filter_bins: Filtering bins according to user-defined thresholds
In malemay/delgbs: Detection of deletions and duplications from GBS data

filter_bins

R Documentation

Filtering bins according to user-defined thresholds

Description

This function takes a data.frame of normalized read counts per sample and per bin and removes the bins considered uninformative for the purposes of CNV calling according to three different criteria: the minimum mean number of reads, the maximum mean number of reads, and the ratio of the variance in the number of reads per sample to the mean number of reads per sample ( overdispersion filter)

Usage

filter_bins(read_counts, max_reads, min_reads, odisp_filter)

Arguments

`read_counts`	a `data.frame` of read counts as generated from function `link{read_counts}`.
`max_reads`	a single numeric value. The maximum mean number of reads per individual that a bin can have to be kept for further processing.
`min_reads`	a single numeric value. The minimum mean number of reads per individual that a bin must have to be kept for further processing.
`odisp_filter`	a single numeric value. The maximum ratio of the variance of the number of reads per individual in a bin to the mean number of reads per individual in this bin. The purpose of this filter is to remove bins that display overdispersion. A value of 3 has commonly been used for this filter.