NAR Genomics and BioinformaticsBioinformaticsPeer-reviewed journal article
Loopsim: Enrichment Analysis of ChromosomeConformation Capture with Fast EmpiricalDistribution Simulation
Gideon ShakediD, Haihan ZhangiD, Zhaolin ZhangiD, Jiayu ZhouiD, Johann Eli GudjonssoniD, James T Elder, Matthew T. PatrickiD, Lam C. TsoiiD
Abstract
SummaryGene regulation is intricately influenced by the three-dimensional organization of the genome. In particular, chromatin can exist in loop structures that enable long-range regulatory interactions. By utilizing chromosome conformation capture techniques such as Hi-C, valuable information regarding the organization of these loop structures in 3D space can be obtained. While functional/feature enrichment has become a standard downstream analysis for different genomic data to provide biological context, tools that developed specifically for high throughput assays capturing chromosome conformation are relatively limited. Here, we present Loopsim, a command-line application that performs enrichment analysis on Hi-C loop profiles against user-defined regions. Loopsim efficiently simulates a background distribution using a distinctive sampling approach that considers loop size, intervals, loop-loop distances, and structure; it then computes loop-level statistics based on the empirical null distribution. AvailabilityLoopsim is a Python package available via PyPI (https://pypi.org/project/loopsim) and the source code is available on GitHub (https://github.com/CutaneousBioinf/Loopsim) under the MIT license.
- assay: Hi-C
- research focus: differential expression
- research focus: gene regulatory network inference
- research focus: benchmarking
- research focus: software / tool
- approach: statistical model
- Citations
- 0
- FWCI
- 0.00
- Field percentile
- 11th percentile
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