{"id":19630530,"url":"https://github.com/mahshaaban/target","last_synced_at":"2026-02-18T20:31:07.648Z","repository":{"id":185878377,"uuid":"204856028","full_name":"MahShaaban/target","owner":"MahShaaban","description":"target: An R Package to Predict Combined Function of Transcription Factors","archived":false,"fork":false,"pushed_at":"2020-04-18T03:30:14.000Z","size":4721,"stargazers_count":5,"open_issues_count":0,"forks_count":1,"subscribers_count":1,"default_branch":"master","last_synced_at":"2025-10-20T01:36:35.930Z","etag":null,"topics":["algorithm","chip-seq","dna-binding","gene-regulation","r-package","transcription-factors"],"latest_commit_sha":null,"homepage":"https://bioconductor.org/packages/target/","language":"HTML","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"gpl-3.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/MahShaaban.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":"CONTRIBUTING.md","funding":null,"license":"LICENSE.md","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null}},"created_at":"2019-08-28T05:37:02.000Z","updated_at":"2025-04-04T07:53:40.000Z","dependencies_parsed_at":null,"dependency_job_id":"10d6f851-302d-4676-8dd9-05d94036715d","html_url":"https://github.com/MahShaaban/target","commit_stats":null,"previous_names":["mahshaaban/target"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/MahShaaban/target","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/MahShaaban%2Ftarget","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/MahShaaban%2Ftarget/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/MahShaaban%2Ftarget/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/MahShaaban%2Ftarget/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/MahShaaban","download_url":"https://codeload.github.com/MahShaaban/target/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/MahShaaban%2Ftarget/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":29594257,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-02-18T18:54:29.675Z","status":"ssl_error","status_checked_at":"2026-02-18T18:50:50.517Z","response_time":162,"last_error":"SSL_read: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["algorithm","chip-seq","dna-binding","gene-regulation","r-package","transcription-factors"],"created_at":"2024-11-11T12:02:52.941Z","updated_at":"2026-02-18T20:31:07.601Z","avatar_url":"https://github.com/MahShaaban.png","language":"HTML","readme":"[![Travis build status](https://travis-ci.org/MahShaaban/target.svg?branch=master)](https://travis-ci.org/MahShaaban/target)\n[![AppVeyor build status](https://ci.appveyor.com/api/projects/status/github/MahShaaban/target?branch=master\u0026svg=true)](https://ci.appveyor.com/project/MahShaaban/target)\n[![Codecov test coverage](https://codecov.io/gh/MahShaaban/target/branch/master/graph/badge.svg)](https://codecov.io/gh/MahShaaban/target?branch=master)\n\n# target\n\nPredict Combined Function of Transcription Factors\n\nImplement the BETA algorithm for infering direct target genes from DNA-binding\nand perturbation expression data Wang et al. (2013). Extend the algorithm to \npredict the combined function of two DNA-binding elements from comprable \nbinding and expression data.\n\n# Installation\n\nThe `target` package can be installed from Bioconductor using `BiocManager`.\n\n```{r install_biocmanager,eval=FALSE}\nif (!requireNamespace(\"BiocManager\", quietly = TRUE))\n    install.packages(\"BiocManager\")\nBiocManager::install(\"target\")\n```\n\n## Getting started\n\nThe `target` package contains two simulated datasets. `sim_peaks` is random \npeaks with random distances from the transcripts of chromosome 1 of the mm10\nmouse genome. `sim_transcripts` is the same transcripts with random singed \nstatistics assigned to each. In the following two examples, we introduce\nchanges in these statistics to simulate conditions where two factors are \nworking cooperatively or competitively on the same transcripts. \n\n```r\n# load libraries\nlibrary(target)\n```\n\n```r\n# load data\ndata(\"sim_peaks\")\ndata(\"sim_transcripts\")\n```\n\nTo help visualize these cases, a plotting function `plot_profiles` was \nconstructed to introduce the changes `change` in the statistics of the \ntranscripts near the `n` number of peaks. The source code for the function is \navailable in `inst/extdata/plot-profiles.R` which we source to use here. \nThe output of the function is a series of plots to visualize the statistics of\nthe two factors before and after introducing the changes, the peaks distances \nand scores and the predicted functions of the factors individually and \ncombined.\n\n```r\n# source the plotting function\nsource(system.file('extdata', 'plot-profiles.R', package = 'target'))\n```\n\nThe first two inputs to the plotting function is the simulated peaks and \ntranscripts. We chose to introduce positive changes to the statistics of the\ntranscripts with the top 5000 nearby peaks of the two factors.\n\n```r\n# simulate and plot cooperative factors\nplot_profiles(sim_peaks,\n              sim_transcripts,\n              n = 5000,\n              change = c(3, 3))\n```\n\nThe changes introduced above are illustrated in the right upper quadrant of the\nscatter plot. The predicted functions of the two factors are similar, as shown\nby distribution function of the regulatory potential of their targets. \nFinally, when the targets are predicted based on the two statistics combined, \nthe sign of the statistics product determines the direction of the factor\ninteractions. Here, more higher ranking transcripts had positive/red/\ncooperative change associated with the two factors.\n\n## References\n\nWang S, Sun H, Ma J, et al. Target analysis by integration of transcriptome and\nChIP-seq data with BETA. Nat Protoc. 2013;8(12):2502–2515. \ndoi:10.1038/nprot.2013.150\n\n# Citation\n\nFor citing the package use:\n\n```{r citation, warning=FALSE}\n# citing the package\ncitation(\"target\")\n","funding_links":[],"categories":[],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmahshaaban%2Ftarget","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fmahshaaban%2Ftarget","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmahshaaban%2Ftarget/lists"}