{"Package":"tidygate","Type":"Package","Title":"Interactively Gate Points","Version":"1.0.14","Authors@R":"c(person(given = \"Stefano\",\nfamily = \"Mangiola\",\nrole = c(\"aut\", \"cre\"),\nemail = \"mangiolastefano@gmail.com\"),\nperson(given = \"Wajid\",\nfamily = \"Jawaid\",\nrole = \"ctb\"),\nperson(given = \"William\",\nfamily = \"Hutchison\",\nrole = \"aut\",\nemail = \"hutchison.w@wehi.edu.au\",\ncomment = c(ORCID = \"0009-0001-6242-4269\"))\n)","Maintainer":"Stefano Mangiola ","Description":"Interactively gate points on a scatter plot. Interactively drawn gates are\nrecorded and can be applied programmatically to reproduce results exactly. Programmatic gating is\nbased on the package gatepoints by Wajid Jawaid (who is also an author of this package).","License":"GPL-3","Encoding":"UTF-8","LazyData":"true","RoxygenNote":"7.3.1","Depends":"R (>= 3.6.0)","Imports":"utils, graphics, lifecycle, scales, magrittr, tibble, dplyr,\npurrr, rlang, tidyr, viridis, grDevices, RColorBrewer, stringr,\nshiny, plotly, ggplot2","RdMacros":"lifecycle","Suggests":"testthat, markdown, knitr, readr","VignetteBuilder":"knitr","Biarch":"true","biocViews":"AssayDomain, Infrastructure","URL":"https://github.com/stemangiola/tidygate","BugReports":"https://github.com/stemangiola/tidygate/issues","NeedsCompilation":"no","Packaged":"2024-09-17 19:33:12 UTC; a1234450","Author":"Stefano Mangiola [aut, cre],\nWajid Jawaid [ctb],\nWilliam Hutchison [aut] ()","Repository":"CRAN","Date/Publication":"2024-09-17 19:50:02 UTC","repoType":"cran","tarballUrl":"ftp://cran.r-project.org/pub/R/src/contrib/tidygate_1.0.14.tar.gz","jsonAuthors":[{"name":"Stefano Mangiola","email":"mangiolastefano@gmail.com","maintainer":true},{"name":"Wajid Jawaid","email":null,"maintainer":false},{"name":"William Hutchison","email":"hutchison.w@wehi.edu.au","maintainer":false}],"readme":"tidygate: add gate information to your tibble\n================\n\n\n\n\n[![Lifecycle:maturing](https://img.shields.io/badge/lifecycle-maturing-blue.svg)](https://lifecycle.r-lib.org/articles/stages.html)\n\n\n## Introduction\n\ntidygate allows you to interactively gate points on a scatter plot.\nInteractively drawn gates are recorded and can be applied\nprogrammatically to reproduce results exactly. Programmatic gating is\nbased on the package [gatepoints](https://github.com/wjawaid/gatepoints)\nby Wajid Jawaid.\n\nFor more tidy data analysis:\n\n- [tidyomics](https://github.com/tidyomics) - A software ecosystem for\n tidy analysis of omic data.\n- [tidyHeatmap](https://github.com/stemangiola/tidyHeatmap) - Produce\n heatmaps with tidy principles.\n\n## Installation\n\n``` r\n# From Github\ndevtools::install_github(\"stemangiola/tidygate\")\n\n# From CRAN\ninstall.package(\"tidygate\")\n```\n\n## Example usage\n\ntidygate provides a single user-facing function: `gate`. The following\nexamples make use of this function, four packages from the tidyverse and\nthe inbuilt `mtcars` dataset.\n\n``` r\nlibrary(dplyr)\nlibrary(ggplot2)\nlibrary(stringr)\nlibrary(readr)\nlibrary(tidygate)\n\nmtcars |>\n head()\n```\n\n ## mpg cyl disp hp drat wt qsec vs am gear carb\n ## Mazda RX4 21.0 6 160 110 3.90 2.620 16.46 0 1 4 4\n ## Mazda RX4 Wag 21.0 6 160 110 3.90 2.875 17.02 0 1 4 4\n ## Datsun 710 22.8 4 108 93 3.85 2.320 18.61 1 1 4 1\n ## Hornet 4 Drive 21.4 6 258 110 3.08 3.215 19.44 1 0 3 1\n ## Hornet Sportabout 18.7 8 360 175 3.15 3.440 17.02 0 0 3 2\n ## Valiant 18.1 6 225 105 2.76 3.460 20.22 1 0 3 1\n\nBy default, `gate` creates an interactive scatter plot based on\nuser-defined X and Y coordinates. Colour, shape, size and alpha can be\ndefined as constant values, or can be controlled by values in a\nspecified column.\n\nOnce the plot has been created, multiple gates can be drawn with the\nmouse. When you have finished, click continue. `gate` will then return a\nvector of strings, recording the gates each X and Y coordinate pair is\nwithin.\n\n``` r\nmtcars_gated <- \n mtcars |>\n mutate(gated = gate(x = mpg, y = wt, colour = disp))\n```\n\n![](man/figures/demo_gate.gif)\n\nTo select points which appear within any gates, filter for non-NA\nvalues. To select points which appear within a specific gate, string\npattern matching can be used.\n\n``` r\n# Select points within any gate\nmtcars_gated |> \n filter(!is.na(gated))\n```\n\n ## mpg cyl disp hp drat wt qsec vs am gear carb gated\n ## Mazda RX4 21.0 6 160.0 110 3.90 2.620 16.46 0 1 4 4 NA\n ## Mazda RX4 Wag 21.0 6 160.0 110 3.90 2.875 17.02 0 1 4 4 NA\n ## Datsun 710 22.8 4 108.0 93 3.85 2.320 18.61 1 1 4 1 NA\n ## Hornet 4 Drive 21.4 6 258.0 110 3.08 3.215 19.44 1 0 3 1 2\n ## Hornet Sportabout 18.7 8 360.0 175 3.15 3.440 17.02 0 0 3 2 1,2\n ## Valiant 18.1 6 225.0 105 2.76 3.460 20.22 1 0 3 1 1,2\n ## Duster 360 14.3 8 360.0 245 3.21 3.570 15.84 0 0 3 4 1\n ## Merc 240D 24.4 4 146.7 62 3.69 3.190 20.00 1 0 4 2 2\n ## Merc 230 22.8 4 140.8 95 3.92 3.150 22.90 1 0 4 2 2\n ## Merc 280 19.2 6 167.6 123 3.92 3.440 18.30 1 0 4 4 1,2\n ## Merc 280C 17.8 6 167.6 123 3.92 3.440 18.90 1 0 4 4 1,2\n ## Merc 450SE 16.4 8 275.8 180 3.07 4.070 17.40 0 0 3 3 1\n ## Merc 450SL 17.3 8 275.8 180 3.07 3.730 17.60 0 0 3 3 1,2\n ## Merc 450SLC 15.2 8 275.8 180 3.07 3.780 18.00 0 0 3 3 1\n ## Cadillac Fleetwood 10.4 8 472.0 205 2.93 5.250 17.98 0 0 3 4 NA\n ## Lincoln Continental 10.4 8 460.0 215 3.00 5.424 17.82 0 0 3 4 NA\n ## Chrysler Imperial 14.7 8 440.0 230 3.23 5.345 17.42 0 0 3 4 NA\n ## Fiat 128 32.4 4 78.7 66 4.08 2.200 19.47 1 1 4 1 NA\n ## Honda Civic 30.4 4 75.7 52 4.93 1.615 18.52 1 1 4 2 NA\n ## Toyota Corolla 33.9 4 71.1 65 4.22 1.835 19.90 1 1 4 1 NA\n ## Toyota Corona 21.5 4 120.1 97 3.70 2.465 20.01 1 0 3 1 NA\n ## Dodge Challenger 15.5 8 318.0 150 2.76 3.520 16.87 0 0 3 2 1\n ## AMC Javelin 15.2 8 304.0 150 3.15 3.435 17.30 0 0 3 2 1\n ## Camaro Z28 13.3 8 350.0 245 3.73 3.840 15.41 0 0 3 4 1\n ## Pontiac Firebird 19.2 8 400.0 175 3.08 3.845 17.05 0 0 3 2 1,2\n ## Fiat X1-9 27.3 4 79.0 66 4.08 1.935 18.90 1 1 4 1 NA\n ## Porsche 914-2 26.0 4 120.3 91 4.43 2.140 16.70 0 1 5 2 NA\n ## Lotus Europa 30.4 4 95.1 113 3.77 1.513 16.90 1 1 5 2 NA\n ## Ford Pantera L 15.8 8 351.0 264 4.22 3.170 14.50 0 1 5 4 1\n ## Ferrari Dino 19.7 6 145.0 175 3.62 2.770 15.50 0 1 5 6 NA\n ## Maserati Bora 15.0 8 301.0 335 3.54 3.570 14.60 0 1 5 8 1\n ## Volvo 142E 21.4 4 121.0 109 4.11 2.780 18.60 1 1 4 2 NA\n\n``` r\n# Select points within gate 2\nmtcars_gated |>\n filter(str_detect(gated, \"2\"))\n```\n\n ## mpg cyl disp hp drat wt qsec vs am gear carb gated\n ## Hornet 4 Drive 21.4 6 258.0 110 3.08 3.215 19.44 1 0 3 1 2\n ## Hornet Sportabout 18.7 8 360.0 175 3.15 3.440 17.02 0 0 3 2 1,2\n ## Valiant 18.1 6 225.0 105 2.76 3.460 20.22 1 0 3 1 1,2\n ## Merc 240D 24.4 4 146.7 62 3.69 3.190 20.00 1 0 4 2 2\n ## Merc 230 22.8 4 140.8 95 3.92 3.150 22.90 1 0 4 2 2\n ## Merc 280 19.2 6 167.6 123 3.92 3.440 18.30 1 0 4 4 1,2\n ## Merc 280C 17.8 6 167.6 123 3.92 3.440 18.90 1 0 4 4 1,2\n ## Merc 450SL 17.3 8 275.8 180 3.07 3.730 17.60 0 0 3 3 1,2\n ## Pontiac Firebird 19.2 8 400.0 175 3.08 3.845 17.05 0 0 3 2 1,2\n\nDetails of the interactively drawn gates are saved to\n`tidygate_env$gates`. This variable is overwritten each time interactive\ngates are drawn, so save it right away if you would like to access it\nlater.\n\n``` r\n# Inspect previously drawn gates\ntidygate_env$gates |>\n head()\n```\n\n ## # A tibble: 6 × 3\n ## x y .gate\n ## \n ## 1 20.4 3.60 1\n ## 2 20.3 3.86 1\n ## 3 18.7 4.26 1\n ## 4 16.0 4.34 1\n ## 5 12.1 4.34 1\n ## 6 11.7 4.26 1\n\n``` r\n# Save if needed\ntidygate_env$gates |>\n write_rds(\"important_gates.rds\")\n```\n\nIf previously drawn gates are supplied to the `programmatic_gates`\nargument, points will be gated programmatically. This feature allows the\nreproduction of previously drawn interactive gates.\n\n``` r\nimportant_gates <-\n read_rds(\"important_gates.rds\")\n\nmtcars |>\n mutate(gated = gate(x = mpg, y = wt, programmatic_gates = important_gates)) |>\n filter(!is.na(gated))\n```\n\n ## mpg cyl disp hp drat wt qsec vs am gear carb gated\n ## Hornet 4 Drive 21.4 6 258.0 110 3.08 3.215 19.44 1 0 3 1 2\n ## Hornet Sportabout 18.7 8 360.0 175 3.15 3.440 17.02 0 0 3 2 1,2\n ## Valiant 18.1 6 225.0 105 2.76 3.460 20.22 1 0 3 1 1,2\n ## Duster 360 14.3 8 360.0 245 3.21 3.570 15.84 0 0 3 4 1\n ## Merc 240D 24.4 4 146.7 62 3.69 3.190 20.00 1 0 4 2 2\n ## Merc 230 22.8 4 140.8 95 3.92 3.150 22.90 1 0 4 2 2\n ## Merc 280 19.2 6 167.6 123 3.92 3.440 18.30 1 0 4 4 1,2\n ## Merc 280C 17.8 6 167.6 123 3.92 3.440 18.90 1 0 4 4 1,2\n ## Merc 450SE 16.4 8 275.8 180 3.07 4.070 17.40 0 0 3 3 1\n ## Merc 450SL 17.3 8 275.8 180 3.07 3.730 17.60 0 0 3 3 1,2\n ## Merc 450SLC 15.2 8 275.8 180 3.07 3.780 18.00 0 0 3 3 1\n ## Dodge Challenger 15.5 8 318.0 150 2.76 3.520 16.87 0 0 3 2 1\n ## AMC Javelin 15.2 8 304.0 150 3.15 3.435 17.30 0 0 3 2 1\n ## Camaro Z28 13.3 8 350.0 245 3.73 3.840 15.41 0 0 3 4 1\n ## Pontiac Firebird 19.2 8 400.0 175 3.08 3.845 17.05 0 0 3 2 1,2\n ## Ford Pantera L 15.8 8 351.0 264 4.22 3.170 14.50 0 1 5 4 1\n ## Maserati Bora 15.0 8 301.0 335 3.54 3.570 14.60 0 1 5 8 1","jobInfo":{"package":"tidygate","version":"1.0.14","parsingStatus":"success","parserVersion":2,"parsedAt":"2024-09-17T22:30:11+0000"}}

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