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igvShiny

The igvShiny package is a wrapper of Integrative Genomics Viewer (IGV). It comprises an htmlwidget version of IGV. It can be used as a module in Shiny apps.

Installation

if (!requireNamespace("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("igvShiny")

Loading the package

Running minimal Shiny app

Running the minimal Shiny app with igvShiny is as simple as:

  • providing genome details via parseAndValidateGenomeSpec
  • using igvShinyOutput as the UI function
  • using renderIgvShiny as the server function

The he minimal Shiny app make look like:

library(igvShiny)
options <- parseAndValidateGenomeSpec(genomeName="hg38",  initialLocus="NDUFS2")
if (interactive()) {
    ui <- shinyUI(fluidPage(igvShinyOutput('igvShiny'), width = 10))
    server <-
        function(input, output, session) {
            output$igvShiny <- renderIgvShiny({
                igvShiny(options)
            })
            }
    runApp(shinyApp(ui = ui, server = server))
    }

Providing genome details

Multiple genomes are currently supported by IGV: link. In igvShiny this set of genomes is called stock genomes. One can select any stock genome easily by running parseAndValidateGenomeSpec with single genomeName value properly assigned. For example to use the most popular mouse genome one need to run:

igvShiny::parseAndValidateGenomeSpec("mm10")
#> $stockGenome
#> [1] TRUE
#> 
#> $dataMode
#> [1] NA
#> 
#> $validated
#> [1] TRUE
#> 
#> $genomeName
#> [1] "mm10"
#> 
#> $initialLocus
#> [1] "all"
#> 
#> $fasta
#> [1] NA
#> 
#> $fastaIndex
#> [1] NA
#> 
#> $annotation
#> [1] NA

The list of available stock genomes in igvShiny can be found with:

igvShiny::get_css_genomes()
#>  [1] "hs1"             "chm13v1.1"       "hg38"            "hg38_1kg"       
#>  [5] "hg19"            "hg18"            "mm39"            "mm10"           
#>  [9] "mm9"             "rn7"             "rn6"             "gorGor6"        
#> [13] "gorGor4"         "panTro6"         "panTro5"         "panTro4"        
#> [17] "macFas5"         "GCA_011100615.1" "panPan2"         "canFam3"        
#> [21] "canFam4"         "canFam5"         "bosTau9"         "bosTau8"        
#> [25] "susScr11"        "galGal6"         "GCF_016699485.2" "danRer11"       
#> [29] "danRer10"        "ce11"            "dm6"             "dm3"            
#> [33] "dmel_r5.9"       "sacCer3"         "ASM294v2"        "ASM985889v3"    
#> [37] "tair10"          "GCA_003086295.2" "GCF_001433935.1" "NC_016856.1"    
#> [41] "GCA_000182895.1"

See also demo app for stock genomes when one can select genome of interest and familiarize with the basic functionalities provided via igvShiny:

library(igvShiny)
demo_app_file <- system.file(package= "igvShiny", "demos", "stockGenomesDemo.R")
    if (interactive()) {
        shiny::runApp(demo_app_file)
        }

It’s also possible to use custom genomes (i.e. non-stock genomes). In such cases one has to provide data for: FASTA file, FASTA index file and genome annotation file. The files can provided as local paths (dataMode = localFiles or via URLs (dataMode = http). See below the examples for both cases.

library(igvShiny)

# defining custom genome with data provided via URLs
base_url <- "https://gladki.pl/igvr/testFiles"
title <- "ribo remote"
fasta_file <- sprintf("%s/%s", base_url, "ribosomal-RNA-gene.fasta")
fastaIndex_file <- sprintf("%s/%s", base_url, "ribosomal-RNA-gene.fasta.fai")
annotation_file <- sprintf("%s/%s", base_url, "ribosomal-RNA-gene.gff3")
locus <- "U13369.1:7,276-8,225"
genomeOptions <- parseAndValidateGenomeSpec(
    genomeName = title,
    initialLocus = locus,
    stockGenome = FALSE,
    dataMode = "http",
    fasta = fasta_file,
    fastaIndex = fastaIndex_file,
    genomeAnnotation = annotation_file
    )
genomeOptions
#> $stockGenome
#> [1] FALSE
#> 
#> $dataMode
#> [1] "http"
#> 
#> $validated
#> [1] TRUE
#> 
#> $genomeName
#> [1] "ribo remote"
#> 
#> $fasta
#> [1] "https://gladki.pl/igvr/testFiles/ribosomal-RNA-gene.fasta"
#> 
#> $fastaIndex
#> [1] "https://gladki.pl/igvr/testFiles/ribosomal-RNA-gene.fasta.fai"
#> 
#> $initialLocus
#> [1] "U13369.1:7,276-8,225"
#> 
#> $annotation
#> [1] "https://gladki.pl/igvr/testFiles/ribosomal-RNA-gene.gff3"

# defining custom genome with data provided with local files
data_directory <- system.file(package = "igvShiny", "extdata")
fasta_file      <- file.path(data_directory, "ribosomal-RNA-gene.fasta")
fastaIndex_file <- file.path(data_directory, "ribosomal-RNA-gene.fasta.fai")
annotation_file <- file.path(data_directory, "ribosomal-RNA-gene.gff3")
genomeOptions2 <- parseAndValidateGenomeSpec(
    genomeName = "ribo local",
    initialLocus = "U13369.1:7,276-8,225",
    stockGenome = FALSE,
    dataMode = "localFiles",
    fasta = fasta_file,
    fastaIndex = fastaIndex_file,
    genomeAnnotation = annotation_file
    )
genomeOptions2
#> $stockGenome
#> [1] FALSE
#> 
#> $dataMode
#> [1] "localFiles"
#> 
#> $validated
#> [1] TRUE
#> 
#> $genomeName
#> [1] "ribo local"
#> 
#> $fasta
#> [1] "/__w/_temp/Library/igvShiny/extdata/ribosomal-RNA-gene.fasta"
#> 
#> $fastaIndex
#> [1] "/__w/_temp/Library/igvShiny/extdata/ribosomal-RNA-gene.fasta.fai"
#> 
#> $initialLocus
#> [1] "U13369.1:7,276-8,225"
#> 
#> $annotation
#> [1] "/__w/_temp/Library/igvShiny/extdata/ribosomal-RNA-gene.gff3"

See also demo apps for custom genomes with data provided via URLs:

library(igvShiny)
demo_app_file <- system.file(
    package = "igvShiny", 
    "demos", 
    "igvShinyDemo-customGenome-http.R"
    )
if (interactive()) {
    shiny::runApp(demo_app_file)
    }

as well as data provided via local files:

library(igvShiny)
demo_app_file <-
    system.file(
        package = "igvShiny", 
        "demos", 
        "igvShinyDemo-customGenome-localFiles.R")
if (interactive()) {
    shiny::runApp(demo_app_file)
    }

Main functionalities

In principle igvShiny provides the same functionalities that one can find in igv.js. In summary following actions are currently possible (wrapped as the R helpers):

  • load tracks with the following formats/data types:
    • Bed
    • BedGraph
    • Seg
    • GWAS
    • Bam
    • Cram
    • Vcf
    • GFF3
  • showGenomicRegion (zoom in or out to show the nominated region, by chromosome locus or gene symbol)
  • getGenomicRegion (return the current IGV region)
  • removeUserAddedTracks (remove tracks from the browser, added during the session by the user)

See also demo app to familiarize with the basic functionalities provided by igvShiny:

library(igvShiny)
demo_app_file <- system.file(package= "igvShiny", "demos", "igvShinyDemo.R")
if (interactive()) {
    shiny::runApp(demo_app_file)
    }

Session Info

sessionInfo()
#> R version 4.3.3 (2024-02-29)
#> Platform: x86_64-pc-linux-gnu (64-bit)
#> Running under: Ubuntu 22.04.4 LTS
#> 
#> Matrix products: default
#> BLAS:   /usr/lib/x86_64-linux-gnu/openblas-pthread/libblas.so.3 
#> LAPACK: /usr/lib/x86_64-linux-gnu/openblas-pthread/libopenblasp-r0.3.20.so;  LAPACK version 3.10.0
#> 
#> locale:
#>  [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
#>  [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8    
#>  [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
#>  [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
#>  [9] LC_ADDRESS=C               LC_TELEPHONE=C            
#> [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       
#> 
#> time zone: UTC
#> tzcode source: system (glibc)
#> 
#> attached base packages:
#> [1] stats4    stats     graphics  grDevices utils     datasets  methods  
#> [8] base     
#> 
#> other attached packages:
#> [1] igvShiny_0.99.7      shiny_1.8.1.1        GenomicRanges_1.54.1
#> [4] GenomeInfoDb_1.38.8  IRanges_2.36.0       S4Vectors_0.40.2    
#> [7] BiocGenerics_0.48.1  BiocStyle_2.30.0    
#> 
#> loaded via a namespace (and not attached):
#>  [1] sass_0.4.9              futile.options_1.0.1    bitops_1.0-7           
#>  [4] stringi_1.8.3           digest_0.6.35           magrittr_2.0.3         
#>  [7] evaluate_0.23           bookdown_0.39           fastmap_1.1.1          
#> [10] jsonlite_1.8.8          backports_1.4.1         formatR_1.14           
#> [13] promises_1.3.0          BiocManager_1.30.22     httr_1.4.7             
#> [16] purrr_1.0.2             scales_1.3.0            randomcoloR_1.1.0.1    
#> [19] textshaping_0.3.7       jquerylib_0.1.4         cli_3.6.2              
#> [22] rlang_1.1.3             XVector_0.42.0          futile.logger_1.4.3    
#> [25] munsell_0.5.1           cachem_1.0.8            yaml_2.3.8             
#> [28] Rtsne_0.17              tools_4.3.3             checkmate_2.3.1        
#> [31] memoise_2.0.1           colorspace_2.1-0        httpuv_1.6.15          
#> [34] GenomeInfoDbData_1.2.11 lambda.r_1.2.4          curl_5.2.1             
#> [37] vctrs_0.6.5             R6_2.5.1                mime_0.12              
#> [40] lifecycle_1.0.4         stringr_1.5.1           zlibbioc_1.48.2        
#> [43] V8_4.4.2                fs_1.6.3                htmlwidgets_1.6.4      
#> [46] cluster_2.1.6           ragg_1.3.0              desc_1.4.3             
#> [49] pkgdown_2.0.9           bslib_0.7.0             later_1.3.2            
#> [52] glue_1.7.0              Rcpp_1.0.12             systemfonts_1.0.6      
#> [55] xfun_0.43               knitr_1.46              xtable_1.8-4           
#> [58] htmltools_0.5.8.1       rmarkdown_2.26          compiler_4.3.3         
#> [61] RCurl_1.98-1.14