createGeneModelFromRegulatoryRegions,Trena-method {trena} | R Documentation

## Create a model for a target gene using a Trena object

### Description

Create a model for a target gene using a Trena object

### Usage

    ## S4 method for signature 'Trena'
    createGeneModelFromRegulatoryRegions(
      obj,
      targetGene,
      solverNames,
      tbl.regulatoryRegions,
      mtx
    )

### Arguments

`obj` | An object of class Trena
`targetGene` | The name of a target gene to use for building a model
`solverNames` | A character vector containing the solver names to be used for building the model
`tbl.regulatoryRegions` | A data frame of regulatory regions, typically generated by using a filter
`mtx` | An assay matrix of expression data

### Value

A data frame containing the gene model

### Examples

    if(interactive()){  # takes too long for the bioconductor build
       # Create a Trena object for human and make a gene model for "MEF2C" using a footprint filter
       trena <- Trena("hg38")
       chromosome <- "chr5"
       mef2c.tss <- 88904257
       loc.start <- mef2c.tss - 1000
       loc.end   <- mef2c.tss + 1000

       database.filename <- system.file(package="trena", "extdata", "mef2c.neigborhood.hg38.footprints.db")
       database.uri <- sprintf("sqlite://%s", database.filename)
       sources <- c(database.uri)
       load(system.file(package="trena", "extdata/ampAD.154genes.mef2cTFs.278samples.RData"))

       motifs.list <- getRegulatoryChromosomalRegions(trena, chromosome, mef2c.tss-1000, mef2c.tss+1000,
       sources, "MEF2C", mef2c.tss)

       library(MotifDb)
       tbl.motifs.tfs <- associateTranscriptionFactors(MotifDb, motifs.list[[1]], source="MotifDb", expand.rows=TRUE)
       model.mef2c <- createGeneModelFromRegulatoryRegions(trena, "MEF2C", c("lasso","ridge","randomforest"),
                                                           tbl.motifs.tfs, mtx.sub)
       } # if interactive

[Package trena version 1.14.0 Index]