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Identification of enriched motif pairs from chromatin interaction data

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spatzie: Identification of enriched motif pairs from chromatin interaction data

license: GPL-3 DOI BioC platforms Coverage Status

https://spatzie.mit.edu

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 https://spatzie.mit.edu.

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 spatzie.mit.edu.

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 3.18 (release) BioC release
Bioconductor 3.19 (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: https://doi.org/10.1093/nar/gkac036

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).

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Identification of enriched motif pairs from chromatin interaction data

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