UMI4Cats {UMI4Cats} | R Documentation

## UMI4Cats: A package for analyzing UMI-4C chromatin contact data

### Description

The UMI4Cats package provides functions for the pre-processing, analysis and visualization of UMI-4C chromatin contact data.

### File preparation

There are two different functions that can be used to prepare the files for analyzing them with UMI4Cats:

1. `demultiplexFastq`. Demultiplex reads belonging to different viewpoints from a paired-end FastQ file.

2. `digestGenome`. Digest the reference genome of choice using a given restriction sequence.

### Processing

The pre-processing functions are wrapped in the `contactsUMI4C` main function. This function will sequentially run the following steps:

1. `prepUMI4C`. Filter specific and high quality reads.

2. `splitUMI4C`. Split reads by the restriction sequence.

3. `alignmentUMI4C`. Align reads to the reference genome.

4. `counterUMI4C`. Apply UMI counting algorithm to quantify the interactions with the viewpoint.

The statistics from the samples analyzed with the `contactsUMI4C` function can be extracted and visualized with the function `statsUMI4C`.

### Analysis

The analysis of UMI-4C data is wrapped in the construction of an object of UMI4C class by the creator function `makeUMI4C`. This function will group your samples according to the variable you provided in the `grouping` argument (default: "condition") and then normalize it to `ref_umi4c`.

Significant interactions with the viewpoint can be called when several replicates are available, using the `callInteractions` function. A set of `query_regions`, such as enhancers or open chromatin regions needs to be provided. When no candidate regions are available, one can use the function `makeWindowFragments` to join a fixed number of restriction fragments into windows. The results of this analysis can be visualized using `plotInteractionsUMI4C` and the list of significant interactions can be retrieved using `getSignInteractions`.

The differential analysis can be performed with `fisherUMI4C` or `waldUMI4C` functions and can be focused in a set of regions of interest by providing the `query_regions` argument. Both will return a UMI4C object containing the results of the differential test. You can access these results with the method `resultsUMI4C`.

### Visualization

An integrative plot showing the results stored inside the UMI4C object can be generated with the function `plotUMI4C`.

[Package UMI4Cats version 1.4.0 Index]