{ "_id": "6a1ac3761d7bb097a09da608", "Package": "mdp", "Title": "Molecular Degree of Perturbation calculates scores for\ntranscriptome data samples based on their perturbation from\ncontrols", "Version": "1.33.0", "Authors@R": "c(person(\"Melissa\", \"Lever\", email = \"melissalever@gmail.com\", role = c(\"aut\")), person(\"Pedro\", \"Russo\", email = \"pedro.russo@usp.br\", role = c(\"aut\")),\nperson(\"Helder\", \"Nakaya\", email = \"hnakaya@usp.br\", role = c(\"aut\", \"cre\")))", "Description": "The Molecular Degree of Perturbation webtool quantifies\nthe heterogeneity of samples. It takes a data.frame of omic\ndata that contains at least two classes (control and test) and\nassigns a score to all samples based on how perturbed they are\ncompared to the controls. It is based on the Molecular Distance\nto Health (Pankla et al. 2009), and expands on this algorithm\nby adding the options to calculate the z-score using the\nmodified z-score (using median absolute deviation), change the\nz-score zeroing threshold, and look at genes that are most\nperturbed in the test versus control classes.", "URL": "https://mdp.sysbio.tools/", "biocViews": "BiomedicalInformatics, QualityControl, Transcriptomics,\nSystemsBiology, Microarray, QualityControl", "License": "GPL-3", "Encoding": "UTF-8", "LazyData": "true", "RoxygenNote": "7.1.1", "VignetteBuilder": "knitr", "Repository": "https://bioc.r-universe.dev", "Date/Publication": "2026-04-28 12:47:50 UTC", "RemoteUrl": "https://github.com/bioc/mdp", "RemoteRef": "HEAD", "RemoteSha": "0fae06586a27846abfb9dbbe933d21630e964fd0", "NeedsCompilation": "no", "Packaged": { "Date": "2026-05-30 07:41:38 UTC", "User": "root" }, "Author": "Melissa Lever [aut],\nPedro Russo [aut],\nHelder Nakaya [aut, cre]", "Maintainer": "Helder Nakaya ", "MD5sum": "dfbea6b5c71b40929d78a5240921f5c8", "_user": "bioc", "_type": "src", "_file": "mdp_1.33.0.tar.gz", "_fileid": "b25ce357aefc6067ee8e11ecc813c1cb6c8a0ff57d0f0286ef71d1697b63488c", "_filesize": 4547651, "_sha256": "b25ce357aefc6067ee8e11ecc813c1cb6c8a0ff57d0f0286ef71d1697b63488c", "_created": "2026-05-30T07:41:38.000Z", "_published": "2026-05-30T11:01:10.080Z", "_jobs": [ { "job": 78634232551, "time": 148, "config": "bioc-checks", "r": "4.6.0", "check": "WARNING", "artifact": "7306569311" }, { "job": 78634232568, "time": 230, "config": "linux-devel-x86_64", "r": "4.7.0", "check": "OK", "artifact": "7306577400" }, { "job": 78634232566, "time": 202, "config": "linux-release-x86_64", "r": "4.6.0", "check": "OK", "artifact": "7306574603" }, { "job": 78634232565, "time": 120, "config": "macos-oldrel-arm64", "r": "4.5.3", "check": "OK", "artifact": "7307694315" }, { "job": 78634232574, "time": 124, "config": "macos-release-arm64", "r": "4.6.0", "check": "OK", 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following creation of RELEASE_3_23 branch\n", "time": 1777380470 }, "_maintainer": { "name": "Helder Nakaya", "email": "hnakaya@usp.br", "login": "csbl-usp", "twitter": "@CSBL1", "description": "Employing systems biology approaches to understand the molecular mechanisms of infectious diseases and vaccine-induced immunity.", "uuid": 8866035 }, "_distro": "noble", "_registered": true, "_dependencies": [ { "package": "R", "version": ">= 4.0", "role": "Depends" }, { "package": "ggplot2", "role": "Imports" }, { "package": "gridExtra", "role": "Imports" }, { "package": "grid", "role": "Imports" }, { "package": "stats", "role": "Imports" }, { "package": "utils", "role": "Imports" }, { "package": "testthat", "role": "Suggests" }, { "package": "knitr", "role": "Suggests" }, { "package": "rmarkdown", "role": "Suggests" }, { "package": "fgsea", "role": "Suggests" }, { "package": "BiocManager", "role": "Suggests" } ], "_owner": "bioc", "_selfowned": true, "_usedby": 0, "_updates": [ { "week": 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"topics": [ "mdp" ] }, { "page": "pathway_summary", "title": "print pathways generates a summary plot for pathways and sample score plot of best gene set", "topics": [ "pathway_summary" ] }, { "page": "sample_data", "title": "Sample score results", "topics": [ "sample_data" ] }, { "page": "sample_plot", "title": "Plot sample scores Plots the sample scores data.frame for a given geneset. 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