proteomics: Statistical Analysis of High Throughput Proteomics Data

Provides methods for making inference in isobaric labelled LC-MS/MS experiments, i.e. iTRAQ experiments. It provides a function that reasonably parses a CSV-export from Proteome Discoverer(TM) into a data frame that can be easily handled in R. Functions and methods are provided for quality control, filtering, norming, and the calculation of response variables for further analysis. The merging of multiple iTRAQ experiments with respect to a reference is also covered.

AuthorThomas W. D. Möbius <>
Date of publication2014-11-22 01:30:39
MaintainerThomas W. D. Möbius <>

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Man pages

accum: Response calculation

addIonSatistics: Summary statistics - Ion intensities per spectra

addLoadings: Adjust for confounding - add an appropiate target

addRetentionAtApex: Summary statistics - Calculates retention time statistics at...

addRetentionIndexTimeStatistics: Summary statistics - Calculates index retention time...

adjustBy: Adjust for confounding - Generic function for centring data

adjusting: Adjust for confounding - State of the art adjustments for...

adjustOne: Adjust for confounding - In one single experiment only

avrgLoading: Adjust for confounding - calculates the average loading

channelResponses: Response calculation

copyLoadings: Adjust for confounding - copy loadings from one experiment to...

factoring: Sample design - Generating multiple factor designs from...

meetSelection: Data parsing - from Proteom Discover v1.4

mergeFrames: Merging multiple experiments

norm2Reference: Response calculation

pAction: Plotting p-value distributions

plotMePeptide: Plot interaction plots of peptides

plotMeProtein: Plot interaction plots of proteins

pRetention: Plot Retention Time Statistics

pVioline: Plot Retention Time Statistics in violine form

pVolcano: Volcano plot

responseStatisics: Summary statistics - Generic to calculate summary statistics

selectByConfidence: Result filtering - Test for biological effect

selectByEffect: Result filtering - Test for biological effect

selectByFDR: Result filtering

testForPeptideEffect: Data Analysis - Testing on peptide level

testForProteinEffect: Data Analysis - Testing on protein level

testing: Data Analysis - Testing features with Tukey Honest...

testingOneshot: Data Analysis - Testing one feature without Tukey Honest...

testingTukey: Data Analysis - Testing one feature with Tukey Honest...

toAlpha: Measuring stability - angle of loading vector

toProportions: Transformation - From intensity scales to density histrograms

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