{ "_id": "6a1aaedb1d7bb097a09d509d", "Package": "qusage", "Version": "2.47.0", "Date": "2013-01-20", "Title": "qusage: Quantitative Set Analysis for Gene Expression", "Authors@R": "c(person(\"Christopher Bolen\", \"Developer\", role = c(\"aut\",\n\"cre\"), email = \"cbolen1@gmail.com\"), person(\"Gur Yaari\",\n\"Developer\", role = \"aut\"), person(\"Juilee Thakar\",\n\"Developer\", role = \"aut\"), person(\"Hailong Meng\",\n\"Developer\", role = \"aut\"), person(\"Jacob Turner\",\n\"Developer\", role = \"aut\"), person(\"Derek Blankenship\",\n\"Developer\", role = \"aut\"), person(\"Steven Kleinstein\",\n\"Developer\", role = \"aut\"))", "Author": "Christopher Bolen and Gur Yaari, with contributions from Juilee\nThakar, Hailong Meng, Jacob Turner, Derek Blankenship, and\nSteven Kleinstein", "Maintainer": "Christopher Bolen ", "Description": "This package is an implementation the Quantitative Set\nAnalysis for Gene Expression (QuSAGE) method described in\n(Yaari G. et al, Nucl Acids Res, 2013). This is a novel Gene\nSet Enrichment-type test, which is designed to provide a\nfaster, more accurate, and easier to understand test for gene\nexpression studies. qusage accounts for inter-gene correlations\nusing the Variance Inflation Factor technique proposed by Wu et\nal. (Nucleic Acids Res, 2012). In addition, rather than simply\nevaluating the deviation from a null hypothesis with a single\nnumber (a P value), qusage quantifies gene set activity with a\ncomplete probability density function (PDF). From this PDF, P\nvalues and confidence intervals can be easily extracted.\nPreserving the PDF also allows for post-hoc analysis (e.g.,\npair-wise comparisons of gene set activity) while maintaining\nstatistical traceability. Finally, while qusage is compatible\nwith individual gene statistics from existing methods (e.g.,\nLIMMA), a Welch-based method is implemented that is shown to\nimprove specificity. The QuSAGE package also includes a mixed\neffects model implementation, as described in (Turner JA et al,\nBMC Bioinformatics, 2015), and a meta-analysis framework as\ndescribed in (Meng H, et al. PLoS Comput Biol. 2019). For\nquestions, contact Chris Bolen (cbolen1@gmail.com) or Steven\nKleinstein (steven.kleinstein@yale.edu)", "License": "GPL (>= 2)", "URL": "http://clip.med.yale.edu/qusage", "biocViews": "GeneSetEnrichment, Microarray, RNASeq, Software,\nImmunoOncology", "Config/pak/sysreqs": "libfftw3-dev", "Repository": "https://bioc.r-universe.dev", "Date/Publication": "2026-04-28 12:38:06 UTC", "RemoteUrl": "https://github.com/bioc/qusage", "RemoteRef": "HEAD", "RemoteSha": "c6d4f2da4b0ee6c168c72eca8a99b36a69d37571", "NeedsCompilation": "no", "Packaged": { "Date": "2026-05-30 07:03:47 UTC", "User": "root" }, "MD5sum": "169fa62c901b090498995d3dcd80917e", "_user": "bioc", "_type": "src", "_file": "qusage_2.47.0.tar.gz", "_fileid": "fc6a7c652af379e3c0d191e5f7254ad0d69c09017fb6489b19ccdc4bda43f88e", "_filesize": 10182369, "_sha256": "fc6a7c652af379e3c0d191e5f7254ad0d69c09017fb6489b19ccdc4bda43f88e", "_created": "2026-05-30T07:03:47.000Z", "_published": "2026-05-30T09:33:15.013Z", "_jobs": [ { "job": 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90, "config": "windows-oldrel", "r": "4.5.3", "check": "NOTE", "artifact": "7306311967" }, { "job": 78632200485, "time": 83, "config": "windows-release", "r": "4.6.0", "check": "NOTE", "artifact": "7306310919" } ], "_bioccheck": { "error": 1, "warning": 5, "note": 17 }, "_buildurl": "https://github.com/r-universe/bioc/actions/runs/26677459422", "_status": "success", "_host": "GitHub-Actions", "_upstream": "https://github.com/bioc/qusage", "_commit": { "id": "c6d4f2da4b0ee6c168c72eca8a99b36a69d37571", "author": "A Wokaty ", "committer": "A Wokaty ", "message": "bump x.y.z version to odd y following creation of RELEASE_3_23 branch\n", "time": 1777379886 }, "_maintainer": { "name": "Christopher Bolen", "email": "cbolen1@gmail.com", "login": "cbolen1", "description": "", "uuid": 31855450 }, "_distro": "noble", "_registered": true, "_dependencies": [ { "package": "R", "version": ">= 2.10", "role": "Depends" }, { "package": "limma", "version": ">= 3.14", "role": "Depends" }, { "package": 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"class": [ "list" ], "fields": [], "table": false, "tojson": true } ], "_help": [ { "page": "aggregateGeneSet", "title": "Calculate Pathway Activation", "topics": [ "aggregateGeneSet" ] }, { "page": "calcBayesCI", "title": "Calculate pathway Confidence Intervals", "topics": [ "calcBayesCI" ] }, { "page": "calcVIF", "title": "Calculate Variance Inflation Factor", "topics": [ "calcVIF" ] }, { "page": "combinePDFs", "title": "Combine PDFs from multiple QuSAGE comparisons", "topics": [ "combinePDFs" ] }, { "page": "eset.full", "title": "Example gene expression set", "topics": [ "eset.full", "flu.meta", "fluExample" ] }, { "page": "fluVaccine", "title": "Gene expression sets from Flu Vaccine trials", "topics": [ "fluVaccine" ] }, { "page": "GeneSets", "title": "Example Gene Sets", "topics": [ "BTM.geneSets", "GeneSets", "ISG.geneSet", "MSIG.geneSets" ] }, { "page": "getXcoords", "title": "Get the X coordinates for the points of the PDF", "topics": [ "getXcoords" ] }, { "page": 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analysis at the gene level to account for repeated measures, continous covariates, and confounder adjusting.", "topics": [ "qgen" ] }, { "page": "QSarray-class", "title": "Class '\"QSarray\"'", "topics": [ "dim,QSarray-method", "head,QSarray-method", "numFeatures", "numFeatures,QSarray-method", "numPathways", "numPathways,QSarray-method", "plot,QSarray-method", "print,QSarray-method", "QSarray-class", "summary,QSarray-method" ] }, { "page": "qsTable", "title": "Summary of QSarray Results", "topics": [ "qsTable" ] }, { "page": "qusage", "title": "Run qusage on an expression dataset", "topics": [ "qusage" ] }, { "page": "read.gmt", "title": "Read in gene set information from .gmt files", "topics": [ "read.gmt" ] } ], "_rundeps": [ "Biobase", "BiocGenerics", "emmeans", "estimability", "fftw", "generics", "lattice", "limma", "mvtnorm", "nlme", "numDeriv", "rlang", "statmod" ], "_vignettes": [ { "source": "qusage.Rnw", "filename": "qusage.pdf", "title": "Running qusage", "engine": 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