newINSPEcT {INSPEcT} | R Documentation

## Create a new INSPEcT object

### Description

The function newINSPEcT creates a new instance of the class INSPEcT provided the experimental time points, expression data (like RPKMs) of mature and eventually nascent RNA. For the nascent analysis, it is also requires a collecting time and the scaling factor to normalize the nascent RNA-seq libraries. This latter parameter can also be calculated by the function itself if both exonic and intronic expression data are provided; otherwise it must be given as an input and it is essential to guarantee the robustness of the analysis.

### Usage

    newINSPEcT(tpts, labeling_time = NULL, nascentExpressions = NULL,
      matureExpressions, preexisting = FALSE, BPPARAM = bpparam(),
      labeledSF = NULL, simulatedData = FALSE, degDuringPulse = FALSE,
      Dmin = 1e-06, Dmax = 10, genesFilter = TRUE)

### Arguments

`tpts` | A vector of time points, one for each sample
`labeling_time` | A number, lenght of the Nascent pulse
`nascentExpressions` | A list which contains exons and introns expression matrices and variances for the nascent RNA
`matureExpressions` | A list which contains exons and introns expression matrices and variances for the mature RNA
`preexisting` | A logical, indicating if the mature expression refers to the pre-exising (unlabeled) population. Not implemented yet for the "degDuringPulse" mode.
`BPPARAM` | Configuration for BiocParallel parallelization. By default is set to bpparam()
`labeledSF` | A vector storing user defined normalization scale over Nascent RNA exons and introns quantifications
`simulatedData` | A logical, set to TRUE in case the analysis is on simulated data
`degDuringPulse` | A logical, set to TRUE in case of a long labelling time. Also degradation of newly synthesized transcripts will be taken into account
`Dmin` | A numerical, it is the lower bound of the degradation rate domain for the prior optimization
`Dmax` | A numerical, it is the upper bound of the degradation rate domain for the prior optimization
`genesFilter` | A logical, if TRUE, filters out genes which have no signal in at least 2/3 of the observations

### Value

An object of class INSPEcT with a first estimation of the rates which can be accessed by the method `ratesFirstGuess`

### Examples

    data('allcounts', package='INSPEcT')
    data('featureWidths', package='INSPEcT')
    data('libsizes', package='INSPEcT')

    matureCounts<-allcounts$mature
    tpts <- c(0,1/6,1/3,1/2,1,1.5,2,4,8,12,16)
    expDes<-rep(tpts,3)

    matExp_DESeq2<-quantifyExpressionsFromTrCounts(
     	allcounts=matureCounts
     	,libsize=totalLS
     	,exonsWidths=exWdths
     	,intronsWidths=intWdths
     	,experimentalDesign=expDes)

    matureInspObj<-newINSPEcT(tpts=tpts
                             ,labeling_time=NULL
                             ,nascentExpressions=NULL
                             ,matureExpressions=matExp_DESeq2)

[Package INSPEcT version 1.12.2 Index]