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# spatzie: Identification of enriched motif pairs from chromatin interaction data [![license: GPL-3](]( [![DOI](]( [![BioC](]( [![platforms](]( [![Coverage Status](]( Given a database of DNA sequence motifs representing transcription factors and enhancer promoter interaction data, spatzie performs statistical analysis to identify co-enriched transcription factors. ## Installation The *spatzie* package is part of Bioconductor since release 3.14. To install it on your system, enter: ``` if (!requireNamespace("BiocManager", quietly = TRUE)) { install.packages("BiocManager") } BiocManager::install("spatzie") ``` Alternatively, the latest version can be installed directly from this repository: ``` if (!requireNamespace("remotes", quietly = TRUE)) { install.packages("remotes") } remotes::install_github("jhammelman/spatzie", build_vignettes = TRUE) ``` Note: For most use cases it is not necessary to install the *spatzie* package locally, as a substantial part of its functionality is offered as an online service at ## Usage For interaction data aligned to the most recent human or mouse genome assemblies (`hg38`, `hg19`, `mm10`, or `mm9`), the most common spatzie use cases are covered by the function `find_ep_coenrichment`, which is prominently featured in one of the vignettes: ``` vignette("single-call", package = "spatzie") ``` The functionality displayed in the vignette above is also available online at []( If more flexibility is required, e.g., different genome assemblies, locally cached promoter annotations, non-standard ways to filter interactions, this vignette is a good starting point: ``` vignette("individual-steps", package = "spatzie") ``` ## Build status | Platform | Status | |------|------| | Travis CI | [![Travis build status](]( | | Bioconductor 3.17 (release) | [![BioC release](]( | | Bioconductor 3.18 (devel) | [![BioC devel](]( | ## Citation If you use *spatzie* in your research, please cite: **spatzie: An R package for identifying significant transcription factor motif co-enrichment from enhancer-promoter interactions** Jennifer Hammelman, Konstantin Krismer, and David K. Gifford *Nucleic Acids Research*, Volume 50, Issue 9, 20 May 2022, Page e52; DOI: ## Funding The development of this method was supported by National Institutes of Health (NIH) grants 1R01HG008754 and 1R01NS109217, and a National Science Foundation Graduate Research Fellowship (1122374).