GenomicDistributions: fast analysis of genomic intervals with Bioconductor

Abstract

Background Epigenome analysis relies on defined sets of genomic regions output by widely used assays such as ChIP-seq and ATAC-seq. Statistical analysis and visualization of genomic region sets is essential to answer biological questions in gene regulation. As the epigenomics community continues generating data, there will be an increasing need for software tools that can efficiently deal with more abundant and larger genomic region sets. Here, we introduce GenomicDistributions, an R package for fast and easy summarization and visualization of genomic region data. Results GenomicDistributions offers a broad selection of functions to calculate properties of genomic region sets, such as feature distances, genomic partition overlaps, and more. GenomicDistributions functions are meticulously optimized for best-in-class speed and generally outperform comparable functions in existing R packages. GenomicDistributions also offers plotting functions that produce editable ggplot objects. All GenomicDistributions functions follow a uniform naming scheme and can handle either single or multiple region set inputs. Conclusions GenomicDistributions offers a fast and scalable tool for exploratory genomic region set analysis and visualization. GenomicDistributions excels in user-friendliness, flexibility of outputs, breadth of functions, and computational performance. GenomicDistributions is available from Bioconductor (https://bioconductor.org/packages/release/bioc/html/GenomicDistributions.html).

Expanding theBonnMusequence-indexed repository of transposon induced maize (Zea maysL.) mutations in dent and flint germplasm

“…In addition, we employed the published ATAC-seq (Ricci et al ., 2019), ChIP-seq (Makarevitch et al ., 2013; Zhang et al ., 2015), NAM-ATAC and NAM-UMRs datasets (Hufford et al ., 2021) to investigate chromatin accessibility and histone modifications in relation to BonnMu insertions. We used the GenomicDistributions R package (Kupkova et al ., 2022) to analyze distributions and create visualizations.…”

Histone variant H2BE enhances chromatin accessibility in neurons to promote synaptic gene expression and long-term memory

“…For downstream analysis, we used a Peak Score cutoff of 25 and removed peaks that were assigned to ‘ChrUn’ (unknown chromosome) by Homer. The R package GenomicDistributions 15 (v1.6.0) was used to analyze the genomic distribution of peaks. IGV tools 16 (2.12.3) was used to generate genome browser views.…”

PML modulates epigenetic composition of chromatin to regulate expression of pro-metastatic genes in triple-negative breast cancer

“…Gene annotation of ATAC-seq, H3K4me3 and H3K27ac peaks was performed with GREAT ( 39 ), while, genes were ascribed to an EDD called domain if they overlapped with a domain by at least one base-pair. Expected partition distribution plots for ATAC differential peaks was performed with the Genomic distribution package ( 40 ). Mean Log2(ChIP/Input) or normalized counts from all replicates were calculated using wiggletools v1.2 ( https://github.com/Ensembl/WiggleTools ).…”