cv_filter: Pooled Coefficient of Variation (CV) Filter Object

In pmartR/pmartRqc: Panomics Marketplace - Quality Control and Statistical Analysis for Panomics Data

Pooled Coefficient of Variation (CV) Filter Object

Description

A pooled CV is calculated for each biomolecule.

Usage

cv_filter(omicsData, use_groups = TRUE)

Arguments

omicsData	an object of class 'pepData', 'proData', 'metabData', 'lipidData', or 'nmrData' created by as.pepData, as.proData, as.metabData, as.lipidData, or as.nmrData, respectively. Note, if group_designation has not been run, the CV is calculated based on all samples for each biomolecule.
use_groups	logical indicator for whether to utilize group information from group_designation when calculating the CV. Defaults to TRUE. If use_groups is set to TRUE but group_designation has not been run on the omicsData object, use_groups will be treated as FALSE.

Details

For each biomolecule, the CV of each group is calculated as the standard deviation divided by the mean, excluding missing values. A pooled CV estimate is then calculated based on the methods of Ahmed (1995). Any groups consisting of a single sample are excluded from the CV calculation, and thus, from the cv_filter result. If group_designation has not been run on the omicsData object, all samples are considered to belong to the same group.

Value

An S3 object of class 'cvFilt' giving the pooled CV for each biomolecule and additional information used for plotting a data.frame with a column giving the biomolecule name and a column giving the pooled CV value.

Author(s)

Lisa Bramer, Kelly Stratton

References

Ahmed, S.E. (1995). A pooling methodology for coefficient of variation. The Indian Journal of Statistics. 57: 57-75.

Examples

library(pmartRdata)
mypep <- group_designation(omicsData = pep_object, 
                           main_effects = "Phenotype")
to_filter <- cv_filter(omicsData = mypep, use_groups = TRUE)
summary(to_filter, cv_threshold = 30)

pmartR/pmartRqc documentation built on March 4, 2024, 3:46 p.m.