{"Package":"valr","Type":"Package","Title":"Genome Interval Arithmetic in R","Version":"0.5.0","Authors@R":"c(\nperson('Jay', 'Hesselberth', role = c('aut', 'cre'),\nemail = 'jay.hesselberth@gmail.com',\ncomment = c(ORCID = '0000-0002-6299-179X')),\nperson('Kent', 'Riemondy', role = c('aut'),\nemail = 'kent.riemondy@ucdenver.edu',\ncomment = c(ORCID = '0000-0003-0750-1273'))\n)","Description":"Read and manipulate genome intervals and signals. Provides\nfunctionality similar to command-line tool suites within R,\nenabling interactive analysis and visualization of genome-scale data.","License":"MIT + file LICENSE","Depends":"R (>= 3.1.2)","Imports":"dplyr (>= 0.7.0), rlang, readr, stringr, tibble (>= 1.4.2),\nbroom, ggplot2","SystemRequirements":"C++11","LinkingTo":"Rcpp (>= 1.0.0),","Suggests":"knitr, rmarkdown, testthat, microbenchmark, covr, curl,\nRMySQL, purrr, tidyr, devtools, DT, cowplot, dbplyr,\nGenomicRanges, IRanges, S4Vectors,","VignetteBuilder":"knitr","RoxygenNote":"6.1.1","URL":"http://github.com/rnabioco/valr, http://rnabioco.github.io/valr","BugReports":"https://github.com/rnabioco/valr/issues","Encoding":"UTF-8","NeedsCompilation":"yes","Packaged":"2019-01-03 08:38:10 UTC; jayhesselberth","Author":"Jay Hesselberth [aut, cre] (),\nKent Riemondy [aut] ()","Maintainer":"Jay Hesselberth ","Repository":"CRAN","Date/Publication":"2019-01-03 16:20:04 UTC","repoType":"cran","tarballUrl":"ftp://cran.r-project.org/pub/R/src/contrib/valr_0.5.0.tar.gz","jsonAuthors":[{"name":"Jay Hesselberth","email":"jay.hesselberth@gmail.com","maintainer":true},{"name":"Kent Riemondy","email":"kent.riemondy@ucdenver.edu","maintainer":false}],"readme":"\n# valr

\n\n[![Build\nStatus](https://travis-ci.org/rnabioco/valr.svg?branch=master)](https://travis-ci.org/rnabioco/valr)\n[![AppVeyor Build\nStatus](https://ci.appveyor.com/api/projects/status/github/rnabioco/valr?branch=master&svg=true)](https://ci.appveyor.com/project/jayhesselberth/valr)\n[![Coverage\nStatus](https://img.shields.io/codecov/c/github/rnabioco/valr/master.svg)](https://codecov.io/github/rnabioco/valr?branch=master)\n[![](https://www.r-pkg.org/badges/version/valr)](https://CRAN.R-project.org/package=valr)\n[![](https://cranlogs.r-pkg.org/badges/valr?color=FFD700)](https://www.r-pkg.org/pkg/valr)\n[![DOI](https://zenodo.org/badge/49370633.svg)](https://zenodo.org/badge/latestdoi/49370633)\n\nThe valr package provides tools to read and manipulate genome intervals\nand signals, similar to the\n[BEDtools](http://bedtools.readthedocs.io/en/latest/) suite. valr\nenables analysis in the R/RStudio environment, leveraging modern R tools\nin the [tidyverse](http://tidyverse.org) for a terse, expressive syntax.\nCompute-intensive algorithms are implemented in\n[Rcpp](http://www.rcpp.org)/C++, and many methods take advantage of the\nspeed and grouping capability provided by\n[dplyr](http://dplyr.tidyverse.org). See `vignette(valr)` for more\ndetails.\n\n## Installation\n\nThe latest stable version can be installed from CRAN:\n\n``` r\ninstall.packages('valr')\n```\n\nThe latest development version can be installed from github:\n\n``` r\n# install.packages(\"devtools\")\ndevtools::install_github('rnabioco/valr')\n```\n\n## valr Example\n\nFunctions in valr have similar names to their BEDtools counterparts, and\nso will be familiar to users coming from the BEDtools suite. Unlike\nother tools that wrap BEDtools and write temporary files to disk, valr\ntools run natively in memory. Similar to\n[pybedtools](https://daler.github.io/pybedtools/#why-pybedtools), valr\nhas a terse syntax:\n\n``` r\nlibrary(valr)\nlibrary(dplyr)\n\nsnps <- read_bed(valr_example('hg19.snps147.chr22.bed.gz'), n_fields = 6)\ngenes <- read_bed(valr_example('genes.hg19.chr22.bed.gz'), n_fields = 6)\n\n# find snps in intergenic regions\nintergenic <- bed_subtract(snps, genes)\n# find distance from intergenic snps to nearest gene\nnearby <- bed_closest(intergenic, genes)\n\nnearby %>%\n select(starts_with('name'), .overlap, .dist) %>%\n filter(abs(.dist) < 5000)\n#> # A tibble: 1,047 x 4\n#> name.x name.y .overlap .dist\n#> \n#> 1 rs530458610 P704P 0 2579\n#> 2 rs2261631 P704P 0 -268\n#> 3 rs570770556 POTEH 0 -913\n#> 4 rs538163832 POTEH 0 -953\n#> 5 rs190224195 POTEH 0 -1399\n#> 6 rs2379966 DQ571479 0 4750\n#> 7 rs142687051 DQ571479 0 3558\n#> 8 rs528403095 DQ571479 0 3309\n#> 9 rs555126291 DQ571479 0 2745\n#> 10 rs5747567 DQ571479 0 -1778\n#> # ... with 1,037 more rows\n```","jobInfo":{"package":"valr","version":"0.5.0","parsingStatus":"success","parserVersion":1,"parsedAt":"2020-05-04T20:30:39+0000"}}

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