{"id":22731075,"url":"https://github.com/genentech/midashla","last_synced_at":"2025-04-14T00:32:42.376Z","repository":{"id":55572879,"uuid":"301934927","full_name":"Genentech/midasHLA","owner":"Genentech","description":"R package enabling statistical association analysis and using immunogenetic data transformation functions for HLA amino acid fine mapping, analysis of HLA evolutionary divergence as well as HLA-KIR interactions.","archived":false,"fork":false,"pushed_at":"2024-01-31T19:02:42.000Z","size":13902,"stargazers_count":11,"open_issues_count":7,"forks_count":6,"subscribers_count":6,"default_branch":"master","last_synced_at":"2024-03-17T14:54:40.475Z","etag":null,"topics":["hla","immunogenetic","kir","r"],"latest_commit_sha":null,"homepage":"https://genentech.github.io/MiDAS","language":"R","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/Genentech.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,"governance":null,"roadmap":null,"authors":null}},"created_at":"2020-10-07T05:22:07.000Z","updated_at":"2024-01-29T13:40:55.000Z","dependencies_parsed_at":"2023-12-19T16:20:39.013Z","dependency_job_id":null,"html_url":"https://github.com/Genentech/midasHLA","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Genentech%2FmidasHLA","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Genentech%2FmidasHLA/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Genentech%2FmidasHLA/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Genentech%2FmidasHLA/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Genentech","download_url":"https://codeload.github.com/Genentech/midasHLA/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":229117070,"owners_count":18022819,"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":["hla","immunogenetic","kir","r"],"created_at":"2024-12-10T19:19:21.099Z","updated_at":"2024-12-10T19:19:21.678Z","avatar_url":"https://github.com/Genentech.png","language":"R","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Meaningful Immunogenetic Data at Scale \u003cimg src=\"vignettes/MiDAS_logo.png\" align=\"right\" alt=\"\" width=\"120\" /\u003e\n\nHuman immunogenetic variation in the form of HLA and KIR \ntypes has been shown to be strongly associated with a \nmultitude of immune-related phenotypes. We present MiDAS, \nan R package enabling statistical association analysis and \nusing immunogenetic data transformation functions for HLA \namino acid fine mapping, analysis of HLA evolutionary \ndivergence as well as HLA-KIR interactions. MiDAS closes the \ngap between inference of immunogenetic variation and its \nefficient utilization to make meaningful discoveries.\n\n## Installation\n\n``` r\n# Install from Bioconductor\nBiocManager::install(\"midasHLA\")\n\n# Install development version from GitHub\ndevtools::install_github(\"Genentech/MiDAS\")\n```\n\n## Usage\n\nA user tutorial is available here: \n[https://genentech.github.io/midasHLA/articles/MiDAS_tutorial.html](https://genentech.github.io/MiDAS/articles/MiDAS_tutorial.html)\n\n## Developers notes\n\n### External data\n\nThe package is shipped together with external data such as \nalignment files or allele frequencies. With time, it is \npossible that those resources will become outdated. Here \nfollows a brief description of scripts that can be used for\nupdating those data. It should be noted that data storage details,\nat the external sources, may be changed. In such circumstances, \nthe scripts might become obsolete. Nevertheless, they should be\na good starting point to update those sources in next package \niterations.\n\n`inst/scripts/download_extdata.R` script is used to download HLA \nalignments files. Those are used for translating HLA alleles to \namino acid level. The alignments are downloaded from \n[EBI's IPD-IMGT/HLA database](www.ebi.ac.uk/ipd/imgt/hla/).\nIn some cases alignment files contain sequences for multiple genes,\n those will be split into separate files (eg. DRB genes)\n\n`inst/scripts/parse_alignments.R` script pre-parses alignments files \nfor package use. Purpose of using pre-parsed files is to speed up \nallele to amino acid sequence translation. Resulting `.Rdata` files \nshould be then placed in `inst/extdata` replacing the old alignment \nfiles. \n\n`data-raw/allele_frequencies.R` script fetches HLA allele frequencies \n(for genes A, B, C, DQA1, DQB1, DPA1, DPB1, DRB1, DRB3, DRB4, DRB5) from \n[www.allelefrequencies.net](www.allelefrequencies.net)\ndatabase and save it in a usable format in `data` directory. This data is\nthen available under the `allele_frequencies` variable.\n\n`data-raw/kir_frequencies.R` script fetches KIR genes frequencies \n(for genes 3DL3, 2DS2, 2DL2, 2DL3, 2DP1, 2DL1, 3DP1, 2DL4, 3DL1, 3DS1, \n2DL5, 2DS3, 2DS5, 2DS4, 2DS1, 3DL2) from \n[www.allelefrequencies.net](www.allelefrequencies.net)\ndatabase and save it in a usable format in `data` directory. This data is\nthen available under the `kir_frequencies` variable.\n\n### Package performance\n\nPackage performance can be checked using scripts located in `inst/benchmark`. \nBriefly, we used GNU's `time` (`/usr/bin/time -v`) to measure time and memory \nconsumption of data transformation and 2 workflows. All tests include loading \npackage and reading in input files steps. Look into `inst/benchmark/*` for more \ndetails. \n\n## Citing\nMigdal M, Ruan DF, Forrest WF, Horowitz A, Hammer C (2021) MiDAS—Meaningful Immunogenetic Data at Scale. PLOS Computational Biology 17(7): e1009131. https://doi.org/10.1371/journal.pcbi.1009131\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fgenentech%2Fmidashla","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fgenentech%2Fmidashla","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fgenentech%2Fmidashla/lists"}