cleaning_filter {CNVgears} | R Documentation

## Filter CNVs calls based on several parameters

### Description

`cleaning_filter` "clean" a CNV calls dataset based on measures such as length, number of calls per sample and more.

### Usage

    cleaning_filter(
      results,
      min_len = 10000,
      min_NP = 10,
      blacklists = NULL,
      blacklist_samples = NULL,
      blacklist_chrs = NULL
    )

### Arguments

`results,` | a `data.table`, the output of `read_results`.
`min_len,` | minimum CNVs length, any shorter event will be filtered out. Default is 10000.
`min_NP,` | minimum CNVs points, any shorter event will be filtered out. Default is 10.
`blacklists,` | blacklist, a `list` of `data.table` or `data.frame` containing at least the following columns: "chr", "start", "end". Any event in a blacklists' region will be filtered out.
`blacklist_samples,` | character vector containing samples ID to filter out.
`blacklist_chrs,` | character vector containing chromosomes names in the package format, 1:22 for autosomes and 23 24 for chr X and Y.

### Details

This function can be used together with `summary` in order to clean the dataset from possible noise and unwanted calls. It is generally recommended to briefly explore the data using `summary` and then proceeding to filter out any unwanted group of events. Mandatory arguments of the function are "results" and "min_len"/"min_NP", default values are the authors suggested minimal filtering step, however its quite common to filter anything shorter than 10 or even 50 kb, and/or any call made by less than 10 points. The use of blacklist of any kind is optional and should be done with caution, as it can filter potential biologically relevant events. Over-segmented samples the user wishes to exclude can be specified via `blacklist_samples`. Immunoglobulin regions can be generated with the function `immuno_regions`, while telomeric and/or centromeric regions can be obtained with `telom_centrom`.

### Value

the `CNVresults` object `results` after the selected filters have been applied.

### Examples

    DT <- cleaning_filter(penn_22, min_len = 50000)

[Package CNVgears version 1.0.0 Index]