[{"_1":2,"_192":-5,"_193":-5},"loaderData",{"_3":4,"_17":18,"_25":26,"_167":168},"root",{"_5":-5,"_6":-7,"_7":8,"_9":-7,"_10":11,"_12":-7,"_13":14,"_15":16},"currentUser","primaryEmail","siteVerification","6LeIxAcTAAAAAJcZVRqyHh71UMIEGNQ_MXjiZKhI","toast","enableDev",false,"incidentStatus","theme","system","contrast","normal","routes/_layout",{"_19":-5,"_20":21,"_22":21,"_23":11,"_24":21},"username","isAskGordonEnabled",true,"isUsingNewTemplate","showMinimalLanding","showHoneypotTrap","routes/_layout.r.$namespace.$reponame",{"_27":28,"_29":-5,"_30":11,"_31":11,"_32":33,"_34":35,"_36":-5,"_37":11,"_38":39,"_88":89,"_108":109,"_156":-5,"_157":11,"_158":21,"_159":11,"_160":-5,"_161":11,"_162":-5,"_163":164,"_165":110,"_166":-7},"canonicalUrl","https://hub.docker.com/r/scrnaseqbenchmark/singler/tags","mcpServer","canSeeDockerfile","canSeeAutobuilds","namespace","scrnaseqbenchmark","reponame","singler","cloudBuildSource","isAutobuildsAvailable","repo",{"_40":41,"_42":43,"_45":46,"_47":48,"_49":11,"_50":51,"_52":53,"_54":55,"_57":35,"_32":33,"_58":59,"_60":44,"_61":62,"_63":62,"_64":65,"_66":-5,"_67":68,"_69":70,"_71":11,"_72":33,"_73":74,"_79":11,"_80":81,"_85":33,"_86":87},"categories",[],"content_types",[44],"image","date_registered","2019-05-16T10:47:45.335733Z","description","","is_private","last_updated","2019-08-02T15:14:55.106666Z","last_modified","2024-10-16T13:48:34.145251Z","media_types",[56],"application/vnd.docker.container.image.v1+json","name","pull_count",532,"repository_type","star_count",1,"status","status_description","active","source","collaborator_count",0,"full_description","# scRNAseq_Benchmark\nBenchmarking classification tools for scRNA-seq data\n\n## How to use\n[snakemake](https://snakemake.readthedocs.io/en/stable/index.html) and\n[singularity](https://www.sylabs.io/docs/) need to be available on your system.\n\nFrom the root of this repository:\n```\nsnakemake \\\n --configfile \\\n --use-singularity\n```\n\nIf your data or output directory is not located under the root of this\nrepository, be sure to tell snakemake to mount the appropriate directories\nin singularity:\n```\nsnakemake \\\n --configfile \\\n --use-singularity \\\n --singularity-args '--bind : --bind :'\n```\n\n#### The config file\n```YML\noutput_dir: \ndatafile: \nlabfile: \ncolumn: \nnumber_of_features: \ngenes: \nhuman: \ntools_to_run: # List of tools to run\n - \n - \n - <...>\n```\n\n##### Tool specific inputs\nSome tools require specific inputs. Add the following to your config file when\none of these tools:\n- Garnett_CV\n ```YML\n Garnett_CV:\n markers: \n ```\n- Garnett_Pretrained\n ```YML\n Garnett_Pretrained:\n classifier: \n ```\n\n\n\n## Included tools/methods\n- kNN50\n- kNN9\n- LDA\n- LDA_rejection (LDA with rejection option)\n- NMC\n- RF\n- SVM\n- SVM (SVM with rejection option)\n- [singleCellNet](https://github.com/pcahan1/singleCellNet)\n- [CHETAH](https://github.com/jdekanter/CHETAH)\n- [scmap](https://github.com/hemberg-lab/scmap)\n - scmapcell\n - scmapcluster\n- [SingleR](https://github.com/dviraran/SingleR)\n- [scID](https://github.com/BatadaLab/scID)\n- [scVI](https://github.com/YosefLab/scVI)\n- [Cell_BLAST](https://github.com/gao-lab/Cell_BLAST)\n- [Garnett](https://cole-trapnell-lab.github.io/garnett/)\n - Garnett_CV (without pretrained classifier)\n - Garnett_Pretrained (with pretrained classifier)\n\n## Adding new tools\nIn order to add a tool to this benchmarking workflow, a rule for this tool\nneeds to be added to the `Snakefile`. This rule should produce as output:\n- a table of predicted label (`/_pred.csv`).\n- a table of true labels (`/_true.csv`).\n- a tables of testing, prediction and/or total time:\n - `//_test_time.csv`\n - `//_training_time.csv`\n - `//_total_time.csv`\n\nThe input to this rule should be:\n- a count table (specified as the `datafile` in the config).\n- a true labels file (specified as the `labfile` in the config).\n\nYou will want to write a wrapper script for the tool you want to\nadd to facilitate this. The `\"{output_dir}/CV_folds.RData\"` input may be\nused to provide your wrapper script with folds for cross_validation.\nIt is recommended to make a docker image containing all dependencies for both\nthe tool and any wrappers for the tool. \nThis wrapper script should also make a selection of the features to be used.\nThis selection should be based on ranking which can be accessed by providing\n`feature ranking` as input to the wrapper script. The number of features to be\nused should be configurable and settable through the 'number_of_features' field\nin the config.\n\nThe following can be used as a template for new rules. Replace everything\nsurrounded by (and including the) `<>` with appropriate values.\n```\nrule SVM:\n input:\n datafile = config[\"datafile\"],\n labfile = config[\"labfile\"],\n folds = \"{output_dir}/CV_folds.RData\",\n ranking = feature_ranking\n output:\n pred = \"{output_dir}//_pred.csv\",\n true = \"{output_dir}//_true.csv\",\n test_time = \"{output_dir}//_test_time.csv\",\n training_time = \"{output_dir}//_training_time.csv\"\n log: \"{output_dir}//.log\"\n params:\n n_features = config.get(\"number_of_features\", 0)\n singularity: \"docker://\"\n shell:\n \" \"\n \"{input.datafile} \"\n \"{input.labfile} \"\n \"{input.folds} \"\n \"{wildcards.output_dir}/ \"\n \"{input.ranking} \"\n \"{params.n_features} \"\n \"&> {log}\"\n```\n","has_starred","hub_user","immutable_tags_settings",{"_75":11,"_76":77},"enabled","rules",[78],".*","is_automated","permissions",{"_82":21,"_83":11,"_84":11},"read","write","admin","user","storage_size",2637175715,"orgData",{"_90":91,"_92":93,"_94":95,"_96":33,"_97":48,"_98":48,"_99":100,"_101":48,"_102":103,"_104":48,"_105":48,"_106":48,"_107":21},"id","53d6bc35d06343c1b0caa2967dd5c7ea","uuid","53d6bc35-d063-43c1-b0ca-a2967dd5c7ea","type","organization","orgname","full_name","location","company","LUMC","profile_url","date_joined","2019-05-07T08:33:55.628431Z","gravatar_url","gravatar_email","badge","is_active","recentTags",[110,146],{"_111":44,"_112":113,"_114":115,"_90":116,"_117":118,"_50":135,"_136":113,"_137":33,"_138":56,"_57":139,"_140":141,"_142":126,"_143":135,"_144":65,"_145":21},"content_type","creator",6267062,"full_size",481290005,55962807,"images",[119],{"_120":121,"_122":123,"_124":48,"_125":126,"_127":128,"_129":130,"_131":48,"_132":-5,"_133":115,"_63":65,"_134":-5},"architecture","amd64","digest","sha256:fbb681cca218d94ac80e9cd82a4563aea4f5038201209b0b557284f20436fa2f","features","last_pulled","2026-09-25T11:27:57.597263511Z","last_pushed","2019-07-31T18:59:15Z","os","linux","os_features","os_version","size","variant","2019-08-02T15:14:54.739875Z","last_updater","last_updater_username","media_type","latest","repository",7127469,"tag_last_pulled","tag_last_pushed","tag_status","v2",{"_111":44,"_112":113,"_114":147,"_90":148,"_117":149,"_50":154,"_136":113,"_137":33,"_138":56,"_57":155,"_140":141,"_142":152,"_143":154,"_144":65,"_145":21},475327392,60734127,[150],{"_120":121,"_122":151,"_124":48,"_125":152,"_127":153,"_129":130,"_131":48,"_132":-5,"_133":147,"_63":65,"_134":-5},"sha256:d6f7b20027e7a692142c9e4d057d4c2fd25964f133e8b61d79be0da3ab997cc6","2026-09-13T21:36:15.615046741Z","2019-07-02T14:15:16Z","2019-07-02T14:15:15.21591Z","pipeline_0.1","sbxKitMetadata","isPotentialSpam","isHubSbxKitsEnabled","showSbxLogoOverride","sbxTrademarkText","displaySecurityMetadata","tagAttestations","tagsHaveAttestations",[],"selectedTag","attestationsUrl","routes/_layout.r.$namespace.$reponame.tags",{"_38":169,"_176":177,"_163":190,"_191":11},{"_40":170,"_42":171,"_45":46,"_47":48,"_49":11,"_50":51,"_52":53,"_54":172,"_57":35,"_32":33,"_58":59,"_60":44,"_61":62,"_63":62,"_64":65,"_66":-5,"_67":68,"_69":70,"_71":11,"_72":33,"_73":173,"_79":11,"_80":175,"_85":33,"_86":87},[],[44],[56],{"_75":11,"_76":174},[78],{"_82":21,"_83":11,"_84":11},"tags",{"_178":179,"_180":-5,"_181":-5,"_182":183},"count",2,"next","previous","results",[184,187],{"_111":44,"_112":113,"_114":115,"_90":116,"_117":185,"_50":135,"_136":113,"_137":33,"_138":56,"_57":139,"_140":141,"_142":126,"_143":135,"_144":65,"_145":21},[186],{"_120":121,"_122":123,"_124":48,"_125":126,"_127":128,"_129":130,"_131":48,"_132":-5,"_133":115,"_63":65,"_134":-5},{"_111":44,"_112":113,"_114":147,"_90":148,"_117":188,"_50":154,"_136":113,"_137":33,"_138":56,"_57":155,"_140":141,"_142":152,"_143":154,"_144":65,"_145":21},[189],{"_120":121,"_122":151,"_124":48,"_125":152,"_127":153,"_129":130,"_131":48,"_132":-5,"_133":147,"_63":65,"_134":-5},[],"canDeleteTags","actionData","errors"]

scrnaseqbenchmark/singler

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