predictiveDistribution: Probability of each region in each cell in the data set.

In aertslab/cisTopic: cisTopic: Probabilistic modelling of cis-regulatory topics from single cell epigenomics data

Probability of each region in each cell in the data set.

Description

Calculates the probability of each region in each cell.

Usage

predictiveDistribution(object, big.matrix = FALSE, ...)

Arguments

object	Initialized cisTopic object.
big.matrix	If having big data, we recommend to use the bigmemory package for the calculations.
...	Ignored.

Value

Returns a matrix where the rows are the regions, the columns the cells, and the values are the probabilities of seeing a region in a matrix.

Examples

bamfiles <- c('example_1.bam', 'example_2.bam', 'example_3.bam')
regions <- 'example.bed'
cisTopicObject <- createcisTopicObjectfromBAM(bamfiles, regions)
cisTopicObject <- runModels(cisTopicObject)
cisTopicObject <- selectModel(cisTopicObject)
cisTopicObject <- predictiveDistribution(cisTopicObject)

aertslab/cisTopic documentation built on April 6, 2024, 9:31 p.m.