Package index • DaparToolshed

All functions

Add_Item_to_Dataset(): xxx
BuildAdjacencyMatrix(): Function matrix of appartenance group
BuildMetacell(): Metacell function
Children(): Names of all chidren of a node
CleanRowData(): Customised resetZoomButton of highcharts plots
ConvertListToHtml(): Convert a list to unnumbered HTML list
aggregateFeatures4Prostar() aggQmetacell() aggregateMethods() RunAggregation() BuildColumnToProteinDataset() Add_Aggregated_rowData() metacell_agg() select_topn() getProteinsStats() CountPep() GetNbPeptidesUsed() GetDetailedNbPeptidesUsed() GetDetailedNbPeptides() GraphPepProt() ExtractUniquePeptides() inner.aggregate.iter() inner.sum() inner.mean() inner.median() inner.medianpolish() inner.robustsummary(): Aggregate an assay's quantitative features
aggregateRedistribution(): Aggregate an assay's quantitative features with shared peptide redistribution
ExtendPalette(): Extends a base-palette of the package RColorBrewer to n colors.
GetColorsForConditions(): Builds a complete color palette for the conditions given in argument
GetIndices_BasedOnConditions(): Search lines which respects request on one or more conditions.
GetIndices_FunFiltering(): Delete the lines in the matrix of intensities and the metadata table given their indices.
GetIndices_WholeLine(): Search lines which respects query on all their elements.
GetIndices_WholeMatrix(): Search lines which respects request on one or more conditions.
GetNbTags(): Number of each metacell tags
GetSoftAvailables(): The set of available softwares to convert from
Keep_Items_from_Dataset(): xxx
LH0(): xxxxxx
LH0.lm(): xxxxxx
LH1(): xxxxxx
LH1.lm(): xxxxxx
MetacellFilteringScope(): Lists the metacell scopes for filtering
Metacell_DIA_NN(): Sets the metacell dataframe for datasets which are from Dia-NN software
Metacell_maxquant(): Sets the metacell dataframe
Metacell_proline(): Sets the metacell dataframe for datasets which are from Proline software
NAIsZero(): xxx
OWAnova(): Applies aov() on a vector of protein abundances using the design derived from the sample names (simple aov wrapper)
Parent(): Parent name of a node
Pipelines(): xxx
ProstarVersions(): Version number of Prostar suite
paramshistory() `paramshistory<-`() GetMetacellTags() qMetacell() `qMetacell<-`() GetUniqueTags() .GetMetadataSlot() .GetRowdataSlot() ConnectedComp() `ConnectedComp<-`() typeDataset() `typeDataset<-`() idcol() `idcol<-`() parentProtId() `parentProtId<-`() filename() `filename<-`() analysis() `analysis<-`() version() `version<-`() design.qf() `design.qf<-`() mainAssay() HypothesisTest() `HypothesisTest<-`() DifferentialAnalysis() `DifferentialAnalysis<-`() names_metacell() `names_metacell<-`(): List of metacell tags
write2excel() .write2excel() addColors(): Exports a QFeatures object to a Excel file.
FunctionFilter() filterFeaturesOneSE(): Filter features of one SE based on their rowData
last_assay() n_assays_in_qf() QFeaturesFromSE(): Utility funcitons to dela with QFeatures objects.
ReplaceSpecialChars(): Standardize names
AdjMatFilters() allPeptides() specPeptides() subAdjMat_specificPeptides() sharedPeptides() subAdjMat_sharedPeptides() topnFunctions() topnPeptides() subAdjMat_topnPeptides(): Filter a peptide assay on the basis of its adjacency matrix.
applyAnovasOnProteins(): iteratively applies OWAnova() on the features of an MSnSet object
buildGraph(): Display a CC
check.conditions(): Check if the design is valid
check.design(): Check if the design is valid
classic1wayAnova(): Function to perform a One-way Anova statistical test on a MsnBase dataset
plotCompareAssays(): Compare two assays
compareNormalizationD_HC(): Builds a plot from a dataframe. Same as compareNormalizationD but uses the library highcharter
compute_t_tests(): xxxxxx
customChart(): Customised resetZoom Button of highcharts plots
diffAnaComputeAdjustedPValues(): Computes the adjusted p-values
diffAnaComputeFDR(): Computes the FDR corresponding to the p-values of the differential analysis
diffAnaVolcanoplot_rCharts(): Volcanoplot of the differential analysis
display.CC.visNet(): Display a CC
formatHSDResults(): xxx
formatLimmaResult(): xxxx
formatPHResults(): Extract logFC and raw pvalues from multiple post-hoc models summaries
formatPHTResults(): xxx
fudge2LRT(): Heuristic to choose the value of the hyperparameter (fudge factor) used to regularize the variance estimator in the likelihood ratio statistic
get.pep.prot.cc(): Build the list of connex composant of the adjacency matrix
getDesignLevel(): xxx
getListNbValuesInLines(): Returns the possible number of values in lines in the data
getNumberOfEmptyLines(): Returns the number of empty lines in the data
globalAdjPval(): Computes the adjusted p-values on all the stacked contrasts using CP4P
hc_logFC_DensityPlot(): Density plots of logFC values
heatmapForMissingValues(): xxx
histPValue_HC(): Plots a histogram of p-values
createQFeatures(): Creates an object of class QFeatures from text file.
impute.pa2(): Missing values imputation from a MSnSet object
is.OfType(): Similar to the function is.na() but focused on the equality with the paramter 'type'.
is.differential(): Identification of differentially abundant peptide/protein
is.subset(): xxx
limmaCompleteTest(): Computes a hierarchical differential analysis
make.contrast(): Builds the contrast 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
make.design(): Builds the design matrix
match.metacell(): Similar to the function is.na() but focused on the equality with the paramter 'type'.
metacellPerLinesHisto_HC() metacellPerLinesHistoPerCondition_HC() metacellHisto_HC() wrapper.mvImage() mvImage() hc_mvTypePlot2(): Bar plot of missing values per lines using highcharter
findMECBlock() reIntroduceMEC() wrapper.impute.KNN() wrapper.impute.fixedValue() wrapper.impute.pa() wrapper.impute.detQuant() getQuantile4Imp() wrapper.impute.slsa(): Finds the LAPALA
my_hc_ExportMenu(): Customised contextual menu of highcharts plots
my_hc_chart(): Customised resetZoomButton of highcharts plots
nEmptyLines(): Number of empty lines in the data
nonzero(): Retrieve the indices of non-zero elements in sparse matrices
normalizeMethods() GlobalQuantileAlignment() SumByColumns() QuantileCentering() MeanCentering() vsn() LOESS(): Normalisation
normalizeFunction(): Normalisation for QFeatures
readExcel() listSheets() write_Assay_To_Excel() WriteHistory() Write_SamplesData_to_Excel() Write_RowData() write.excel(): This function exports a data.frame to a Excel file.
pepa.test(): PEptide based Protein differential Abundance test
pkgs.require(): Loads packages
plotJitter(): Jitter plot of CC
plotJitter_rCharts(): Display a a jitter plot for CC
postHocTest(): Post-hoc tests for classic 1-way ANOVA
pushpvalue(): Push p-values based on metacell tags
SymFilteringOperators() qMetacellFilteringScope() qMetacellWholeMatrix() qMetacellWholeLine() qMetacellOnConditions(): Search lines which respects request on one or more conditions.
metacell.def() custom_metacell_colors() Set_POV_MEC_tags() Set_POV_MEC_tags2() Metacell_generic() UpdateMetacellAfterImputation() search.metacell.tags() metacombine(): Quantitative metadata vocabulary for entities
samLRT(): xxxxxx
separateAdjPval(): Computes the adjusted p-values separately on contrast using CP4P
splitAdjacencyMat(): splits an adjacency matrix into specific and shared
subR25pept: subR25pept dataset
subR25prot: subR25prot dataset
test.design(): Check if xxxxxx
testAnovaModels(): Applies a statistical test on each element of a list of linear models
thresholdpval4fdr(): xxx
translatedRandomBeta(): Generator of simulated values
wrapper.dapar.impute.mi(): Missing values imputation using the LSimpute algorithm.
wrapper.impute.mle(): Imputation of peptides having no values in a biological condition.
wrapper.impute.pa2(): Missing values imputation from a SummarizedExperiment object
wrapper.pirat(): Missing values imputation using Pirat
wrapperCalibrationPlot(): Performs a calibration plot on an SummarizedExperiment object, calling the cp4p package functions.
wrapperClassic1wayAnova(): Wrapper for One-way Anova statistical test