{"id":21976705,"url":"https://github.com/CoreArray/gds2bgen","last_synced_at":"2025-07-22T19:30:44.905Z","repository":{"id":81752658,"uuid":"158320160","full_name":"CoreArray/gds2bgen","owner":"CoreArray","description":"R package for the format conversion from bgen to gds","archived":false,"fork":false,"pushed_at":"2025-06-14T04:29:16.000Z","size":41695,"stargazers_count":3,"open_issues_count":2,"forks_count":1,"subscribers_count":1,"default_branch":"master","last_synced_at":"2025-06-14T05:28:13.076Z","etag":null,"topics":["bgen","gds"],"latest_commit_sha":null,"homepage":"","language":"C++","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/CoreArray.png","metadata":{"files":{"readme":"README.md","changelog":"NEWS","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,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null}},"created_at":"2018-11-20T02:36:13.000Z","updated_at":"2025-06-14T04:29:20.000Z","dependencies_parsed_at":null,"dependency_job_id":"4052ebc0-15c3-4df2-aa1e-66ce6c1360d7","html_url":"https://github.com/CoreArray/gds2bgen","commit_stats":null,"previous_names":["corearray/gds2bgen"],"tags_count":2,"template":false,"template_full_name":null,"purl":"pkg:github/CoreArray/gds2bgen","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/CoreArray%2Fgds2bgen","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/CoreArray%2Fgds2bgen/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/CoreArray%2Fgds2bgen/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/CoreArray%2Fgds2bgen/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/CoreArray","download_url":"https://codeload.github.com/CoreArray/gds2bgen/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/CoreArray%2Fgds2bgen/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":266561056,"owners_count":23948585,"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","status":"online","status_checked_at":"2025-07-22T02:00:09.085Z","response_time":66,"last_error":null,"robots_txt_status":null,"robots_txt_updated_at":null,"robots_txt_url":"https://github.com/robots.txt","online":true,"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":["bgen","gds"],"created_at":"2024-11-29T16:11:49.807Z","updated_at":"2025-07-22T19:30:44.875Z","avatar_url":"https://github.com/CoreArray.png","language":"C++","funding_links":[],"categories":[],"sub_categories":[],"readme":"gds2bgen: Format Conversion from BGEN to GDS\n===\n\n![GPLv3](http://www.gnu.org/graphics/gplv3-88x31.png)\n[GNU General Public License, GPLv3](http://www.gnu.org/copyleft/gpl.html)\n\n\n## Description\n\nThis package provides functions for format conversion from [bgen](http://bgenformat.org) files to [SeqArray GDS](https://github.com/zhengxwen/SeqArray) files.\n\n* gds2bgen has been moved to https://github.com/CoreArray/gds2bgen from https://github.com/zhengxwen/gds2bgen since Feb 2025.\n\n\n## Version\n\nv0.9.4\n\n\n## Package Maintainer\n\nDr. Xiuwen Zheng ([zhengx@u.washington.edu](zhengx@u.washington.edu))\n\n\n## Installation\n\nRequires R (≥ v3.5.0), [gdsfmt](http://www.bioconductor.org/packages/gdsfmt) (≥ v1.20.0), [SeqArray](http://www.bioconductor.org/packages/SeqArray) (≥ v1.24.0)\n\n* Installation from Github:\n```R\nlibrary(\"devtools\")\ninstall_github(\"CoreArray/gds2bgen\")\n```\nThe `install_github()` approach requires that you build from source, i.e. `make` and compilers must be installed on your system -- see the [R FAQ](http://cran.r-project.org/faqs.html) for your operating system; you may also need to install dependencies manually.\n\nOr manually intall the package\n```sh\ngit clone https://github.com/CoreArray/gds2bgen\ncd gds2bgen/src\nunzip bgen_v1.1.8.zip\ncd bgen_v1.1.8\npython ./waf configure\npython ./waf\ncp build/libbgen.a ..\ncp build/3rd_party/zstd-1.1.0/libzstd.a ..\nrm -rf build\nsleep 1; touch ../libbgen.a\ncd ../../..\nR CMD INSTALL gds2bgen\n```\n\n\n## Copyright Notice\n\nThis package includes the sources of the bgen library (https://enkre.net/cgi-bin/code/bgen/dir?ci=trunk), Boost (the C++\nlibraries, https://www.boost.org) and Zstandard (https://zstd.net).\n\n\n## Citations for GDS\n\nZheng X, Levine D, Shen J, Gogarten SM, Laurie C, Weir BS (2012). A High-performance Computing Toolset for Relatedness and Principal Component Analysis of SNP Data. *Bioinformatics*. [DOI: 10.1093/bioinformatics/bts606](http://dx.doi.org/10.1093/bioinformatics/bts606).\n\nZheng X, Gogarten S, Lawrence M, Stilp A, Conomos M, Weir BS, Laurie C, Levine D (2017). SeqArray -- A storage-efficient high-performance data format for WGS variant calls. *Bioinformatics*. [DOI: 10.1093/bioinformatics/btx145](http://dx.doi.org/10.1093/bioinformatics/btx145).\n\n\n## Examples\n\n```R\nlibrary(gds2bgen)\n\nseqBGEN_Info()  # bgen library version\n## \"bgen_lib_v1.1.8\"\n\nbgen_fn \u003c- system.file(\"extdata\", \"example.8bits.bgen\", package=\"gds2bgen\")\n# or bgen_fn \u003c- \"your_bgen_file.bgen\"\nseqBGEN_Info(bgen_fn)\n\n## File: gds2bgen/extdata/example.8bits.bgen\n## # of samples: 500\n## # of variants: 199\n## Compression method: zlib\n## Layout version: v1.2\n## Unphased: TRUE\n## # of bits: 8\n## Ploidy: 2\n## sample id: sample_001, sample_002, sample_003, sample_004, ...\n\n\n# example.8bits.bgen ==\u003e example.gds, using 4 cores\nseqBGEN2GDS(bgen_fn, \"example.gds\",\n    storage.option=\"LZMA_RA\",  # compression option, e.g., ZIP_RA for zlib or LZ4_RA for LZ4\n    float.type=\"packed8\",      # 8-bit packed real numbers\n    geno=FALSE,     # 2-bit integer genotypes, stored in 'genotype/data'\n    dosage=TRUE,    # numeric alternative allele dosages, stored in 'annotation/format/DS'\n    prob=FALSE,     # numeric genotype probabilities, stored in 'annotation/format/GP'\n    parallel=4      # the number of cores\n)\n\n\n# show file structure\nlibrary(SeqArray)\n(f \u003c- seqOpen(\"example.gds\"))\nseqClose(f)\n\n## File: example.gds (137.7K)\n## +    [  ] *\n## |--+ description   [  ] *\n## |--+ sample.id   { Str8 500 LZMA_ra(7.02%), 393B } *\n## |--+ variant.id   { Int32 199 LZMA_ra(33.9%), 277B } *\n## |--+ position   { Int32 199 LZMA_ra(60.6%), 489B } *\n## |--+ chromosome   { Str8 199 LZMA_ra(15.7%), 101B } *\n## |--+ allele   { Str8 199 LZMA_ra(11.8%), 101B } *\n## |--+ genotype   [  ] *\n## |--+ phase   [  ]\n## |--+ annotation   [  ]\n## |  |--+ id   { Str8 199 LZMA_ra(18.6%), 321B } *\n## |  |--+ qual   { Float32 199 LZMA_ra(11.8%), 101B } *\n## |  |--+ filter   { Int32 199 LZMA_ra(11.3%), 97B } *\n## |  |--+ info   [  ]\n## |  \\--+ format   [  ]\n## |     |--+ DS   [  ] *\n## |     |  \\--+ data   { PackedReal8U 500x199 LZMA_ra(55.6%), 54.0K } *\n## \\--+ sample.annotation   [  ]\n```\n\n\n## Also See\n\n[seqVCF2GDS()](https://rdrr.io/bioc/SeqArray/man/seqVCF2GDS.html) in the [SeqArray](https://bioconductor.org/packages/SeqArray) package, conversion from VCF files to GDS files.\n\n[seqBED2GDS()](https://rdrr.io/bioc/SeqArray/man/seqBED2GDS.html) in the [SeqArray](https://bioconductor.org/packages/SeqArray) package, conversion from PLINK BED files to GDS files.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FCoreArray%2Fgds2bgen","html_url":"https://awesome.ecosyste.ms/projects/github.com%2FCoreArray%2Fgds2bgen","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FCoreArray%2Fgds2bgen/lists"}