix, for statistical testing downstream. Data can be adaptively binned, where each gene has a different number of bins and bin widths, but the bin positions for a given gene are the same across different conditions and replicates. Alternatively, data can also be binned into bins of fixed width, down to the single-codon level.

### Usage

    dataBinning(data, bin.width = 0, zero.omit = FALSE,
        bin.from.5UTR = TRUE, cores = NULL)

### Arguments

`data` | A list of mapped P-site position matrices from the `coverage` object of the `psiteMapping` function. In each element of the list, rows correspond to replicates, while columns correspond to nucleotides across the total transcript.
`bin.width` | Binning width per bin. If specified, it is the number of codons merged per bin; if not specified, an adaptive binning width method is used.
`zero.omit` | If the `zero.omit` argument is set to `TRUE`, bins with zero mapped P-site counts across all replicates are removed from the differential pattern analysis.
`bin.from.5UTR` | When the coding region length is not any integer multiple of binning width, and if value of `bin.from.5UTR` is set to `TRUE`, the uneven width bins will be arranged at the 3' end of the total transcript. If set to `FALSE`, binning will proceed from the 3' end.
`cores` | The number of cores to use for parallel execution. If not specified, the number of cores is set to the value of `detectCores(logical = FALSE)`.

### Details

We recommend to use an adaptive bin width h following the Freedman-Diaconis rule,

h= 2*IQR/m^(1/3)

. To see certain regions of transcripts in greater detail (e.g. near the start and stop codons), a specified `bin.width` per bin can be used to check the local differential pattern, though it may lead to low power at small fold change positions and potentially high computational time.

### Value

A list of binned P-site footprint matrices: in each matrix, rows correspond to replicates, columns correspond to bins.

### See Also

`psiteMapping`

### Examples

    data(data.psite)
    data.binned <- dataBinning(data = data.psite$coverage, bin.width = 0,
        zero.omit = FALSE, bin.from.5UTR = TRUE, cores = 2)
    data.codon <- dataBinning(data = data.psite$coverage, bin.width = 1,
        zero.omit = FALSE, bin.from.5UTR = TRUE, cores = 2)

[Package RiboDiPA version 1.0.0 Index]