{ "_id": "6ae771a42e87f76f20acd368", "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": "2026-11-01 14:14:04 UTC", "User": "root" }, "_user": "bioc", "_type": "src", "_file": "qusage_2.47.0.tar.gz", "_fileid": "https://r2.ropensci.org/168e316e826a17895f9f4e08d71ed86db8224392ffd58574f4d923a8aa58534e", "_filesize": 10185845, "_sha256": "168e316e826a17895f9f4e08d71ed86db8224392ffd58574f4d923a8aa58534e", "_expires": "2027-02-09T17:06:42.000Z", "_created": "2026-11-01T14:14:04.000Z", "_published": "2026-11-01T17:06:44.762Z", "_upstream": "https://github.com/bioc/qusage", "_status": "success", "_maintainer": { "name": "Christopher Bolen", "email": "cbolen1@gmail.com", "login": "cbolen1", "description": "", "uuid": 31855450 }, "_jobs": [ { "job": 124873639554, "time": 137, "config": "bioc-checks", "r": "4.6.2", "check": "ERROR", "artifact": "13087748024" }, { "job": 124873639444, "time": 204, "config": "linux-devel-x86_64", "r": "4.7.0", "check": "NOTE", "artifact": "13087688305" }, { "job": 124873639547, "time": 218, "config": "linux-release-x86_64", "r": "4.6.2", "check": "NOTE", "artifact": "13087553589" }, { "job": 124873639623, "time": 133, "config": "macos-oldrel-arm64", "r": "4.5.3", "check": "NOTE", "artifact": "13093030209" }, { "job": 124873639460, "time": 95, "config": "macos-release-arm64", "r": "4.6.2", "check": "NOTE", "artifact": "13092433771" }, { "job": 124865184600, "time": 363, "config": "source", "r": "4.6.2", "check": "OK", "artifact": "13087470109" }, { "job": 124873639505, "time": 92, 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{ "page": "qgen", "title": "Run qusage while incoprating generalized least squares and linear mixed model 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" ], 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