anota2seqGetQualityControl: Retrieve the anota2seqPerformQC output from the...

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

Description

Retrieves the anota2seqPerformQC output from the Anota2seqDataSet

Usage

anota2seqGetQualityControl(object)

## S4 method for signature 'Anota2seqDataSet'
anota2seqGetQualityControl(object)

Arguments

object

An Anota2seqDataSet.

Value

The function outputs a list containing the following data:

• omniIntStats: A matrix with a summary of the statistics from the omnibus interaction analysis containing the following columns:

  • intMS: the mean square for the interaction;

  • intDf: the degrees of freedom for the interaction;

  • residMS: the residual error mean square;

  • residDf: the degrees of freedom for the residual error;

  • residMSRvm: the mean square for the residual error after applying RVM;

  • residDfRvm: the degrees of freedom for the residual error after applying RVM;

  • intRvmFval: the F-value for the RVM statistics;

  • intP: the p-value for the interaction;

  • intRvmP: the p-value for the interaction using RVM statistics;

  • intPAdj: the adjusted [for multiple testing using the selected multiple testing correction method] p-value of the interaction;

  • intRvmPAdj: the adjusted [for multiple testing using the selected multiple testing correction method] p-value of the interaction using RVM statistics).

• omniGroupStats: A matrix with a summary of the statistics from the omnibus treatment analysis containing the following columns:

  • groupSlope: the common slope used in APV;

  • groupSlopeP: if the slope is <0 or >1 a p-value for the slope being <0 or >1 is calculated; if the slope is >=0 & <=1 this value is set to 1;

  • groupMS: the mean square for treatments;

  • groupDf: the degrees of freedom for the treatments;

  • groupResidMS: the residual error mean square);

  • groupResidDf: the degrees of freedom for the residual error;

  • residMSRvm: the mean square for the residual error after applying RVM;

  • groupResidDfRvm: the degrees of freedom for the residual error after applying RVM;

  • groupRvmFval: the F-value for the RVM statistics;

  • groupP: the p-value for the sample class effect;

  • groupRvmP: the p-value for the sample class effect using RVM statistics;

  • groupPAdj: the adjusted [for multiple testing using the selected multiple testing correction method] p-value of the sample class effect);

  • groupRvmPAdj: the adjusted [for multiple testing using the selected multiple testing correction method] p-value of the sample class effect using RVM statistics).

• groupIntercepts A matrix with the group intercepts, i.e. the translational activity for each group independent of cytosolic mRNA level. Can be used for e.g. clustering of translational activity.

• correctionMethod: The multiple testing correction method used to adjust the nominal p-values.

• dsfSummary: A vector with the obtained frequencies of outlier dfbetas without the interaction term in the model.

• dfbetas: A matrix with the dfbetas from the model without the interaction term in the model.

• residuals: The residuals from the regressions without the interaction term in the model.

• fittedValues: A matrix with the fitted values from the regressions without the interaction term in the model.

• phenoClasses: The sample classes used in the analysis. The sample class order can be used to create the contrast matrix when using anota2seqRun or anota2seqAnalyze.

• sampleNames: A vector with the sample names (from the translated mRNA [e.g. polysome-associated mRNA or RPF] samples).

• abParametersInt: The ab parameters for the inverse gamma fit for the interactions within RVM.

• abParametersGroup: The ab parameters for the inverse gamma fit for treatments within RVM.

See Also

See Also as anota2seqPerformQC

Examples

data(anota2seq_data)
#Initialize Anota2seqDataSet
Anota2seqDataSet <- anota2seqDataSetFromMatrix(
    dataP = anota2seq_data_P[1:100,],
    dataT = anota2seq_data_T[1:100,],
    phenoVec = anota2seq_pheno_vec,
    dataType = "RNAseq",
    normalize = TRUE)
#Run QC
Anota2seqDataSet <- anota2seqPerformQC(Anota2seqDataSet)

#Get QC
qc <- anota2seqGetQualityControl(Anota2seqDataSet)

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