checkNo.replicates: A function to detect disparity in the number of replicates...

In clippda: A package for the clinical proteomic profiling data analysis

Description

Sometimes in a mass spectrometry experiment, it happens that a few samples have been mislabelled. Mislabelling means that some replicates are in the wrong sample group, and this results in some samples having more (or less) replicates than the number intended by the experimentalist. Apart from disparity in the number of replicates due to mislabelling, a few samples, e.g. the quality control (QC) samples, are often assayed several times. The aim is to analyze data with the same number of technical replicates (in this case, duplicates) for every sample. The function checkNo.replicates identifies samples with a disparate number of replicates. The identified samples are treated as follows:

(i) The QC samples can be independently analysed to ascertain the reproducibility of the data.

(ii) The samples with no replicates are discarded from further analysis.

(iii) The samples with more replicates than expected, due to mislabelling (or otherwise), are pre-processed using the function: mostSimilarTwo which detects and discards replicates which give conflicting peak information compared to the rest of the replicates. Here, the two most similar replicates are treated as the correct replicates for the sample in question.

Usage

checkNo.replicates(rawData, no.peaks, no.replicates)

Arguments

rawData	Duplicate data in the same format as the raw data from the Biomarker wizard software.
no.peaks	The number of peaks detected by the Biomarker wizard
no.replicates	The number of replicates intended by the biologist.

Value

It returns a vector whose elements are labels for samples with a disparate number peaks.

Author(s)

Stephen Nyangoma

Examples

data(liverRawData)

rawData <- liverRawData

no.peaks <- 53

no.replicates <- 2

checkNo.replicates(rawData,no.peaks,no.replicates) 

clippda documentation built on Nov. 8, 2020, 8:13 p.m.