model.results.pairwise: Ouput of groupComparisonTMTPTM for full pairwise test

In devonjkohler/MSstatsTMTPTM: Post Translational Modification (PTM) Significance Analysis in shotgun mass spectrometry-based proteomic experiments with tandem mass tag (TMT) labeling

Description

Returns the a list with three dataframes for three statistical models. One for each Protein, PTM, and PTM adjusted for protein level.

Usage

model.results.pairwise

Format

A list of three dataframes

Details

• List objects: PTM.Model, Protein.Model, Adjusted.Model (all dataframe). Columns as follows:

• Protein : Protein ID

• Label: Label of the pairwise comparision or contrast

• log2FC: Log2 fold change

• SE: Standard error of the comparsion of contrast results

• DF: Degree of freedom

• pvalue: Value of p statistic of the test

• adj.pvalue: adjusted p value

• issue: used for indicating the reason why a comparison is not testable. NA means the comparison is testable. 'oneConditionMissing' means the protein has no measurements in one conndition of the comparison. Furtherone, when 'issue = oneConditionMissing', 'log2FC = Inf' means the negative condition (with coefficient -1 in the Label column) is missing and 'log2FC = -Inf' means the positive condition (with coefficient 1 in the Label column) is missing. completeMissing' means the protein has no measurements in all the connditions of the comparison. unfittableModel' means there is no enough measurements to fit the linear model. In other words, each condition has only one measurement.

Examples

names(model.results.pairwise)
head(model.results.pairwise[[1]])

devonjkohler/MSstatsTMTPTM documentation built on Oct. 27, 2021, 7:50 a.m.