{"id":32554172,"url":"https://github.com/noriakis/scstruc","last_synced_at":"2025-10-28T21:57:40.989Z","repository":{"id":205212335,"uuid":"713660071","full_name":"noriakis/scstruc","owner":"noriakis","description":"Evaluation of gene regulatory network based on Bayesian network structure in single-cell transcriptomics","archived":false,"fork":false,"pushed_at":"2025-10-27T01:16:56.000Z","size":7627,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-10-27T03:15:00.765Z","etag":null,"topics":["bayesian-network","single-cell","structure-learning"],"latest_commit_sha":null,"homepage":"","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/noriakis.png","metadata":{"files":{"readme":"README.Rmd","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","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":"2023-11-03T01:18:52.000Z","updated_at":"2025-10-27T01:16:59.000Z","dependencies_parsed_at":null,"dependency_job_id":"f0477ad7-eaee-4acf-815a-963290fea0d0","html_url":"https://github.com/noriakis/scstruc","commit_stats":null,"previous_names":["noriakis/stfuncs","noriakis/scstruc"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/noriakis/scstruc","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/noriakis%2Fscstruc","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/noriakis%2Fscstruc/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/noriakis%2Fscstruc/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/noriakis%2Fscstruc/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/noriakis","download_url":"https://codeload.github.com/noriakis/scstruc/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/noriakis%2Fscstruc/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":281520715,"owners_count":26515681,"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":"2025-10-28T02:00:06.022Z","response_time":60,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","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":["bayesian-network","single-cell","structure-learning"],"created_at":"2025-10-28T21:57:36.902Z","updated_at":"2025-10-28T21:57:40.983Z","avatar_url":"https://github.com/noriakis.png","language":"R","funding_links":[],"categories":[],"sub_categories":[],"readme":"---\noutput: github_document\n---\n\n\u003c!-- README.md is generated from README.Rmd. Please edit that file --\u003e\n\n```{r setup, include = FALSE}\nknitr::opts_chunk$set(\n  collapse = TRUE,\n  comment = \"#\u003e\",\n  fig.path = \"man/figures/README-\",\n  fig.dev = \"grDevices::png\",\n  dpi = 300L,\n  dev.args = list(),\n  fig.ext = \"png\",\n  fig.height=8,\n  fig.width=12,\n  fig.retina = 2L,\n  fig.align = \"center\"\n)\n```\n\n# scstruc\n\nThe package for analysing the gene regulatory network based on Bayesian network structure of single-cell transcriptomics data. The function works primarily with `SingleCellExperiment`. Multiple algorithms tailored for single-cell transcriptomics data are prepared. The inferred networks are validated based on the causal relationships between genes.\n\n\u003c!-- badges: start --\u003e\n[![R-CMD-check](https://github.com/noriakis/scstruc/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/noriakis/scstruc/actions/workflows/R-CMD-check.yaml)\n\u003c!-- badges: end --\u003e\n\n\n## Installation\n\nUsing `devtools`:\n\n```{r, eval=FALSE}\ndevtools::install_github(\"noriakis/scstruc\")\n```\n\n## Documentation\n\nThe documentation is available [here](https://noriakis.github.io/software/scstruc).\n\n## Examples\n\nBased on `SingleCellExperiment`, the network is inferred and plotted.\n\n```{r message=FALSE, warning=FALSE, fig.width=12, fig.height=12}\nlibrary(scran)\nlibrary(scstruc)\nlibrary(ggraph)\nlibrary(bnlearn)\nsce \u003c- mockSCE()\nsce \u003c- logNormCounts(sce)\nincluded_genes \u003c- sample(row.names(sce), 100)\ngs \u003c- scstruc(sce, included_genes, changeSymbol=FALSE)\nplotNet(gs$net, gs$data, showText=FALSE)\n```\n\nUsing bootstrapping, the averaged network is obtained. This time, `L1MB` algorithm with the selection of neighbors based on BIC is used.\n\n```{r message=FALSE, warning=FALSE, fig.width=8, fig.height=8}\nlibrary(glmnet)\ngs2 \u003c- scstruc(sce, included_genes, algorithm=\"glmnet_BIC\", boot=TRUE,\n               changeSymbol=FALSE, R=20)\nplotAVN(gs2$net, sizeRange=c(1,3))\n```\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fnoriakis%2Fscstruc","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fnoriakis%2Fscstruc","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fnoriakis%2Fscstruc/lists"}