--- title: "hicVennDiagram Vignette: overview" author: "Jianhong Ou" date: "`r BiocStyle::doc_date()`" package: "`r BiocStyle::pkg_ver('hicVennDiagram')`" vignette: > %\VignetteIndexEntry{hicVennDiagram Vignette: overview} %\VignetteEngine{knitr::rmarkdown} %\VignetteEncoding{UTF-8} output: html_document: theme: simplex toc: true toc_float: true toc_depth: 4 fig_caption: true --- ```{r, echo=FALSE, results="hide", warning=FALSE} suppressPackageStartupMessages({ library(hicVennDiagram) library(GenomicRanges) }) knitr::opts_chunk$set(warning=FALSE, message=FALSE) ``` # Introduction When comparing samples, it is common to perform the task of identifying overlapping loops among two or more sets of genomic interactions. Traditionally, this is achieved through the use of visualizations such as `vennDiagram` or `UpSet` plots. However, it is frequently observed that the total count displayed in these plots does not match the original counts for each individual list. The reason behind this discrepancy is that a single overlap may encompass multiple interactions for one or more samples. This issue is extensively discussed in the realm of overlapping caller for ChIP-Seq peaks. The _hicVennDiagram_ aims to provide a easy to use tool for overlapping interactions calculation and proper visualization methods. The _hicVennDiagram_ generates plots specifically crafted to eliminate the deceptive visual representation caused by the counts method. # Quick start Here is an example using _hicVennDiagram_ with 3 files in `BEDPE` format. ## Installation First, install _hicVennDiagram_ and other packages required to run the examples. ```{r installation, eval=FALSE} library(BiocManager) BiocManager::install("hicVennDiagram") ``` ## Load library ```{r load_library} library(hicVennDiagram) library(ggplot2) ``` ```{r quick_start} # list the BEDPE files file_folder <- system.file("extdata", package = "hicVennDiagram", mustWork = TRUE) file_list <- dir(file_folder, pattern = ".bedpe", full.names = TRUE) names(file_list) <- sub(".bedpe", "", basename(file_list)) basename(file_list) venn <- vennCount(file_list) ## upset plot ## temp fix for https://github.com/krassowski/complex-upset/issues/195 upset_themes_fix <- lapply(ComplexUpset::upset_themes, function(.ele){ lapply(.ele, function(.e){ do.call(theme, .e[names(.e) %in% names(formals(theme))]) }) }) upsetPlot(venn, themes = upset_themes_fix) ## venn plot vennPlot(venn) ## use browser to adjust the text position, and shape colors. browseVenn(vennPlot(venn)) ``` # Details about `vennCount` The `vennCount` function borrows the power of `InteractionSet:findOverlaps` to calculate the overlaps and then summarizes the results for each category. Users may want to try different combinations of `maxgap` and `minoverlap` parameters to calculate the overlapping loops. ```{r vennCount} venn <- vennCount(file_list, maxgap=50000, FUN = max) # by default FUN = min upsetPlot(venn, label_all=list( na.rm = TRUE, color = 'black', alpha = .9, label.padding = unit(0.1, "lines") ), themes = upset_themes_fix) ``` # Plot for overlapping peaks output by `ChIPpeakAnno` ```{r chippeakanno_findOverlapsOfPeaks, warning=FALSE} library(ChIPpeakAnno) bed <- system.file("extdata", "MACS_output.bed", package="ChIPpeakAnno") gr1 <- toGRanges(bed, format="BED", header=FALSE) gff <- system.file("extdata", "GFF_peaks.gff", package="ChIPpeakAnno") gr2 <- toGRanges(gff, format="GFF", header=FALSE, skip=3) ol <- findOverlapsOfPeaks(gr1, gr2) overlappingPeaksToVennTable <- function(.ele){ .venn <- .ele$venn_cnt k <- which(colnames(.venn)=="Counts") rownames(.venn) <- apply(.venn[, seq.int(k-1)], 1, paste, collapse="") colnames(.venn) <- sub("count.", "", colnames(.venn)) vennTable(combinations=.venn[, seq.int(k-1)], counts=.venn[, k], vennCounts=.venn[, seq.int(ncol(.venn))[-seq.int(k)]]) } venn <- overlappingPeaksToVennTable(ol) vennPlot(venn) upsetPlot(venn, themes = upset_themes_fix) ## change the font size of labels and numbers updated_theme <- ComplexUpset::upset_modify_themes( ## get help by vignette('Examples_R', package = 'ComplexUpset') list('intersections_matrix'= ggplot2::theme( ## font size of label: gr1/gr2 axis.text.y=ggplot2::element_text(size=24), ## font size of label `group` axis.title.x=ggplot2::element_text(size=24)), 'overall_sizes'= ggplot2::theme( ## font size of x-axis 0-200 axis.text=ggplot2::element_text(size=12), ## font size of x-label `Set size` axis.title=ggplot2::element_text(size=18)), 'Intersection size'= ggplot2::theme( ## font size of y-axis 0-150 axis.text=ggplot2::element_text(size=20), ## font size of y-label `Intersection size` axis.title=ggplot2::element_text(size=16) ), 'default'=ggplot2::theme_minimal()) ) updated_theme <- lapply(updated_theme, function(.ele){ lapply(.ele, function(.e){ do.call(theme, .e[names(.e) %in% names(formals(theme))]) }) }) upsetPlot(venn, label_all=list(na.rm = TRUE, color = 'gray30', alpha = .7, label.padding = unit(0.1, "lines"), size = 8 #control the font size of the individual num ), base_annotations=list('Intersection size'= ComplexUpset::intersection_size( ## font size of counts in the bar-plot text = list(size=6) )), themes = updated_theme ) ``` # Session Info ```{r sessionInfo, results='asis'} sessionInfo() ```