cisTopic: The cisTopic Class

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

The cisTopic Class

Description

The cisTopic object contains the initial data and the rest of the objects (e.g. models, distributions), created during the cisTopic workflow. cisTopic is ideally suited for single cell epigenomics experiments.

Details

Each cisTopic object contains several objects, which are listed below:

Slots

count.matrix

Matrix with the number of counts per region (rows) in each cell (columns). When dealing with single cell methylation data, we use beta values instead of counts.

binary.count.matrix

Matrix with regions as rows and cells as columns, where 1 represents an accessible region and 0 a non-accessible region. By default, a region is considered accessible if there is at least one count within the region.

is.acc

Counts threshold to determine if a region is accessible (0 by default)

models

List with all the LDA models trained. Each model is represented as an object of the class cisTopicModel. This slot will only be functional when the number of topics and the size of the data set allows it.

log.lik

Data frame containing the log likelihood of the models built.

selected.model

List with the information regards the model selected. The unnormalized cell assignments throughtout the sampling iterations are stored in [e-mail]$document_expects; while the corresponding unnormalized region assignments are stored in [e-mail]$topics.

dr

Dimensionality reduction outputs, which can be applied on 'cell' or 'region'. Within each slot ('cell' or 'regions'), there are sub-slots named by technique: 'Umap', 'tSNE', 'DiffussionMap', 'PCA', 'Biplot'.

calc.params

Named list to store all calculation-related parameter choices.

cell.names

Vector with the names of all the single cells (column names of the counts/accessibility matrix).

cell.data

Data frame that contains the meta-information about each cell, starting with number of counts detected in the defined regions (nCounts), and accessible regions (nAcc); more information is added using AddCellMetadata.

region.names

Vector with the position coordinates of all the regions (row names of the counts/accessibility matrix).

region.ranges

GRanges object with the regions coordinates.

region.data

Data frame that contains the meta-information about each region, starting with the region coordinates ('seqnames', 'start', 'end') and width (width), number of counts mapped to that region accross the data set (nCounts), number of cells in which the region is accessible (nCells); more information is added using AddRegionMetadata

binarized.cisTopics

List containing the regions that are considered as part of a cisTopic.

signatures

List containing regions belonging to given region signatures.

binarized.regions.to.Rct

List containing the RcisTarget regions that map to the top regions in each of the cisTopics.

binarized.RcisTarget

List containing objects of the class RcisTarget produced by running RcisTarget in the top binarized regions for each cisTopic.

binarized.rGREAT

List with rGREAT results when using the top binarized regions.

cistromes.ctx

List with cistromes based on ctx regions.

cistromes.regions

List with cistromes based on data regions.

cistromes.genes

List with cistromes based on data regions converted to genes.

project.name

Vector with the name of the project (for record keeping).

other

List to store any kind of related data (e.g. region lists).

version

Version of package used in object creation.

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