{"id":16698419,"url":"https://github.com/lgatto/rintro","last_synced_at":"2025-03-14T04:09:23.027Z","repository":{"id":138540237,"uuid":"9978871","full_name":"lgatto/RIntro","owner":"lgatto","description":"An introduction to R for beginners, using microarrays as main thread","archived":false,"fork":false,"pushed_at":"2014-11-12T21:09:28.000Z","size":14756,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":4,"default_branch":"master","last_synced_at":"2025-01-20T23:12:56.652Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":"http://lgatto.github.io/RIntro/","language":"R","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/lgatto.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2013-05-10T09:54:31.000Z","updated_at":"2017-03-04T21:19:08.000Z","dependencies_parsed_at":"2023-03-13T10:53:47.962Z","dependency_job_id":null,"html_url":"https://github.com/lgatto/RIntro","commit_stats":null,"previous_names":[],"tags_count":2,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/lgatto%2FRIntro","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/lgatto%2FRIntro/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/lgatto%2FRIntro/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/lgatto%2FRIntro/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/lgatto","download_url":"https://codeload.github.com/lgatto/RIntro/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":243521281,"owners_count":20304186,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","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":[],"created_at":"2024-10-12T17:52:01.343Z","updated_at":"2025-03-14T04:09:23.004Z","avatar_url":"https://github.com/lgatto.png","language":"R","readme":"\nA 1 day `R` introductory course for non-programmers, using\nmicroarrays as main thread. Also includes an intro to Bioconductor and\nthe `eSet` infrastructure. Initially set up for the\n[diXa](http://www.dixa-fp7.eu/dixa-training/dixa-training-agenda/dixa-microarray-training)\nMicroarray Analysis using R and Bioconductor training (see tags for\nspecific courses). Partially based on the\n[Beginners guide to solving biological problems in `R`](http://www.training.cam.ac.uk/gsls/course/gsls-rintro)\n(see also [here](http://logic.sysbiol.cam.ac.uk/teaching/Rcourse/))\ncourse by Robert Stojnić, Rob Foy, John Davey, Laurent Gatto and Ian\nRoberts.\n\n## Slides\n\nThe [slides](https://github.com/lgatto/RIntro/blob/master/RIntro.pdf?raw=true)\nprovide a general introduction to [`R`](http://www.r-project.org/) and\nthe main data structures. Scripting and plotting is presented by means\nof exercises using microarray data as example. Finally,\n[Bioconductor](http://bioconductor.org/) and the microarray\n`eSet`/`ExpressionSet` classes are introduced and compared to the\nprevious introductory material and exercises.\n\n## Exercises\n\n1. Using `R` interactively and running a script.\n2. [Vectors](https://github.com/lgatto/RIntro/blob/master/Exercises/Exercise-02.md)\n3. [How to store microarray data](https://github.com/lgatto/RIntro/blob/master/Exercises/Exercise-03.md)\n  * expression data and meta data\n  * matrices, data frames and lists.\n4. [A short microarray analysis](https://github.com/lgatto/RIntro/blob/master/Exercises/Exercise-04.md)\n  * reading spreadsheets into `R`\n  * saving/loading objects\n  * basic plotting\n  * `for` loops: counting differentially expressed genes in three\n     microarray result data\n5. [Another microarray analysis](https://github.com/lgatto/RIntro/blob/master/Exercises/Exercise-05.md)\n  * combining multiple expression matrices and produce a heatmap\n  * extracting, parsing and visualising genes of interest\n6. [A short Bioconductor data analysis](https://github.com/lgatto/RIntro/blob/master/Exercises/Exercise-06.md)\n  * Quality control\n  * Exploratory data analysis\n\n## See also\n\nSee the [TeachingMaterial](https://github.com/lgatto/TeachingMaterial)\nrepository for more material.\n\n\nThis material is licensed under the\n[Creative Commons Attribution-ShareAlike 3.0 License](http://creativecommons.org/licenses/by-sa/3.0/).\n","funding_links":[],"categories":[],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flgatto%2Frintro","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Flgatto%2Frintro","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flgatto%2Frintro/lists"}