TimeCompare {TADCompare} | R Documentation

## Time-varying TAD boundary analysis

### Description

Time-varying TAD boundary analysis

### Usage

    TimeCompare(
      cont_mats,
      resolution,
      z_thresh = 2,
      window_size = 15,
      gap_thresh = 0.2,
      groupings = NULL
    )

### Arguments

`cont_mats` | List of contact matrices in either sparse 3 column, n x n or n x (n+3) form where the first three columns are coordinates in BED format. See "Input_Data" vignette for more information. If an n x n matrix is used, the column names must correspond to the start point of the corresponding bin. Required.
`resolution` | Resolution of the data. Used to assign TAD boundaries to genomic regions. If not provided, resolution will be estimated from column names of the first matrix. Default is "auto".
`z_thresh` | Threshold for boundary score. Higher values result in a more stringent detection of differential TADs. Default is 3.
`window_size` | Size of sliding window for TAD detection, measured in bins. Results should be consistent. Default is 15.
`gap_thresh` | Required % of non-zero entries before a region will be considered non-informative and excluded. Default is .2
`groupings` | Variable for defining groups of replicates at a given time point. Each group will be combined using consensus boundary scores. It should be a vector of equal length to cont_mats where each entry is a label corresponding to the group membership of the corresponding matrix. Default is NULL, implying one matrix per time point.

### Details

Given a list of sparse 3 column, n x n, or n x (n+3) contact matrices representing different time points, TimeCompare identifies all TAD boundaries. Each TAD boundary is classified into six categories (Common, Dynamic, Early/Late Appearing and Early/Late Disappearing), based on how it changes over time.

### Value

A list containing consensus TAD boundaries and overall scores

- TAD_Bounds - Data frame containing all regions with a TAD boundary at one or more time point. Coordinate corresponds to genomic region, sample columns correspond to individual boundary scores for each sample, Consensus_Score is the consensus boundary score across all samples. Category is the differential boundary type.

- All_Bounds - Data frame containing consensus scores for all regions

- Count_Plot - Plot containing the prevelance of each boundary type

### Examples

    # Read in data
    data("time_mats")
    # Find time varying TAD boundaries
    diff_list <- TimeCompare(time_mats, resolution = 50000)

[Package TADCompare version 1.2.0 Index]