calculatePeaks: Count peaks

Description

calculatePeaks calculates the number of peaks in a sample.

Usage

calculatePeaks(data, bins = c(0, 2, 3), labels = c("No contamination",
  "Drop-in contamination", "Gross contamination"), nool = FALSE,
  permarker = FALSE, debug = FALSE)

Arguments

data

data frame containing at least the columns 'Sample.Name' and 'Height'.

labels

character vector defining the group labels (if any).

bins

numeric vector containing the maximum number of peaks required for a sample to get a specific label.

nool

logical if TRUE, off-ladder alleles 'OL' peaks will be discarded. if FALSE, all peaks will be included in the calculations.

permarker

logical if TRUE, peaks will counted per marker. if FALSE, peaks will counted per sample.

debug

logical indicating printing debug information.

Value

data.frame with with additional columns 'Peaks', 'Group', and 'Id'.

Details

Counts the number of peaks in a sample profile based on values in the 'Height' column. Each sample can be labelled according to custom labels defined by the number of peaks. Peaks can be counted per sample or per marker per sample. There is an option to discard off-ladder peaks ('OL'). The default purpose for this function is to categorize contamination in negative controls, but it can be used to simply calculating the number of peaks in any sample. NB! A column 'Peaks' for the number of peaks will be created. If present it will be overwritten. NB! A column 'Group' for the sample group will be created. If present it will be overwritten. NB! A column 'Id' will be created by combining the content in the 'Sample.Name' and 'File' column (if available). The unique entries in the 'Id' column will be the definition of a sample. If 'File' is present this allows for identical sample names in different batches (files) to be identified as different samples. If 'Id' is present it will be overwritten.