Package: intervene
Intervenea tool for intersection and visualization of multiple gene or genomic region setsDocumentationA detailed documentation is available in different formats:HTML|PDF|ePUBInstallationQuick installation using Condacondainstall-cbiocondainterveneThis will install all the dependencies and you are ready to use Intervene.Install usingpipYou can install Intervene from PyPi using pip.Install from PyPi:pip install interveneNote: If you install using pip, make sure to install BEDTools and R packages listed below.Intervene requires the following Python modules and R packages:Python (=> 3.3 ):https://www.python.org/BedTools (Latest version):https://github.com/arq5x/bedtools2pybedtools (>= 0.7.9):https://daler.github.io/pybedtools/Pandas (>= 0.16.0):http://pandas.pydata.org/Seaborn (>= 0.7.1):http://seaborn.pydata.org/R (>= 3.0):https://www.r-project.org/R packages including UpSetR (v1.4.0), corrplotInstall BEDToolsWe are using pybedtools, which is Python wrapper for BEDTools. So, BEDTools should be installed before using Intervene. It’s recomended to have a latest version, but if you have an older version already install, it should be fine.A quick installation, if you have conda installed.condainstall-cbiocondabedtoolsPlease read the instructions athttps://github.com/arq5x/bedtools2to install BEDTools, and make sure it is on your path and you are able to call bedtools from any directory.Install required R packagesIntervene rquires three R packages,UpSetR,corrplotfor visualization andCairoto generate high-quality vector and bitmap figures.install.packages(c("UpSetR","corrplot","Cairo"))Install Intervene from sourceYou can install a development version by usinggitfrom GitHub or Bitbucket.Install development version fromBitbucketIf you havegitinstalled, use this:gitclonehttps://bitbucket.org/CBGR/intervene.gitcdintervenepythonsetup.pysdistinstallInstall development version fromGitHubIf you havegitinstalled, use this:gitclonehttps://github.com/asntech/intervene.gitcdintervenepythonsetup.pysdistinstallHow to use InterveneOnce you have installed Intervene, you can type:intervene--helpThis will show the following help message.usage:intervene<subcommand>[options]positionalarguments<subcommand>:{venn,upset,pairwise}ListofsubcommandsvennVenndiagramofintersectionofgenomicregionsorlistsets(upto6-way).upsetUpSetdiagramofintersectionofgenomicregionsorlistsets.pairwisePairwiseintersectionandheatmapofNgenomicregionsetsin<BED/GTF/GFF>format.optionalarguments:-h,--helpshowthishelpmessageandexit-v,--versionshowprogram'sversionnumberandexitto see the help for the three subcommandspairwise,vennandupsettype:intervenepairwise--helpintervenevenn--helpinterveneupset--helpRun Intervene on test dataTo run Intervene using example data, use the following commands. To access the test data make sure you havesudoorrootaccess.intervenepairwise--testintervenevenn--testinterveneupset--testIf you have installed Intervene locally from the source code, you may have problem to find test data. You can download the test data herehttps://github.com/asntech/intervene/tree/master/intervene/example_dataand point to it using-iinstead of--test../intervene/intervenevenn-iintervene/example_data/ENCODE_hESC/*.bed./intervene/interveneupset-iintervene/example_data/ENCODE_hESC/*.bed./intervene/intervenepairwise-iintervene/example_data/dbSUPER_mm9/*.bedThe above three test commands will generate the following three figures (a, b and c).By default your results will stored in the current working directory with a folder namedIntervene_results. If you wish to save the results in a specific folder, you can type:intervene upset --test --output ~/path/to/your/folderInteractive Shiny AppIntervene Shiny App is freely available athttps://asntech.shinyapps.io/interveneorhttps://intervene.shinyapps.io/interveneThe source code for the Shiny app is available athttps://github.com/asntech/intervene-shinySupportIf you have questions, or found any bug in the program, please write to us ataziz.khan[at]ncmm.uio.noCite UsIf you use Intervene please cite us:Khan A, Mathelier A. Intervene: a tool for intersection and visualization of multiple gene or genomic region sets. BMC Bioinformatics. 2017;18:287. doi:10.1186/s12859-017-1708-7