fisherUMI4C {UMI4Cats} | R Documentation

## Differential UMI4C contacts using Fisher's Exact test

### Description

Using the UMIs inside `query_regions` performs Fisher's Exact test to calculate significant differences between contact intensities.

### Usage

    fisherUMI4C(
      umi4c,
      grouping = "condition",
      query_regions,
      resize = NULL,
      window_size = 5000,
      filter_low = 50,
      padj_method = "fdr",
      padj_threshold = 0.05
    )

### Arguments

`umi4c` | UMI4C object as generated by `makeUMI4C` or the `UMI4C` constructor.
`grouping` | Name of the column in colData used to merge the samples or replicates. If none available or want to add new groupings, run `addGrouping`. Default: "condition".
`query_regions` | `GenomicRanges` object or `data.frame` containing the region coordinates used to perform the differential analysis.
`resize` | Width in base pairs for resizing the `query_regions`. Default: no resizing.
`window_size` | If `query_regions` are not defined, wil bin region in `window_size` bp and perform the analysis using this windows.
`filter_low` | Either the minimum median UMIs requiered to perform Fisher's Exact test or `FALSE` for performing the test in all windows.
`padj_method` | Method for adjusting p-values. See `p.adjust` for the different methods.
`padj_threshold` | Numeric indicating the adjusted p-value threshold to use to define significant differential contacts.

### Details

This function calculates the overlap of fragment ends with either the provided `query_regions` or the binned region using `window_size`. The resulting number of UMIs in each `query_region` will be the sum of UMIs in all overlapping fragment ends. As a default, will filter out those regions whose median UMIs are lower than `filter_low`.

Finally, a contingency table for each `query_reegions` or `window` that passed the `filter_low` filter is created as follows:

| query_region | region
Reference | n1 | N1-n1
Condition | n2 | N2-n2

and the Fisher's Exact test is performed. Obtained p-values are then converted to adjusted p-values using `padj_method` and the results list is added to the `UMI4C` object.

### Value

Calculates statistical differences between UMI-4C experiments.

### Examples

    data("ex_ciita_umi4c")
    ex_ciita_umi4c <- addGrouping(ex_ciita_umi4c, grouping="condition")

    # Perform differential test
    enh <- GRanges(c("chr16:10925006-10928900", "chr16:11102721-11103700"))
    umi_dif <- fisherUMI4C(ex_ciita_umi4c, query_regions = enh,
                           filter_low = 20, resize = 5e3)
    resultsUMI4C(umi_dif)

[Package UMI4Cats version 1.0.1 Index]