{"id":21547967,"url":"https://github.com/illumina/happyr","last_synced_at":"2025-08-07T16:15:48.291Z","repository":{"id":71076018,"uuid":"100359406","full_name":"Illumina/happyR","owner":"Illumina","description":"R tools to interact with hap.py 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github_document\n---\n\n```{r, echo = FALSE}\nknitr::opts_chunk$set(\n  collapse = TRUE,\n  comment = \"#\u003e\",\n  fig.path = \"examples/README-\",\n  fig.height = 3.5,\n  fig.width = 5,\n  fig.align = \"center\"\n)\n```\n\n\n# happyR\n\n[![Build Status](https://travis-ci.org/Illumina/happyR.svg?branch=master)](https://travis-ci.org/Illumina/happyR)\n[![codecov](https://codecov.io/gh/Illumina/happyR/branch/master/graph/badge.svg)](https://codecov.io/gh/Illumina/happyR)\n\nTools to help analyse your [hap.py](https://github.com/Illumina/hap.py) results in R.\nSee the [documentation](https://illumina.github.io/happyR) for usage and examples.\n\n## Install\n\n```{r install, eval=FALSE}\ndevtools::install_github(\"Illumina/happyR\")\n```\n\n## Demo\n\nThis example walks through a comparison of samples prepared using PCR-Free versus \nNano library preps with 2 replicates per group.\n\n```{r usage, message=FALSE, warning=FALSE}\nlibrary(happyR)\nlibrary(tidyverse, quietly = TRUE)\n\n# groups are defined either by a CSV or data.frame with three \n# required columns: a label for each group (group_id), a unique\n# label per replicate (replicate_id) and a path to the respective\n# pre-computed hap.py output (happy_prefix)\nextdata_dir \u003c- system.file(\"extdata\", package = \"happyR\")\n# these extdata files are supplied with the package\nsamplesheet \u003c- tibble::tribble(\n  ~group_id,  ~replicate_id, ~happy_prefix,\n  \"PCR-Free\", \"NA12878-I30\", paste(extdata_dir, \"NA12878-I30_S1\", sep = \"/\"),\n  \"PCR-Free\", \"NA12878-I33\", paste(extdata_dir, \"NA12878-I33_S1\", sep = \"/\"),\n  \"Nano\",     \"NA12878-R1\",  paste(extdata_dir, \"NA12878-R1_S1\", sep = \"/\"),\n  \"Nano\",     \"NA12878-R2\",  paste(extdata_dir, \"NA12878-R2_S1\", sep = \"/\")\n)\n\n# here the above table is used to read hap.py output files from disk \n# and attach the group + replicate metadata\nhap_samplesheet \u003c- read_samplesheet_(samplesheet)\n\n# extract summary PASS performance for each replicate and plot\nsummary \u003c- extract_results(hap_samplesheet$results, table = \"summary\") %\u003e% \n  inner_join(samplesheet, by = \"happy_prefix\") %\u003e% \n  filter(Filter == \"PASS\")\n\nggplot(data = summary, aes(x = METRIC.Recall, y = METRIC.Precision, color = group_id, shape = Type)) +\n  geom_point() + theme_minimal() + \n  xlim(NA, 1) + ylim(NA, 1) +\n  scale_color_brewer(palette = \"Set2\") +\n  labs(x = \"Recall\", y = \"Precision\", color = \"Prep\") +\n  ggtitle(\"PCR-Free vs. Nano variant calling\",\n          \"PCR treatment reduces indel calling performance\")  \n```\n\n## System requirements\n\nOriginally developed for R v3.4.0. [Tests](https://travis-ci.org/Illumina/happyR) are run using the most recent available R versions (incl. devel) on Ubuntu (Trusty) and OS X (El Capitan) platforms. happyR has not been tested on Windows. Dependencies are listed in [DESCRIPTION](DESCRIPTION). \n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fillumina%2Fhappyr","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fillumina%2Fhappyr","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fillumina%2Fhappyr/lists"}