{"Type":"Package","Package":"umiAnalyzer","Title":"Tools for Analyzing Sequencing Data with Unique Molecular\nIdentifiers","Version":"1.0.0","Date":"2021-11-23","Authors@R":"c(\nperson(\"Stefan\", \"Filges\", , \"stefan.filges@gu.se\", role = c(\"aut\", \"cre\"),\ncomment = c(ORCID = \"0000-0002-5994-6699\")),\nperson(\"Gustav\", \"Johansson\", , \"gustav.johansson@gu.se\", role = \"ctb\")\n)","Maintainer":"Stefan Filges ","Description":"Tools for analyzing sequencing data containing unique\nmolecular identifiers generated by 'UMIErrorCorrect'\n().","License":"GPL-3","URL":"https://github.com/sfilges/umiAnalyzer","BugReports":"https://github.com/sfilges/umiAnalyzer/issues","Depends":"R (>= 4.1.0)","Imports":"BiocManager, dplyr (>= 0.7.5), DT (>= 0.19), forcats (>=\n0.5.0), ggplot2 (>= 2.2.1), graphics, grDevices, gridExtra (>=\n2.3), magrittr (>= 1.5), methods, pheatmap (>= 1.0.12), plotly\n(>= 4.9.2.1), readr (>= 1.1.1), Rsamtools (>= 1.32.3), scales\n(>= 1.1.0), shiny (>= 1.7.1), shinydashboard (>= 0.7.2),\nshinyFiles (>= 0.9.0), shinyWidgets (>= 0.6.2), stats, stringr\n(>= 1.4.0), tibble (>= 1.4.2), tidyr (>= 0.8.1), utils, viridis\n(>= 0.5.1)","Suggests":"knitr (>= 1.27), rmarkdown (>= 2.1)","VignetteBuilder":"knitr","Config/testthat/edition":"3","Encoding":"UTF-8","Language":"en-US","RoxygenNote":"7.1.2","NeedsCompilation":"no","Packaged":"2021-11-24 21:59:58 UTC; stefa","Author":"Stefan Filges [aut, cre] (),\nGustav Johansson [ctb]","Repository":"CRAN","Date/Publication":"2021-11-25 08:40:02 UTC","repoType":"cran","tarballUrl":"ftp://cran.r-project.org/pub/R/src/contrib/umiAnalyzer_1.0.0.tar.gz","jsonAuthors":[{"name":"Stefan Filges","email":"stefan.filges@gu.se","maintainer":true},{"name":"Gustav Johansson","email":"gustav.johansson@gu.se","maintainer":false}],"readme":"# umiAnalyzer 1.0.0\n\nTools for analyzing sequencing data containing unique\nmolecular identifiers generated by UMIErrorCorrect \n(). The package \nallows merging of multiple samples into a single UMIexperiment object which \ncan be easily manipulated using build-in functions to generate tabular and\ngraphical output. The package includes a shiny app with a graphical\nuser interface for data exploration and generating plots and report\ndocuments.\n\nThis README serves as a basic introduction, for more detailed information and examples read\nthe wiki pages on GitHub () or\nthe R vignette using:\n\n```r\nbrowseVignettes('umiAnalyzer')\n```\n\nFor a version history/changelog, please see the [NEWS](https://github.com/sfilges/umiAnalyzer/blob/master/NEWS.md) file.\n\nRequirements\n------------\n\n- R (>= 4.1.0), which can be downloaded and installed via The Comprehensive R Archive Network [CRAN](https://cran.r-project.org/).\n- Installation from R using install_github requires the devtools package\n\nInstallation \n------------\n\nInstall the current stable version from CRAN or GitHub or the latest\ndevelopment version from GitHub.\n\n```r\n# from CRAN (not supported yet)\n#install.packages('umiAnalyzer')\n\n# Current stable version from github using the devtools package:\ndevtools::install_github('sfilges/umiAnalyzer')\n\n# Latest development version from github:\ndevtools::install_github('sfilges/umiAnalyzer', ref = 'devel')\n```\n\nRunning the visualization app\n------------\n\nRun the following command in the R console to start the app:\n\n```r\numiAnalyzer::runUmiVisualizer()\n```\n\n# Using the R package in your own scripts\n\nHow to make build your own UMIexperiment object\n---------------------\n\nDefine a variable containing the path to the directory with all the UMIErrorCorrect \noutput folders belonging to your experiment. umiAnalyzer comes with raw test data \ngenerated with UMIErrorCorrect that you can import if you don't have any of your own.\n\nCall the createUmiExperiment to create your UMIexperiment object.\n\nThe UMIexperiment object always maintains your raw data, however you can create \nas many filters as you like, which will be saved as separate objects to access. \nYou can filter the consensus table of UMIexperiment object with filterUMIobject. \nThe only mandatory arguments are the object to be filtered and a user defined name. \nYou can use that name to retrieve a filtered table using getFilter. \n\n```r\nlibrary(umiAnalyzer)\n\nmain <- system.file('extdata', package = 'umiAnalyzer')\n\nsimsen <- createUmiExperiment(main)\n\nreads <- parseBamFiles(main, consDepth = 10)\n\nplotFamilyHistogram(reads)\n\nsimsen <- generateQCplots(simsen)\n\nsimsen <- filterUmiObject(simsen)\n\nmyfilter <- getFilteredData(simsen)\nmyfilter\n\nsimsen <- generateAmpliconPlots(simsen)\n```","jobInfo":{"package":"umiAnalyzer","version":"1.0.0","parsingStatus":"success","parserVersion":1,"parsedAt":"2021-11-25T10:30:13+0000"}}

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