{"id":20837787,"url":"https://github.com/astrazeneca/arrayedcrisprscreener","last_synced_at":"2025-10-06T18:06:51.280Z","repository":{"id":212293834,"uuid":"731125902","full_name":"AstraZeneca/arrayedCRISPRscreener","owner":"AstraZeneca","description":"The goal of arrayedCRISPRscreener is to simulate arrayed CRISPR screening data for the purpose of benchmarking data analysis tools as well as power calculation.","archived":false,"fork":false,"pushed_at":"2023-12-13T12:14:36.000Z","size":232,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":0,"default_branch":"main","last_synced_at":"2025-10-06T18:05:03.117Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":"","language":"R","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"other","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/AstraZeneca.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}},"created_at":"2023-12-13T12:12:22.000Z","updated_at":"2023-12-13T12:23:34.000Z","dependencies_parsed_at":null,"dependency_job_id":"4d591bb6-9932-4db9-aa6b-864269475474","html_url":"https://github.com/AstraZeneca/arrayedCRISPRscreener","commit_stats":null,"previous_names":["astrazeneca/arrayedcrisprscreener"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/AstraZeneca/arrayedCRISPRscreener","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/AstraZeneca%2FarrayedCRISPRscreener","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/AstraZeneca%2FarrayedCRISPRscreener/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/AstraZeneca%2FarrayedCRISPRscreener/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/AstraZeneca%2FarrayedCRISPRscreener/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/AstraZeneca","download_url":"https://codeload.github.com/AstraZeneca/arrayedCRISPRscreener/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/AstraZeneca%2FarrayedCRISPRscreener/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":278655146,"owners_count":26022968,"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":"2025-10-06T02:00:05.630Z","response_time":65,"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":[],"created_at":"2024-11-18T01:08:35.229Z","updated_at":"2025-10-06T18:06:51.243Z","avatar_url":"https://github.com/AstraZeneca.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, include = FALSE}\nknitr::opts_chunk$set(\n  collapse = TRUE,\n  comment = \"#\u003e\",\n  fig.path = \"man/figures/README-\",\n  out.width = \"100%\"\n)\n```\n\n# arrayedCRISPRscreener\n\n\u003c!-- badges: start --\u003e\n\u003c!-- badges: end --\u003e\n\nThe goal of arrayedCRISPRscreener is to simulate arrayed CRISPR screening data for the purpose of benchmarking data analysis tools as well as power calculation.\n\n## Installation\n\nYou can install arrayedCRISPRscreener from [GitHub](https://github.com/AstraZeneca/arrayedCRISPRscreener) with:\n\n```{r}\n# install.packages(\"devtools\")\n# devtools::install(\"arrayedCRISPRscreener\")\n```\n## Quick start\n\n```{r}\nlibrary(arrayedCRISPRscreener)\nlibrary(ggplot2)\n```\n\nThe simulation is designed to run based on a platemap layout. \nThe following are the most basic steps for simulating arrayedCRISPR data using the platemap design. \nPlease note that an example platemap is included in the package. \nTo perform a simulation, users must specify parameters that correspond to various experimental factors. \nFor example, we demonstrate a simulation that only includes the gKO effect, without any additional treatments.\n\n```{r}\n## data frame of platemap layout\nplate_layout \u003c- platemap # example platemap design\nhead(plate_layout)\n\n## Number of randomly selected wells with phenotypic effect due to gKO\nn_hit \u003c- 10\n\n## Number of gKO treatment interacting phenotypic effect with other treatment.\n## In this example, we assume there is no additional treatment in the assay\nn_hit_with_interaction \u003c- 0\n\n## Numeric value desired number of cells per well\ndesired_cells_per_well \u003c- 1000\n\n## Numeric value baseline endpoint value due to gKO\nbase_level \u003c- log(100)\n\n## variation among the negative genes\nsigma_bg0 \u003c- 0.05\n\n## Average gKO effect size as percentage based on the baseline endpoint value\nmu_bg \u003c- 0.2\n\n## Variation of gKO effect\nsigma_bg \u003c- 0.05\n\n## Average effect size of interaction between gKO and other stimulated\n## treatment as percentage based on the baseline endpoint value\nmu_btg \u003c- 0\n\n## Variation of interaction effect\nsigma_btg \u003c- 0\n\n## Coefficient of variation (sig/mu) for the variation between cells within well\ncv_cell \u003c- 0.05\n\n## Measurement error in log scale\nmeasure_error \u003c- 0.3\n\n## Spatial bias can be included in the simulated data. Example input for\n## spatial biased is included in the package as follow,\nhead(wells_with_spatial_bias)\n\n## Data frame specifying the systematic spatial bias\nwells_with_spatial_bias$spatial_bias \u003c-\n  0.2 * wells_with_spatial_bias$spatial_bias\nsummary(wells_with_spatial_bias$spatial_bias)\n\n## Simulation for single plate\nsdata \u003c- sim_single_plate(platemap,\n                          n_hit,\n                          n_hit_with_interaction,\n                          desired_cells_per_well,\n                          base_level,\n                          mu_bg,\n                          sigma_bg,\n                          mu_btg,\n                          sigma_btg,\n                          cv_cell,\n                          measure_error,\n                          wells_with_spatial_bias,\n                          sigma_bg0)\n\nhead(as.data.frame(sdata))\n```\n\nWe can visualized the simulated arrayed CRISPR screen data based on a 384 well-plate in a heatmap. \n\n```{r, example, fig.width = 7} \np \u003c- ggplot(sdata, aes(x = Column, y = Row)) +\n            geom_tile(aes(fill = y), color = \"white\") +\n            scale_y_discrete(limits = rev(unique(sdata$Row))) +\n            scale_fill_continuous(type = \"viridis\") +\n            labs(fill = \"endpoint.simulated\") + theme_bw()\n\nprint(p)\n```\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fastrazeneca%2Farrayedcrisprscreener","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fastrazeneca%2Farrayedcrisprscreener","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fastrazeneca%2Farrayedcrisprscreener/lists"}