UMI4Cats | R Documentation |
The UMI4Cats package provides functions for the pre-processing, analysis and visualization of UMI-4C chromatin contact data.
There are two different functions that can be used to prepare the files for analyzing them with UMI4Cats:
demultiplexFastq
. Demultiplex reads belonging to
different viewpoints from a paired-end FastQ file.
digestGenome
. Digest the reference genome of choice
using a given restriction sequence.
The pre-processing functions are wrapped in the contactsUMI4C
main function. This function will sequentially run the following steps:
prepUMI4C
. Filter specific and high quality reads.
splitUMI4C
. Split reads by the restriction sequence.
alignmentUMI4C
. Align reads to the reference genome.
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
.
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
.
An integrative plot showing the results stored inside the UMI4C
object can be generated with the function plotUMI4C
.
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