createTADdata {preciseTAD} | R Documentation

## Function to create a data matrix used for building a predictive model to classify boundary regions from functional genomic elements

### Description

Function to create a data matrix used for building a predictive model to classify boundary regions from functional genomic elements

### Usage

    createTADdata(
      bounds.GR,
      resolution,
      genomicElements.GR,
      featureType = "distance",
      resampling,
      trainCHR,
      predictCHR = NULL
    )

### Arguments

`bounds.GR` | a GRanges object with chromosomal coordinates of TAD boundaries used to identify positive cases (can be obtained using `extractBoundaries`). Required.
`resolution` | Numeric, the width to bin the genome at, should match the resolution that TADs were called at. Required.
`genomicElements.GR` | a GRangesList object containing GRanges objects for each ChIP-seq data to leverage in the random forest model (can be obtained using the `bedToGRangesList`). Required.
`featureType` | Character, controls how the feature space is constructed (one of either "binary" (overlap yes/no), "oc" (overlap counts, the number of overlaps), "op" (overlap percent, the percent of bin width covered by the genomic annotation), or "distance" (log2-transformed distance from the center of the nearest genomic annotation to the center of the bin); default is "distance"). Required.
`resampling` | Character, controls if and how the data should be resampled to create balanced classes of boundary vs. nonboundary regions (one of either "none" - no re-sampling, "ros" - Random Over-Sampling, "rus" - Random Under-Sampling. Required.
`trainCHR` | Character vector of chromosomes to use to build the binned data matrix for training. Required.
`predictCHR` | Character vector of chromosomes to use to build the binned data matrix for testing. Default in NULL, indicating no test data is created. If trainCHR=predictCHR then a 7:3 split is created.

### Value

A list object containing two data.frames: 1) the training data, 2) the test data (only if predictCHR is not NULL, otherwise it is NA). "y" is an indicator whether the corresponding bin is a TAD boundary, and the subsequent columns have the association measures between bins and the genomic annotations

### Examples

    # Create training data for CHR21 and testing data for CHR22 with
    # 5 kb binning, oc-type predictors from 26 different transcription factor
    # binding sites from the GM12878 cell line, and random under-sampling

    # Read in ARROWHEAD-called TADs at 5kb
    data(arrowhead_gm12878_5kb)

    #Extract unique boundaries
    bounds.GR <- extractBoundaries(domains.mat = arrowhead_gm12878_5kb,
                                   preprocess = FALSE,
                                   CHR = c("CHR21", "CHR22"),
                                   resolution = 5000)

    # Read in GRangesList of 26 TFBS
    data(tfbsList)

    tadData <- createTADdata(bounds.GR = bounds.GR,
                             resolution = 5000,
                             genomicElements.GR = tfbsList,
                             featureType = "oc",
                             resampling = "rus",
                             trainCHR = "CHR21",
                             predictCHR = "CHR22")

[Package preciseTAD version 1.2.0 Index]