{"id":17403705,"url":"https://github.com/federicomarini/pcaexplorer","last_synced_at":"2025-04-13T02:12:58.205Z","repository":{"id":80516438,"uuid":"53661116","full_name":"federicomarini/pcaExplorer","owner":"federicomarini","description":"pcaExplorer - Interactive exploration of Principal Components of Samples and Genes in RNA-seq data","archived":false,"fork":false,"pushed_at":"2025-03-07T14:00:49.000Z","size":62812,"stargazers_count":56,"open_issues_count":7,"forks_count":17,"subscribers_count":11,"default_branch":"devel","last_synced_at":"2025-04-04T04:11:09.146Z","etag":null,"topics":["bioconductor","principal-components","r","reproducible-research","rna-seq-analysis","rna-seq-data","shiny","transcriptome","user-friendly"],"latest_commit_sha":null,"homepage":"https://federicomarini.github.io/pcaExplorer/","language":"R","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"other","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/federicomarini.png","metadata":{"files":{"readme":"README.md","changelog":"NEWS.md","contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":"CODE_OF_CONDUCT.md","threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2016-03-11T11:00:26.000Z","updated_at":"2025-03-07T13:44:44.000Z","dependencies_parsed_at":"2024-04-07T11:27:55.359Z","dependency_job_id":"7a0219fe-e12c-4436-9cd7-621d652cd433","html_url":"https://github.com/federicomarini/pcaExplorer","commit_stats":{"total_commits":552,"total_committers":14,"mean_commits":39.42857142857143,"dds":0.08695652173913049,"last_synced_commit":"11c744f314f43dad956e2fe4e0c12cc0b7d99375"},"previous_names":[],"tags_count":2,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/federicomarini%2FpcaExplorer","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/federicomarini%2FpcaExplorer/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/federicomarini%2FpcaExplorer/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/federicomarini%2FpcaExplorer/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/federicomarini","download_url":"https://codeload.github.com/federicomarini/pcaExplorer/tar.gz/refs/heads/devel","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":248654094,"owners_count":21140236,"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","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":["bioconductor","principal-components","r","reproducible-research","rna-seq-analysis","rna-seq-data","shiny","transcriptome","user-friendly"],"created_at":"2024-10-16T19:07:19.135Z","updated_at":"2025-04-13T02:12:58.167Z","avatar_url":"https://github.com/federicomarini.png","language":"R","readme":"\u003cimg src=\"man/figures/pcaExplorer.png\" align=\"right\" alt=\"\" width=\"120\" /\u003e\n\n# pcaExplorer - Interactive exploration of Principal Components of Samples and Genes in RNA-seq data \n\n\u003ca href=\"https://doi.org/10.1186/s12859-019-2879-1\"\u003e\u003cimg src=\"https://img.shields.io/badge/doi-pcaExplorer-blue.svg\"\u003e\u003ca\u003e\n\u003ca href=\"https://doi.org/10.1002/cpz1.411\"\u003e\u003cimg src=\"https://img.shields.io/badge/doi-pcaExplorer_protocol-blue.svg\"\u003e\u003ca\u003e\n\n## Software status\n\n[![R build status](https://github.com/federicomarini/pcaExplorer/workflows/R-CMD-check/badge.svg)](https://github.com/federicomarini/pcaExplorer/actions)\n\n| Platforms |  OS  | R CMD check |\n|:----------------:|:----------------:|:----------------:|\n| Bioc ([_devel_](http://bioconductor.org/packages/devel/bioc/html/pcaExplorer.html)) | Multiple | [![Bioconductor-devel Build Status](http://bioconductor.org/shields/build/devel/bioc/pcaExplorer.svg)](http://bioconductor.org/checkResults/devel/bioc-LATEST/pcaExplorer) |\n| Bioc ([_release_](http://bioconductor.org/packages/release/bioc/html/pcaExplorer.html)) | Multiple | [![Bioconductor-release Build Status](http://bioconductor.org/shields/build/release/bioc/pcaExplorer.svg)](http://bioconductor.org/checkResults/release/bioc-LATEST/pcaExplorer) |\n\n[![codecov.io](https://codecov.io/github/federicomarini/pcaExplorer/coverage.svg?branch=master)](https://codecov.io/github/federicomarini/pcaExplorer?branch=master)\n\n`pcaExplorer` is a Bioconductor package containing a Shiny application for\nanalyzing expression data in different conditions and experimental factors. \n\nIt is a general-purpose interactive companion tool for RNA-seq analysis, which \nguides the user in exploring the Principal Components of the data under inspection.\n\n`pcaExplorer` provides tools and functionality to detect outlier samples, genes\nthat show particular patterns, and additionally provides a functional interpretation of \nthe principal components for further quality assessment and hypothesis generation\non the input data. \n\nMoreover, a novel visualization approach is presented to simultaneously assess \nthe effect of more than one experimental factor on the expression levels.\n\nThanks to its interactive/reactive design, it is designed to become a practical\ncompanion to any RNA-seq dataset analysis, making exploratory data analysis \naccessible also to the bench biologist, while providing additional insight also\nfor the experienced data analyst.\n\n## Installation\n\n`pcaExplorer` can be easily installed using `BiocManager::install()`:\n\n``` r\nif (!requireNamespace(\"BiocManager\", quietly=TRUE))\n    install.packages(\"BiocManager\")\nBiocManager::install(\"pcaExplorer\")\n```\n\nor, optionally, \n\n``` r\nBiocManager::install(\"federicomarini/pcaExplorer\")\n# or alternatively...\ndevtools::install_github(\"federicomarini/pcaExplorer\")\n```\n\n## Quick start\n\nThis command loads the `pcaExplorer` package\n\n``` r\nlibrary(\"pcaExplorer\")\n```\n\nThe `pcaExplorer` app can be launched in different modes:\n\n- `pcaExplorer(dds = dds, dst = dst)`, where `dds` is a `DESeqDataSet` object and `dst` is a `DESeqTransform`\nobject, which were created during an existing session for the analysis of an RNA-seq\ndataset with the `DESeq2` package\n\n- `pcaExplorer(dds = dds)`, where `dds` is a `DESeqDataSet` object. The `dst` object is automatically \ncomputed upon launch.\n\n- `pcaExplorer(countmatrix = countmatrix, coldata = coldata)`, where `countmatrix` is a count matrix, generated\nafter assigning reads to features such as genes via tools such as `HTSeq-count` or `featureCounts`, and `coldata`\nis a data frame containing the experimental covariates of the experiments, such as condition, tissue, cell line,\nrun batch and so on.\n\n- `pcaExplorer()`, and then subsequently uploading the count matrix and the covariates data frame through the \nuser interface. These files need to be formatted as tab separated files, which is a common format for storing\nsuch count values.\n\nAdditional parameters and objects that can be provided to the main `pcaExplorer` function are:\n\n- `pca2go`, which is an object created by the `pca2go` function, which scans the genes with high loadings in \neach principal component and each direction, and looks for functions (such as GO Biological Processes) that \nare enriched above the background. The offline `pca2go` function is based on the routines and algorithms of \nthe `topGO` package, but as an alternative, this object can be computed live during the execution of the app\nexploiting the `goana` function, provided by the `limma` package. Although this likely provides more general\n(and probably less informative) functions, it is a good compromise for obtaining a further data interpretation.\n\n- `annotation`, a data frame object, with `row.names` as gene identifiers (e.g. ENSEMBL ids) identical to the \nrow names of the count matrix or `dds` object, and an extra column `gene_name`, containing e.g. HGNC-based \ngene symbols. This can be used for making information extraction easier, as ENSEMBL ids (a usual choice when\nassigning reads to features) do not provide an immediate readout for which gene they refer to. This can be\neither passed as a parameter when launching the app, or also uploaded as a tab separated text file.\n\n## Contact\n\nFor additional details regarding the functions of **pcaExplorer**, please consult the documentation or \nwrite an email to marinif@uni-mainz.de. \n\n## Code of Conduct\n\nPlease note that the pcaExplorer project is released with a [Contributor Code of Conduct](https://contributor-covenant.org/version/2/0/CODE_OF_CONDUCT.html). By contributing to this project, you agree to abide by its terms.\n\n### Bug reports/Issues/New features\n\nPlease use https://github.com/federicomarini/pcaExplorer/issues for reporting bugs, issues or for \nsuggesting new features to be implemented. \n","funding_links":[],"categories":[],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ffedericomarini%2Fpcaexplorer","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Ffedericomarini%2Fpcaexplorer","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ffedericomarini%2Fpcaexplorer/lists"}