anota2seqGetQualityControl {anota2seq} | R Documentation

## Retrieve the anota2seqPerformQC output from the Anota2seqDataSet

### 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)

[Package anota2seq version 1.0.1 Index]