{"id":23757654,"url":"https://github.com/broadinstitute/funpipe","last_synced_at":"2025-08-09T23:06:55.396Z","repository":{"id":57432669,"uuid":"123972975","full_name":"broadinstitute/funpipe","owner":"broadinstitute","description":"A python3 library for building best practice fungal genomic analysis pipeline","archived":false,"fork":false,"pushed_at":"2024-11-08T11:38:27.000Z","size":3504,"stargazers_count":6,"open_issues_count":37,"forks_count":4,"subscribers_count":4,"default_branch":"main","last_synced_at":"2025-07-11T13:36:27.645Z","etag":null,"topics":["bioinformatics-pipeline","fungal","genetics","genomics","infectious-disease","python-library","python3"],"latest_commit_sha":null,"homepage":"","language":"HTML","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/broadinstitute.png","metadata":{"files":{"readme":"README.md","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}},"created_at":"2018-03-05T20:13:19.000Z","updated_at":"2024-08-25T02:42:33.000Z","dependencies_parsed_at":"2024-01-08T19:57:54.221Z","dependency_job_id":"7a20cd3d-fb0b-4afe-b6a9-f28f951593c7","html_url":"https://github.com/broadinstitute/funpipe","commit_stats":{"total_commits":222,"total_committers":5,"mean_commits":44.4,"dds":"0.027027027027026973","last_synced_commit":"c48211fb85114df60aa378ed455680d58887f9b6"},"previous_names":[],"tags_count":1,"template":false,"template_full_name":null,"purl":"pkg:github/broadinstitute/funpipe","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/broadinstitute%2Ffunpipe","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/broadinstitute%2Ffunpipe/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/broadinstitute%2Ffunpipe/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/broadinstitute%2Ffunpipe/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/broadinstitute","download_url":"https://codeload.github.com/broadinstitute/funpipe/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/broadinstitute%2Ffunpipe/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":269649848,"owners_count":24453541,"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":"2025-08-09T02:00:10.424Z","response_time":111,"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":["bioinformatics-pipeline","fungal","genetics","genomics","infectious-disease","python-library","python3"],"created_at":"2024-12-31T19:49:51.718Z","updated_at":"2025-08-09T23:06:55.352Z","avatar_url":"https://github.com/broadinstitute.png","language":"HTML","funding_links":[],"categories":[],"sub_categories":[],"readme":"# FunPipe: a python library for building best practice fungal genomic analysis pipeline\n\n`FunPipe` is a python library designed for efficient implementation of bioinformatic tools and pipelines for fungal genomic analysis. It contains wrapper functions to popular tools, customized functions for specific analyses tasks, and command line tools developed using those functions. This package is developing to facilitate fungal genomics, but many of the functions are generally applicable to other genomic analysis as well.\n\n## Synposis\n* [funpipe](./funpipe): a directory that contains python library\n* [scripts](./scripts): tools and established pipelines, doc [here](#DOC)\n* [tests](./tests): unit tests\n* [docs](./docs): API documentation\n* `README.md`: this file\n* `setup.py`: pip setup script\n* `conda_env.yml`: spec file for setting up conda environment\n* `Dockerfile`: docker images\n* `requirements.txt`: sphinx requirement file (not requirement for this package)\n* `LICENSE`: MIT license\n\n## Installation\n### **\u003ca name='CONDA'\u003eInstall with Conda\u003c/a\u003e**\nIt is recommended to install funpipe via `conda`, as it automatically setup all required bioinformatic tools. This is very useful on servers or\nclusters without root privilage. Make sure `conda` is available in your environment via `which conda`. If `conda` is not available in your system, install Python3.7 version of it [here](https://conda.io/miniconda.html).\n\nHTTP errors sometimes occur when creating the conda environment, simply rerun the `conda env create -f conda_env.yml` to continue creating the environment.\n\n```sh\n# clone this repo\ngit clone git@github.com:broadinstitute/funpipe.git\n\n# setup conda environment\ncd funpipe\n\nconda env create -f conda_env.yml # this will take about 10 min\nconda list  # verify new environment was installed correctly\n\n# activate funpipe environment\nconda activate funpipe\n\n# the latest stable version of funpipe is available in this environment\n# to use the latest funpipe version, do\npip install .\n\n# deactivate the environment when done\nconda deactivate\n\n\n# to complete remove the environment\nconda remove -n funpipe --all\n```\n\nNote:\n* `diamond=0.9.22` uses boost library, which depends on `python 2.7`. This conflicts with funpipe's python version. To use diamond, use it via [docker](#DOCKER).\n\n### **\u003ca name='DOCKER'\u003eInstall via Docker\u003c/a\u003e**\nThere's a bit more overhead using Docker, but it came along with the benefits of consistent  environment (i.e.: including the operation systems). It's very useful when using `funpipe` on the cloud.\n\nTo use docker:\n```\n# Download docker\ndocker pull broadinstitute/funpipe:latest\n\n# Run analysis interactively\ndocker run --rm -v $path_to_data/data -t broadinstitute/funpipe \\\n    /bin/bash -c \"/scripts/vcf_qc_metr.py \\\n        -p prefix --jar /bin/GenomeAnalysisTK.jar \\\n        --fa /data/reference.fa\n    \"\n```\n\nYou can use `Dockerfile` to compile the docker from scratch:\n```sh\ncd funpipe\ndocker build funpipe .\n```\n\n### **Install with PIP**\nThis approach is for advanced users who don't like conda and want to integrate funpipe into their current working environment. Before starting pip installation, make sure the following list of bioinformatic tools (or a subset of tools of interest) are properly installed and add to your `PATH`. Path to Java tools (JARs) need to be specified when evocaking specific functions.\n\n**Requirements**\n* Python \u003e= 3.7\n* Bioinformatic tool collections: can be automatically installed via conda [here](#CONDA)\n    * Basic functions:\n        - samtools\u003e=1.9\n        - bwa\u003e=0.7.8\n        - gatk\u003e=3.8\n        - picard\u003e=2.18.17\n    * Phylogenetics:\n        - raxml\u003e=8.2.12\n        - readseq\u003e=2.1.30\n    * CNV:\n        - breakdancer\u003e=1.4.5\n        - cnvnator\u003e=0.3\n    * Microbiome:\n        - pilon\u003e=1.23\n        - diamond\u003e=0.9.22\n\nTo install with pip:\n```sh\n# install latest stable release\npip install funpipe\n\n# install a specific version\npip install funpipe==0.1.0\n```\n\nTo install the latest version: funpipe\n```sh\ngit clone git@github.com:broadinstitute/funpipe.git\ncd funpipe\npip install .\n```\n\n## \u003ca name='DOC'\u003eDocumentation\u003c/a\u003e\nMajor analysis pipelines/tools:\n- Quality control modules\n    - Reference genome quality evaluation with `Pilon`.\n    - FASTQ quality control with `fastqc`.\n    - BAM quality control using `Picard`.\n    - VCF quality control using `GATK VariantEval`.\n- Variant Annotation with `snpEff`.\n- Genomic Variation\n    - Coverage analysis\n    - Mating type analysis\n    - Copy number variation with `CNVnator`\n- Phylogenetic analysis\n  - Dating analysis with `BEAST`.\n  - Phylogenetic tree with `FastTree`, `RAxML` and `IQTREE`.\n- GWAS analysis with `GEMMA`.\n\nHere are scripts to run each of the above pipelines, use `\u003ctoolname\u003e -h` to see the manuals.\n```sh\n##### Quality control #####\nrun_pilon.py          # Evaluate reference genome quality with pilon\nfastqc.py             # Fastq quality control\nbam_qc_metr.py        # Quality control of BAMs\nvcf_qc_metr.py        # Quality control of VCFs\n\n##### Variant Annotation #####\nrun_snpeff.py         # Annotation genomic variants with snpEff\nphylo_analysis.py     # Phylogenetic analysis\n\n##### Genomic Variations #####\ncoverage_analysis.py  # Hybrid coverage and ploidy analysis\n\n```\nYou can also use out APIs to build your customized analysis scripts or pipelines. The docs will be available here: https://funpipe.readthedocs.io\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbroadinstitute%2Ffunpipe","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fbroadinstitute%2Ffunpipe","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbroadinstitute%2Ffunpipe/lists"}