The sparse nature of single cell epigenomics data can be overruled using probabilistic modelling methods such as Latent Dirichlet Allocation (LDA). This package allows the probabilistic modelling of cis-regulatory topics (cisTopics) from single cell epigenomics data, and includes functionalities to identify cell states based on the contribution of cisTopics and explore the nature and regulatory proteins driving them.
|Author||Carmen Bravo González-Blas|
|Bioconductor views||GenomicRanges rtracklayer|
|Maintainer||Carmen Bravo González-Blas <email@example.com>|
|Package repository||View on GitHub|
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