getCVreplicates: getCVreplicates

In BowenNCSU/xMSanalyzer: xMSanalyzer: R package for data analysis, comparison, and annotation of metabolomics data.

Description

Evaluate feature consistency based on coefficient of variation, where cv=sd/mean. Only calculate CV for samples for which a signal is detected in at least 60 If signal is detected in 60 which is calculated using non-missing replicates.

Usage

getCVreplicates(curdata, alignment.tool, numreplicates, min.samp.percent = 0.6, 
    impute.bool = TRUE, missingvalue)

Arguments

curdata	Feature alignment output matrix from apLCMS or XCMS with sample intensities
alignment.tool	Name of the feature alignment tool eg: "apLCMS" or "XCMS"
numreplicates	Number of replicates per sample
min.samp.percent	If signal is detected in x proportion of technical replicates, then the missing values are replaced by mean intensity which is calculated using non-missing replicates. eg: 0.7
impute.bool	Should the missingvalues be replaced by mean of the other replicates? eg: TRUE or FALSE
missingvalue	How are the missing values represented? eg: 0 or NA

Value

Matrix of feature consistency based on CV with columns: mz: m/z of the feature minCV: minimum CV between technical replicates across all samples first_quartileCV: 25th percentile CV medianCV: 50th percentile CV meanCV: average of cofficient of variations between technical replicates per sample across all samples third_quartileCV: 75th percentile CV maxCV: maximum CV between technical replicates across all samples

Author(s)

Karan Uppal <[e-mail]>

BowenNCSU/xMSanalyzer documentation built on May 24, 2019, 7:36 a.m.