# Tools for the Differential Analysis of Proteins Abundance with R

## Documentation for package ‘DAPAR’ version 1.19.13

- DESCRIPTION file.
- User guides, package vignettes and other documentation.
- Package NEWS.

## Help Pages

A B C D E F G H I L M N P R S T U V W

## -- A --

addOriginOfValue | Sets the OriginOfValues dataframe
aggregateIter | xxxx
aggregateIterParallel | xxxx
aggregateMean | Compute the intensity of proteins as the mean of the intensities of their peptides.
aggregateSum | Compute the intensity of proteins with the sum of the intensities of their peptides.
aggregateTopn | Compute the intensity of proteins as the sum of the intensities of their n best peptides.

## -- B --

barplotEnrichGO_HC | A barplot that shows the result of a GO enrichment, using the package 'highcharter'
barplotGroupGO_HC | A barplot which shows the result of a GO classification, using the package 'highcharter'
boxPlotD | Builds a boxplot from a dataframe
boxPlotD_HC | Builds a boxplot from a dataframe using the library 'highcharter'
BuildAdjacencyMatrix | Function matrix of appartenance group
BuildColumnToProteinDataset | creates a column for the protein dataset after agregation by using the previous peptide dataset.
BuildColumnToProteinDataset_par | creates a column for the protein dataset after agregation by using the previous peptide dataset.
buildGraph | Display a CC

## -- C --

check.conditions | Check if the design is valid
check.design | Check if the design is valid
compareNormalizationD | Builds a plot from a dataframe
compareNormalizationDSubset | Builds a plot from a dataframe
compareNormalizationD_HC | Builds a plot from a dataframe. Same as compareNormalizationD but uses the library 'highcharter'
compute.group.t.tests | xxxxxx
compute.t.tests | xxxxxx
compute.t.tests2 | xxxxxx
corrMatrixD | Displays a correlation matrix of the quantitative data of the 'exprs()' table.
corrMatrixD_HC | Displays a correlation matrix of the quantitative data of the 'exprs()' table.
CountPep | Compute the number of peptides used to aggregate proteins
createMSnset | Creates an object of class 'MSnSet' from text file
CVDistD | Distribution of CV of entities
CVDistD_HC | Distribution of CV of entities

## -- D --

deleteLinesFromIndices | Delete the lines in the matrix of intensities and the metadata table given their indice.
densityPlotD | Builds a densityplot from a dataframe
densityPlotD_HC | Builds a densityplot from a dataframe
diffAnaComputeFDR | Computes the FDR corresponding to the p-values of the differential analysis using
diffAnaGetSignificant | Returns a MSnSet object with only proteins significant after differential analysis.
diffAnaSave | Returns a 'MSnSet' object with the results of the differential analysis performed with 'limma' package.
diffAnaVolcanoplot | Volcanoplot of the differential analysis
diffAnaVolcanoplot_rCharts | Volcanoplot of the differential analysis
display.CC.visNet | Display a CC

## -- E --

enrich_GO | Calculates GO enrichment classes for a given list of proteins/genes ID. It results an enrichResult instance.

## -- F --

finalizeAggregation | Finalizes the aggregation process
findMECBlock | Finds the LAPALA into a 'MSnSet' object
formatLimmaResult | xxxx
fudge2LRT | Heuristic to choose the value of the hyperparameter (fudge factor) used to regularize the variance estimator in the likelihood ratio statistic

## -- G --

get.pep.prot.cc | Build the list of connex composant of the adjacency matrix
GetDetailedNbPeptides | Computes the detailed number of peptides for each protein
GetDetailedNbPeptidesUsed | Computes the detailed number of peptides used for aggregating each protein
getIndicesConditions | Gets the conditions indices.
getIndicesOfLinesToRemove | Get the indices of the lines to delete, based on a prefix string
getListNbValuesInLines | Returns the possible number of values in lines in the data
GetNbPeptidesUsed | Computes the number of peptides used for aggregating each protein
getNumberOf | Number of lines with prefix
getNumberOfEmptyLines | Returns the number of empty lines in the data
getPourcentageOfMV | Percentage of missing values
getProcessingInfo | Returns the contains of the slot processing of an object of class 'MSnSet'
getProteinsStats | Computes the number of proteins that are only defined by specific peptides, shared peptides or a mixture of two.
getQuantile4Imp | Quantile imputation value definition
getTextForAggregation | Build the text information for the Aggregation process
getTextForAnaDiff | Build the text information for the Aggregation process
getTextForFiltering | Build the text information for the filtering process
getTextForGOAnalysis | Build the text information for the Aggregation process
getTextForHypothesisTest | Build the text information for the hypothesis test process
getTextForNewDataset | Build the text information for a new dataset
getTextForNormalization | Build the text information for the Normalization process
getTextForpeptideImputation | Build the text information for the peptide Imputation process
getTextForproteinImputation | Build the text information for the protein Imputation process
GOAnalysisSave | Returns an 'MSnSet' object with the results of the GO analysis performed with the functions 'enrichGO' and/or 'groupGO' of the 'clusterProfiler' package.
GraphPepProt | Function to create a histogram that shows the repartition of peptides w.r.t. the proteins
groupttest | xxxxxx
group_GO | Calculates the GO profile of a vector of genes/proteins at a given level of the Gene Ontology

## -- H --

hc_logFC_DensityPlot | Density plots of logFC values
hc_mvTypePlot2 | Distribution of Observed values with respect to intensity values
heatmap.DAPAR | This function is inspired from the function 'heatmap.2' that displays quantitative data in the 'exprs()' table of an object of class 'MSnSet'. For more information, please refer to the help of the heatmap.2 function.
heatmapD | This function is a wrapper to 'heatmap.2' that displays quantitative data in the 'exprs()' table of an object of class 'MSnSet'
histPValue_HC | Plots a histogram ov p-values

## -- I --

impute.detQuant | Deterministic imputation
impute.pa2 | Missing values imputation from a 'MSnSet' object
inner.aggregate.iter | xxxx
inner.aggregate.topn | xxxx
inner.mean | xxxx
inner.sum | xxxx
is.MV | Similar to the function 'is.na' but focused on the equality with the missing values in the dataset (type 'POV' and 'MEC')
is.OfType | Similar to the function 'is.na' but focused on the equality with the paramter 'type'.

## -- L --

LH0 | xxxxxx
LH0.lm | xxxxxx
LH1 | xxxxxx
LH1.lm | xxxxxx
limmaCompleteTest | Computes a hierarchical differential analysis
listSheets | This function returns the list of the sheets names in a Excel file.

## -- M --

make.contrast | Builds the contrast matrix
make.design | Builds the design matrix
make.design.1 | Builds the design matrix for designs of level 1
make.design.2 | Builds the design matrix for designs of level 2
make.design.3 | Builds the design matrix for designs of level 3
mvFilter | Filter lines in the matrix of intensities w.r.t. some criteria
mvFilterFromIndices | Filter lines in the matrix of intensities w.r.t. some criteria
mvFilterGetIndices | Filter lines in the matrix of intensities w.r.t. some criteria
mvHisto | Histogram of missing values
mvHisto_HC | Histogram of missing values
mvImage | Heatmap of missing values
mvPerLinesHisto | Bar plot of missing values per lines
mvPerLinesHistoPerCondition | Bar plot of missing values per lines and per condition
mvPerLinesHistoPerCondition_HC | Bar plot of missing values per lines and per condition
mvPerLinesHisto_HC | Bar plot of missing values per lines using highcharter
my_hc_chart | Customised resetZoomButton of highcharts plots
my_hc_ExportMenu | Customised contextual menu of highcharts plots

## -- N --

nonzero | Retrieve the indices of non-zero elements in sparse matrices
NumericalFiltering | Removes lines in the dataset based on numerical conditions.
NumericalgetIndicesOfLinesToRemove | Get the indices of the lines to delete, based on a prefix string

## -- P --

pepa.test | PEptide based Protein differential Abundance test
plotJitter | Jitter plot of CC
plotJitter_rCharts | Display a a jitter plot for CC
plotPCA_Eigen | Plots the eigen values of PCA
plotPCA_Eigen_hc | Plots the eigen values of PCA with the highcharts library
plotPCA_Ind | Plots individuals of PCA
plotPCA_Var | Plots variables of PCA
proportionConRev_HC | Barplot of proportion of contaminants and reverse

## -- R --

rbindMSnset | Similar to the function 'rbind' but applies on two subsets of the same 'MSnSet' object.
readExcel | This function reads a sheet of an Excel file and put the data into a data.frame.
reIntroduceMEC | Put back LAPALA into a 'MSnSet' object
removeLines | Removes lines in the dataset based on a prefix string.

## -- S --

samLRT | xxxxxx
saveParameters | Saves the parameters of a tool in the pipeline of Prostar
scatterplotEnrichGO_HC | A dotplot that shows the result of a GO enrichment, using the package 'highcharter'
setMEC | Sets the MEC tag in the OriginOfValues
splitAdjacencyMat | splits an adjacency matrix into specific and shared
StringBasedFiltering | Removes lines in the dataset based on a prefix strings (contaminants, reverse or both).
StringBasedFiltering2 | Removes lines in the dataset based on a prefix strings.

## -- T --

test.design | Check if xxxxxx
translatedRandomBeta | Generator of simulated values

## -- U --

univ_AnnotDbPkg | Returns the totality of ENTREZ ID (gene id) of an OrgDb annotation package. Careful : org.Pf.plasmo.db : no ENTREZID but ORF

## -- V --

violinPlotD | Builds a violinplot from a dataframe

## -- W --

wrapper.compareNormalizationD | Builds a plot from a dataframe
wrapper.compareNormalizationDSubset | Builds a plot from a dataframe
wrapper.compareNormalizationD_HC | Builds a plot from a dataframe
wrapper.corrMatrixD | Displays a correlation matrix of the quantitative data of the 'exprs()' table
wrapper.corrMatrixD_HC | Displays a correlation matrix of the quantitative data of the 'exprs()' table
wrapper.CVDistD | Distribution of CV of entities
wrapper.CVDistD_HC | Distribution of CV of entities
wrapper.dapar.impute.mi | Missing values imputation using the LSimpute algorithm.
wrapper.hc_mvTypePlot2 | Distribution of observed values with respect to intensity values from a 'MSnSet' object
wrapper.heatmapD | This function is a wrapper to 'heatmap.2' that displays quantitative data in the 'exprs()' table of an object of class 'MSnSet'
wrapper.impute.detQuant | Wrapper of the function 'impute.detQuant' for objects of class 'MSnSet'
wrapper.impute.fixedValue | Missing values imputation from a 'MSnSet' object
wrapper.impute.KNN | KNN missing values imputation from a 'MSnSet' object
wrapper.impute.mle | Imputation of peptides having no values in a biological condition.
wrapper.impute.pa | Imputation of peptides having no values in a biological condition.
wrapper.impute.pa2 | Missing values imputation from a 'MSnSet' object
wrapper.impute.slsa | Imputation of peptides having no values in a biological condition.
wrapper.mvHisto | Histogram of missing values from a 'MSnSet' object
wrapper.mvHisto_HC | Histogram of missing values from a 'MSnSet' object
wrapper.mvImage | Heatmap of missing values from a 'MSnSet' object
wrapper.mvPerLinesHisto | Histogram of missing values per lines from an object 'MSnSet'
wrapper.mvPerLinesHistoPerCondition | Bar plot of missing values per lines and per conditions from an object 'MSnSet'
wrapper.mvPerLinesHistoPerCondition_HC | Bar plot of missing values per lines and per conditions from an object 'MSnSet'
wrapper.mvPerLinesHisto_HC | Histogram of missing values per lines from an object using highcharter 'MSnSet'
wrapper.normalizeD | Normalisation
wrapper.pca | Compute the PCA
wrapper.t_test_Complete | xxxxx
wrapperCalibrationPlot | Performs a calibration plot on an 'MSnSet' object, calling the 'cp4p' package functions.
writeMSnsetToCSV | Exports a MSnset dataset into a zip archive containing three zipped CSV files.
writeMSnsetToExcel | This function exports a 'MSnSet' object to a Excel file.