DEXUSResult-class {dexus} | R Documentation

## Class `"DEXUSResult"`

### Description

This class contains the result of an RNA-Seq data analysis. The class contains the transcript names together with the parameters per condition, i.e., overdispersion and mean. Further it contains informative/non-informative values or p-values.

### Objects from the Class

Objects can be created by calls of the form `new("DEXUSResult", ...)`.

### Slots

`transcriptNames`

  The names of the transcripts, genes, exons, or regions of interest

`sampleNames`

  The sample names as they were given in the input matrix.

`inputData`

  The original read count matrix.

`normalizedData`

  The normalized read count matrix.

`sizeFactors`

  The size factors that were calculated for the normalization. This is that factor that scales each column or sample.

`INIValues`

  An informative/non-informative value for each sample that measures the evidence for differential expression.

`INIThreshold`

  The threshold for the I/NI values. Transcript with I/NI values above the threshold will be considered as differentially expressed.

`INICalls`

  A binary value for each transcript indicating whether it is differentially expressed.

`pvals`

  In case of two known conditions or multiple known conditions it is possible to calculate a p-value for each transcript. This value is given in this slot.

`responsibilities`

  A matrix of the size of the input matrix. It indicates the condition for each sample and transcript. The condition named "1" is the major condition. All other conditions are minor conditions. In case of supervised (two known conditions or multiple known conditions) analyses this clustering matrix will be the same for all transcripts.

`posteriorProbs`

  An array of the dimension of transcripts times samples times conditions. It gives the probability that a certain read count x was generated under a condition.

`logFC`

  The log foldchanges between the conditions. The reference is always condition "1".

`conditionSizes`

  The ratio of samples belonging to that condition. These are the α_i values of the model.

`sizeParameters`

  The size parameter estimates for each condition. These are the r_i values of the model.

`means`

  The mean of each condition. The μ_i values of the model.

`dispersions`

  The dispersion estimates for each condition. The inverse size parameters.

`params`

  The input parameters of the DEXUS algorithm.

### Methods

[

  Subsetting of a DEXUSResult.

as.data.frame

  Converts the result object into a data frame.

conditionSizes

  Returns the condition sizes or α_i parameters of the model.

dispersions

  Returns the dispersion, i.e. the inverse size parameters, of the model.

INI

  I/NI filtering of the result object.

INICalls

  Returns a logical value indication whether this transcript is differentially expressed or not.

INIThreshold

  Returns the thresholds for the I/NI values.

INIThreshold<-

  Sets the I/NI threshold. I/NI calls will be changed accordingly.

INIValues

  Returns the I/NI values.

inputData

  Returns the input read counts.

logFC

  Returns the log foldchange with respect to the first condition.

means

  Returns the mean per condition.

normalizedData

  Returns the normalized data.

params

  Returns a list of input parameters of DEXUS.

plot

  Plots a heatmap of the read counts of the top genes.

posteriorProbs

  Returns an array of posterior probabilities.

pvals

  Returns the p-values per transcript in supervised mode.

responsibilities

  Returns the clustering vector.

sampleNames

  Returns the sample names.

show

  Displays a data frame of results.

sizeFactors

  Returns the size factors used for normalization.

sizeParameters

  Returns the size parameters, i.e. the r_i values of the model.

sort

  Sorts the result object by I/NI values or p-values.

transcriptNames

  Returns the transcript names.

### Author(s)

Guenter Klambauer

### Examples

    showClass("DEXUSResult")

[Package dexus version 1.30.0 Index]