anota2seqSelSigGenes: Select identifiers from the output of 'anota2seqAnalyze'.

In anota2seq: Generally applicable transcriptome-wide analysis of translational efficiency using anota2seq

Description

This function filters the output based on significance threshold, effect sizes (of total mRNA, translated mRNA, translation, buffering), identifier names and/or APV regression slopes.

Usage

anota2seqSelSigGenes(Anota2seqDataSet, useRVM = TRUE,
  analysis = anota2seqGetAvailableAnalyzes(Anota2seqDataSet),
  selIds = NULL, selContrast = seq(along =
  1:dim(anota2seqGetContrasts(Anota2seqDataSet))[2]),
  minSlopeTranslation = NULL, maxSlopeTranslation = NULL,
  minSlopeBuffering = NULL, maxSlopeBuffering = NULL, slopeP = NULL,
  minEff = NULL, maxP = NULL, maxPAdj = NULL, selDeltaPT = NULL,
  selDeltaTP = NULL, selDeltaP = NULL, selDeltaT = NULL,
  sortBy = c("rvmP", "none", "Eff", "p"))

Arguments

Anota2seqDataSet	An Anota2seqDataSet containing the output from the anota2seqAnalyze function performed on the analysis to be filtered by anota2seqSelSigGenes.
useRVM	If a significance threshold is provided (maxP or maxPAdj, see below), should the output be filtered on Random Variance Model p-values or on non-RVM p-values? Default is TRUE i.e. RVM p-values.
analysis	A vector of character string(s) specifying which analysis(es) should be considered for filtering. Should be at least one of the following: "translated mRNA", "total mRNA", "translation" or "buffering". By default, filtering will be performed on all available analyzes in the Anota2seqDataSet object.
selIds	The function can consider only a subset of the identifiers from the input data set. For custom selection of identifiers, supply a vector of identifiers (row names from the original data set) to be included. Default is NULL i.e. filtering is performed on all identifiers.
selContrast	Which contrast(s) should be evaluated during the filtering and sorting? Descriptions of the contrasts can be found in the output from the anota2seqAnalyze object in the usedContrasts slot. Indicate the contrast(s) by a numeric vector of the column number(s). By default, all available contrasts in the Anota2seqDataSet object are filtered.
minSlopeTranslation	The output can be filtered so that identifiers whose identified slopes in analysis of changes in translational efficiency leading to altered protein levels are too small can be excluded. Default is NULL i.e. no filtering based on lower boundary of the slope. To exclude identifiers with e.g. a slope <(-1), assign -1 to minSlopeTranslation. Only applied when analysis is set to "translation".
maxSlopeTranslation	The output can be filtered so that identifiers whose identified slopes in analysis of changes in translational efficiency leading to altered protein levels are too large can be excluded. Default is NULL i.e. no filtering based on upper boundary of the slope. To exclude identifiers with e.g. a slope >2, assign 2 to maxSlopeTranslation. Only applied when analysis is set to "translation".
minSlopeBuffering	The output can be filtered so that identifiers whose identified slopes in analysis of changes in translational efficiency leading to buffering are too small can be excluded. Default is NULL i.e. no filtering based on lower boundary of the slope. To exclude identifiers with e.g. a slope <(-2), assign -2 to minSlopeBuffering Only applied when analysis is set to "buffering".
maxSlopeBuffering	The output can be filtered so that genes whose identified slopes in analysis of changes in translational efficiency leading to buffering are too large can be excluded. Default is NULL i.e. no filtering based on upper boundary of the slope. To exclude identifiers with e.g. a slope > 1, assign 1 to maxSlopeBuffering. Only applied when analysis is set to "buffering".
slopeP	A p-value for the slope being <0 or >1 if the estimate for the slope is <0 or >1 (for translation) and <-1 or >0 if the estimate for the slope is <-1 or >0 (for buffering). This p-value can be used to filter the output based on unrealistic slopes. When set low, fewer identifiers will be disqualified. Default is NULL i.e. no filtering based on slope p-value. Only applied for when analysis is set to "translation" or "buffering".
minEff	The output can be filtered based on minimum effect for inclusion. The value is applied both to negative and positive effects: e.g. a value of 1 will evaluate if the effects are >1 OR <(-1). Default is NULL i.e. no filtering based on effect.
maxP	The output can be filtered based on raw p-values from the anota2seq analysis (i.e. smaller compared to assigned value). If useRVM is set to TRUE, filtering will be performed on RVM values, otherwise filtering will be performed on non-RVM values. Default is NULL i.e. no filtering.
maxPAdj	The output can be filtered based on adjusted p-values from the anota2seq analysis (i.e. smaller compared to assigned value). If useRVM is set to TRUE, filtering will be performed on RVM values, otherwise filtering will be performed on non-RVM values. The adjustment method that was used when running anota2seqAnalyze will be evaluated. Default is NULL i.e. no filtering.
selDeltaPT	The output can be filtered based on the mean log2(translation data (e.g. polysome-associated mRNA) / total mRNA data) between treatments difference. The treatments are defined by the selected contrast. Default is NULL i.e. no filtering. Only applied when analysis is set to "translation".
selDeltaTP	The output can be filtered based on the mean log2(total mRNA / translation data (e.g. polysome-associated mRNA)) between treatments difference. The treatments are defined by the selected contrast. Default is NULL i.e. no filtering. Only applied when analysis is set to "buffering".
selDeltaP	The output for analysis changes in translational efficiency leading to altered protein levels can be filtered based on the translation data only so that the minimum absolute difference between treatments for translated mRNA data (e.g. polysome-associated mRNA) is used for inclusion. The treatments are defined by the selected contrast. Default is NULL i.e. no filtering. Use when analysis parameter is set to "translation" (i.e. changes in translational efficiency leading to altered protein levels) or "translated mRNA".
selDeltaT	The output for analysis of changes in translational efficiency leading to buffering can be filtered based on the total mRNA data only so that the minimum absolute difference between treatments for buffering is used for inclusion. The treatments are defined by the selected contrast. Default is NULL i.e. no filtering. Use when analysis parameter is set to "buffering" or "total mRNA".
sortBy	The output can be sorted by effect ("Eff"), raw p-value ("p"), raw RVM p-value ("rvmP") or not sorted ("none"). Default is "rvmP" when useRVM is set to TRUE and "p" when useRVM is set to FALSE.

Value

An Anota2seqDataSet. anota2seqSelSigGenes saves its output data in the 'selectedTranslatedmRNA', 'selectedTotalmRNA', 'selectedTranslation' and 'selectedBuffering' slots of the Anota2seqDataSet when analysis is set to "translated mRNA", "total mRNA", "translation" and "buffering" respectively. This output contains statistics from the applied APV model on selected genes, see anota2seqGetOutput for a detailed description.

See Also

anota2seqAnalyze, anota2seqGetOutput

Examples

data(anota2seq_data)
# Initialize the Anota2seqDataSet
Anota2seqDataSet <- anota2seqDataSetFromMatrix(
    dataP = anota2seq_data_P[1:100,],
    dataT = anota2seq_data_T[1:100,],
    phenoVec = anota2seq_pheno_vec,
    dataType = "RNAseq",
    normalize = TRUE)
# Run analysis of changes in translational efficiency leading to 
# altered protein levels
Anota2seqDataSet <- anota2seqAnalyze(
    Anota2seqDataSet,
    analysis = c("translation"))
# Select significant genes (with a FDR threshold of 0.15) for changes 
# in translational efficiency leading to altered protein level
Anota2seqDataSet <- anota2seqSelSigGenes(Anota2seqDataSet,
                                         maxPAdj = .15) 

anota2seq documentation built on Nov. 8, 2020, 6 p.m.