{ "_id": "6a1aec371d7bb097a09f430e", "Package": "KnowSeq", "Type": "Package", "Title": "KnowSeq R/Bioc package: The Smart Transcriptomic Pipeline", "Version": "1.27.0", "Authors@R": "c(person(\"Daniel\", \"Castillo-Secilla\", role = c(\"aut\",\"cre\"), \nemail = \"cased@ugr.es\"),\nperson(\"Juan Manuel\", \"Galvez\", role=\"ctb\"),\nperson(\"Francisco\", \"Carrillo-Perez\", role=\"ctb\"),\nperson(\"Marta\", \"Verona-Almeida\", role=\"ctb\"),\nperson(\"Daniel\", \"Redondo-Sanchez\", role=c(\"ctb\")),\nperson(\"Francisco Manuel\", \"Ortuno\", role=c(\"ctb\")),\nperson(\"Luis Javier\", \"Herrera\", role=c(\"ctb\")),\nperson(\"Ignacio\", \"Rojas\", role=c(\"ctb\")))", "Description": "KnowSeq proposes a novel methodology that comprises the\nmost relevant steps in the Transcriptomic gene expression\nanalysis. KnowSeq expects to serve as an integrative tool that\nallows to process and extract relevant biomarkers, as well as\nto assess them through a Machine Learning approaches. Finally,\nthe last objective of KnowSeq is the biological knowledge\nextraction from the biomarkers (Gene Ontology enrichment,\nPathway listing and Visualization and Evidences related to the\naddressed disease). Although the package allows analyzing all\nthe data manually, the main strenght of KnowSeq is the\npossibilty of carrying out an automatic and intelligent HTML\nreport that collect all the involved steps in one document. It\nis important to highligh that the pipeline is totally modular\nand flexible, hence it can be started from whichever of the\ndifferent steps. KnowSeq expects to serve as a novel tool to\nhelp to the experts in the field to acquire robust knowledge\nand conclusions for the data and diseases to study.", "License": "GPL (>=2)", "Encoding": "UTF-8", "RoxygenNote": "7.1.1", "biocViews": "GeneExpression, DifferentialExpression, GeneSetEnrichment,\nDataImport, Classification, FeatureExtraction, Sequencing,\nRNASeq, BatchEffect, Normalization, Preprocessing,\nQualityControl, Genetics, Transcriptomics, Microarray,\nAlignment, Pathways, SystemsBiology, GO, ImmunoOncology", "VignetteBuilder": "knitr", "git_url": "https://github.com/CasedUgr/KnowSeq", "Config/pak/sysreqs": "cmake make libicu-dev libpng-dev libuv1-dev\nlibxml2-dev libssl-dev zlib1g-dev", "Repository": "https://bioc.r-universe.dev", "Date/Publication": "2026-04-28 12:50:26 UTC", "RemoteUrl": "https://github.com/bioc/KnowSeq", "RemoteRef": "HEAD", "RemoteSha": "d40e5bcd1e4eabefd5812f7951a2b2f95f036d9d", "NeedsCompilation": "no", "Packaged": { "Date": "2026-05-30 09:40:26 UTC", "User": "root" }, "Author": "Daniel Castillo-Secilla [aut, cre],\nJuan Manuel Galvez [ctb],\nFrancisco Carrillo-Perez [ctb],\nMarta Verona-Almeida [ctb],\nDaniel Redondo-Sanchez [ctb],\nFrancisco Manuel Ortuno [ctb],\nLuis Javier Herrera [ctb],\nIgnacio Rojas [ctb]", "Maintainer": "Daniel Castillo-Secilla ", "MD5sum": "e81fb43d0d978285c0c422cd6ecdc9fd", "_user": "bioc", "_type": "src", "_file": "KnowSeq_1.27.0.tar.gz", "_fileid": "bae77bd67a63fd71cdcfa82e999270f2b30ceccaee27c26f339b01e22d6dac34", "_filesize": 8556391, "_sha256": "bae77bd67a63fd71cdcfa82e999270f2b30ceccaee27c26f339b01e22d6dac34", "_created": "2026-05-30T09:40:26.000Z", "_published": "2026-05-30T13:55:03.443Z", "_jobs": [ { "job": 78640287565, "time": 277, "config": "bioc-checks", "r": "4.6.0", "check": "WARNING", "artifact": "7307387905" }, { "job": 78640287573, "time": 355, "config": "linux-devel-x86_64", "r": "4.7.0", "check": "ERROR", "artifact": "7307394870" }, { "job": 78640287563, "time": 363, "config": "linux-release-x86_64", "r": "4.6.0", "check": "ERROR", "artifact": "7307395682" }, { "job": 78640287556, "time": 176, "config": "macos-oldrel-arm64", "r": "4.5.3", "check": "ERROR", "artifact": "7308669652" }, { "job": 78640287560, "time": 156, "config": "macos-release-arm64", "r": "4.6.0", "check": "ERROR", "artifact": "7308669361" }, { "job": 78639596485, "time": 316, "config": "source", "r": "4.6.0", "check": "OK", "artifact": "7307250224" }, { "job": 78640287566, "time": 345, "config": "wasm-release", "r": "4.6.0", "check": "OK", "artifact": "7307394016" }, { "job": 78640287576, "time": 233, "config": "windows-devel", "r": "4.7.0", "check": "ERROR", "artifact": "7307384781" }, { "job": 78640287577, "time": 270, "config": "windows-oldrel", "r": "4.5.3", "check": "ERROR", "artifact": "7307388512" }, { "job": 78640287578, "time": 272, "config": "windows-release", "r": "4.6.0", "check": "ERROR", "artifact": "7307388319" } ], "_bioccheck": { "error": 0, "warning": 2, "note": 18 }, "_buildurl": "https://github.com/r-universe/bioc/actions/runs/26676230423", "_status": "success", "_host": "GitHub-Actions", "_upstream": "https://github.com/bioc/KnowSeq", "_commit": { "id": "d40e5bcd1e4eabefd5812f7951a2b2f95f036d9d", "author": "A Wokaty ", "committer": "A Wokaty ", "message": "bump x.y.z version to odd y following creation of RELEASE_3_23 branch\n", "time": 1777380626 }, "_maintainer": { "name": "Daniel Castillo-Secilla", "email": "cased@ugr.es", "login": "casedugr", "linkedin": "in/cased93", "description": "I'm a Ph.D. with experience in Bioinformatics, Computational Biology, and Biomedical Engineering. Currently working as Senior BioInformatician at Fujitsu.", "uuid": 37144717 }, "_distro": "noble", "_registered": true, "_dependencies": [ { "package": "R", "version": ">= 4.0", "role": "Depends" }, { "package": "cqn", "version": ">= 1.28.1", "role": "Depends" }, { "package": "stringr", "role": "Imports" }, { "package": "methods", "role": "Imports" }, { "package": "ggplot2", "version": ">= 3.3.0", "role": "Imports" }, { "package": "jsonlite", "role": "Imports" }, { "package": "kernlab", "role": "Imports" }, { "package": "rlist", "role": "Imports" }, { "package": "rmarkdown", "role": "Imports" }, { "package": "reshape2", "role": "Imports" }, { "package": "e1071", "role": "Imports" }, { "package": "randomForest", "role": "Imports" }, { "package": "caret", "role": "Imports" }, { "package": "XML", "role": "Imports" }, { "package": "praznik", "role": "Imports" }, { "package": "R.utils", "role": "Imports" }, { "package": "httr", "role": "Imports" }, { "package": "sva", "version": ">= 3.30.1", "role": "Imports" }, { "package": "edgeR", "version": ">= 3.24.3", "role": "Imports" }, { "package": "limma", "version": ">= 3.38.3", "role": "Imports" }, { "package": "grDevices", "role": "Imports" }, { "package": "graphics", "role": "Imports" }, { "package": "stats", "role": "Imports" }, { "package": "utils", "role": "Imports" }, { "package": "Hmisc", "version": ">= 4.4.0", "role": "Imports" }, { "package": "gridExtra", "role": "Imports" }, { "package": "knitr", "role": "Suggests" } ], "_owner": "bioc", "_selfowned": true, "_usedby": 0, "_updates": [ { "week": "2025-44", "n": 2 }, { "week": "2026-18", "n": 2 } ], "_tags": [], "_bioc": [ { "branch": "devel", "version": "1.27.0", "bioc": "3.24" }, { "branch": "release", "version": "1.25.0", "bioc": "3.23" } ], "_topics": [ "geneexpression", "differentialexpression", "genesetenrichment", "dataimport", "classification", "featureextraction", "sequencing", "rnaseq", "batcheffect", "normalization", "preprocessing", "qualitycontrol", "genetics", "transcriptomics", "microarray", "alignment", "pathways", "systemsbiology", "go", "immunooncology" ], "_userbio": { "uuid": 2286807, "type": "organization", "name": "Bioconductor", "description": "Software for the analysis and comprehension of high-throughput genomic data" }, "_downloads": { "count": 402, "source": "https://www.bioconductor.org/packages/stats/bioc/KnowSeq" }, "_mentions": 1, "_searchresults": 10, "_rbuild": "4.6.0", "_assets": [ "extra/citation.cff", "extra/citation.html", "extra/citation.json", "extra/citation.txt", "extra/contents.json", "extra/KnowSeq.html", "extra/NEWS.html", "extra/NEWS.txt", "manual.pdf" ], "_realowner": "bioc", "_cranurl": false, "_exports": [ "batchEffectRemoval", "calculateGeneExpressionValues", "countsToMatrix", "dataPlot", "DEGsEvidences", "DEGsExtraction", "DEGsToDiseases", "DEGsToPathways", "downloadPublicSeries", "featureSelection", "fileMove", "gdcClientDownload", "geneOntologyEnrichment", "getGenesAnnotation", "hisatAlignment", "knn_test", "knn_trn", "knowseqReport", "plotConfMatrix", "rawAlignment", "rf_test", "rf_trn", "RNAseqQA", "sraToFastq", "svm_test", "svm_trn" ], "_help": [ { "page": "batchEffectRemoval", "title": "Corrects the batch effect of the data by using the selected method.", "topics": [ "batchEffectRemoval" ] }, { "page": "calculateGeneExpressionValues", "title": "Calculates the gene expression values by using a matrix of counts from RNA-seq.", "topics": [ "calculateGeneExpressionValues" ] }, { "page": "countsToMatrix", "title": "countsToMatrix merges in a matrix the information in the count files.", "topics": [ "countsToMatrix" ] }, { "page": "dataPlot", "title": "Plot different graphs depending on the current step of KnowSeq pipeline.", "topics": [ "dataPlot" ] }, { "page": "DEGsEvidences", "title": "DEGsEvidences function returns for each DEG a list of evidences that correlate it with the studied disease.", "topics": [ "DEGsEvidences" ] }, { "page": "DEGsExtraction", "title": "DEGsExtraction performs the analysis to extract the Differentially Expressed Genes (DEGs) among the classes to compare.", "topics": [ "DEGsExtraction" ] }, { "page": "DEGsToDiseases", "title": "DEGsToDiseases obtains the information about what diseases are related to the DEGs indicated by parameter.", "topics": [ "DEGsToDiseases" ] }, { "page": "DEGsToPathways", "title": "The function uses the DEGs to retrieves the different pathways in which those DEGs involve any interaction.", "topics": [ "DEGsToPathways" ] }, { "page": "downloadPublicSeries", "title": "Download automatically samples from NCBI/GEO and ArrayExpress public databases.", "topics": [ "downloadPublicSeries" ] }, { "page": "featureSelection", "title": "featureSelection function calculates the optimal order of DEGs to achieve the best result in the posterior machine learning process by using mRMR algorithm or Random Forest. Furthermore, the ranking is returned and can be used as input of the parameter vars_selected in the machine learning functions.", "topics": [ "featureSelection" ] }, { "page": "fileMove", "title": "This function is used to move files to other locations.", "topics": [ "fileMove" ] }, { "page": "gdcClientDownload", "title": "This function downloads a list of controlled files from GDC Portal with the user token and the manifest with the information about the desired controlled files.", "topics": [ "gdcClientDownload" ] }, { "page": "geneOntologyEnrichment", "title": "geneOntologyEnrichment obtains the information about what Gene Ontology terms are related to the DEGs.", "topics": [ "geneOntologyEnrichment" ] }, { "page": "getGenesAnnotation", "title": "getGenesAnnotation returns the required information about a list of genes from Ensembl biomart.", "topics": [ "getGenesAnnotation" ] }, { "page": "hisatAlignment", "title": "hisatAlignment allows downloading and processing the fastq samples in a CSV file by using hisat2 aligner.", "topics": [ "hisatAlignment" ] }, { "page": "knn_test", "title": "knn_test allows assessing the final DEGs through a machine learning step by using k-NN with a test dataset.", "topics": [ "knn_test" ] }, { "page": "knn_trn", "title": "knn_trn allows assessing the final DEGs through a machine learning step by using k-NN in a cross validation process.", "topics": [ "knn_trn" ] }, { "page": "knowseqReport", "title": "knowseqReport creates a report for a given set of genes which their label.", "topics": [ "knowseqReport" ] }, { "page": "plotConfMatrix", "title": "plotConfMatrix plots a confusion matrix with some statistics.", "topics": [ "plotConfMatrix" ] }, { "page": "rawAlignment", "title": "rawAlignment allows downloading and processing the fastq samples in a CSV file.", "topics": [ "rawAlignment" ] }, { "page": "rf_test", "title": "rf_test allows assessing the final DEGs through a machine learning step by using Random Forest with a test dataset.", "topics": [ "rf_test" ] }, { "page": "rf_trn", "title": "rf_trn allows assessing the final DEGs through a machine learning step by using Random Forest in a cross validation process.", "topics": [ "rf_trn" ] }, { "page": "RNAseqQA", "title": "RNAseqQA performs the quality analysis of an expression matrix.", "topics": [ "RNAseqQA" ] }, { "page": "sraToFastq", "title": "sraToFastq downloads and converts the sra files to fastq files. The function admits both gz and sra formats.", "topics": [ "sraToFastq" ] }, { "page": "svm_test", "title": "svm_test allows assessing the final DEGs through a machine learning step by using SVM with a test dataset.", "topics": [ "svm_test" ] }, { "page": "svm_trn", "title": "svm_trn allows assessing the final DEGs through a machine learning step by using svm in a cross validation process.", "topics": [ "svm_trn" ] } ], "_rundeps": [ "annotate", "AnnotationDbi", "askpass", "backports", "base64enc", "BH", "Biobase", "BiocGenerics", "BiocParallel", "Biostrings", "bit", "bit64", "blob", "bslib", "cachem", "caret", "checkmate", "class", "cli", "clock", "cluster", "codetools", "colorspace", "cpp11", "cqn", "crayon", "curl", "data.table", "DBI", "diagram", "digest", "dplyr", "e1071", "edgeR", "evaluate", "farver", "fastmap", "fontawesome", "foreach", "foreign", "formatR", "Formula", "fs", "futile.logger", "futile.options", "future", "future.apply", "genefilter", "generics", "ggplot2", "globals", "glue", "gower", "gridExtra", "gtable", "hardhat", "highr", "Hmisc", "htmlTable", "htmltools", "htmlwidgets", "httr", "ipred", "IRanges", "isoband", "iterators", "jquerylib", "jsonlite", "KEGGREST", "kernlab", "KernSmooth", "knitr", "labeling", "lambda.r", "lattice", "lava", "lifecycle", "limma", "listenv", "locfit", "lubridate", "magrittr", "MASS", "Matrix", "MatrixGenerics", "MatrixModels", "matrixStats", "mclust", "memoise", "mgcv", "mime", "ModelMetrics", "nlme", "nnet", "nor1mix", "numDeriv", "openssl", "parallelly", "pillar", "pkgconfig", "plyr", "png", "praznik", "pROC", "prodlim", "progressr", "proxy", "purrr", "quantreg", "R.methodsS3", "R.oo", "R.utils", "R6", "randomForest", "rappdirs", "RColorBrewer", "Rcpp", "recipes", "reshape2", "rlang", "rlist", "rmarkdown", "rpart", "RSQLite", "rstudioapi", "S4Vectors", "S7", "sass", "scales", "Seqinfo", "shape", "snow", "SparseM", "sparsevctrs", "SQUAREM", "statmod", "stringi", "stringr", "survival", "sva", "sys", "tibble", "tidyr", "tidyselect", "timechange", "timeDate", "tinytex", "tzdb", "utf8", "vctrs", "viridisLite", "withr", "xfun", "XML", "xtable", "XVector", "yaml" ], "_vignettes": [ { "source": "KnowSeq.Rmd", "filename": "KnowSeq.html", "title": "Transcriptomic Intelligent Pipeline: The KnowSeq user guide ", "author": "Daniel Castillo-Secilla, Juan Manuel Galvez, Marta Verona-Almeida, Francisco Carrillo-Perez, Francisco Manuel Ortuno, Luis Javier Herrera and Ignacio Rojas", "engine": "knitr::rmarkdown", "headings": [ "Citation", "Installation", "Introduction", "Transcriptomic RAW data processing", "Alignment preparation", "Launching Raw Alignment step ", "NCBI/GEO CSV format", "ArrayExpress CSV format", "GDC Portal CSV format", "Downloading automatically GDC Portal controlled files (GDC permission required)", "Preparing the count files", "Processing count files", "Merging all count files", "Getting the annotation of the genes", "Converting to gene expression matrix", "Biomarkers identification & assessment", "Batch effect removal", "Differential Expressed Genes extraction and visualization", "Performing the machine learning processing: classifier design and assessment and gene selection", "DEGs enrichment methodology", "Gene Ontology", "Pathway Information", "Related diseases", "Gene Expression Intelligent Report", "Session Info", "References" ], "created": "2019-05-15 14:16:03", "modified": "2021-04-22 18:06:14", "commits": 27 } ], "_score": 3.3010299956639813, "_indexed": true, "_nocasepkg": "knowseq", "_universes": [ "bioc", "casedugr" ], "_binaries": [ { "r": "4.7.0", "os": "linux", "version": "1.27.0", "date": "2026-05-30T10:03:11.000Z", "distro": "noble", "commit": "d40e5bcd1e4eabefd5812f7951a2b2f95f036d9d", "fileid": "500c44976d68b9522262648e8a2a7e546dc6a73a7eb4ef3b5341e926bab31015", "status": "failure", "check": "ERROR", "buildurl": "https://github.com/r-universe/bioc/actions/runs/26676230423" }, { "r": "4.6.0", "os": "linux", "version": "1.27.0", "date": "2026-05-30T10:03:35.000Z", "distro": "noble", "commit": "d40e5bcd1e4eabefd5812f7951a2b2f95f036d9d", "fileid": "7f25414278612827b0df7955fdcb4cfbf974b55079c6c194c2b5da0e353cc5ff", "status": "failure", "check": "ERROR", "buildurl": "https://github.com/r-universe/bioc/actions/runs/26676230423" }, { "r": "4.5.3", "os": "mac", "version": "1.27.0", "date": "2026-05-30T13:53:14.000Z", "commit": "d40e5bcd1e4eabefd5812f7951a2b2f95f036d9d", "fileid": "c3078dda4644b70218c3009afa9834a5538e555ed4cf5e7b2b34e3f3629942d8", "status": "failure", "check": "ERROR", "buildurl": "https://github.com/r-universe/bioc/actions/runs/26676230423" }, { "r": "4.6.0", "os": "mac", "version": "1.27.0", "date": "2026-05-30T13:53:11.000Z", "commit": "d40e5bcd1e4eabefd5812f7951a2b2f95f036d9d", "fileid": "f85f24b8f8d8510cdb0b43cab7711e79435326a98b78b446dd406ebcf76ab994", "status": "failure", "check": "ERROR", "buildurl": "https://github.com/r-universe/bioc/actions/runs/26676230423" }, { "r": "4.6.0", "os": "wasm", "version": "1.27.0", "date": "2026-05-30T10:05:33.000Z", "commit": "d40e5bcd1e4eabefd5812f7951a2b2f95f036d9d", "fileid": "828f0bd314741509ec664ffadcff7dfc5306ce2a6202f564ac904806405b7d27", "status": "success", "buildurl": "https://github.com/r-universe/bioc/actions/runs/26676230423" }, { "r": "4.7.0", "os": "win", "version": "1.27.0", "date": "2026-05-30T10:01:24.000Z", "commit": "d40e5bcd1e4eabefd5812f7951a2b2f95f036d9d", "fileid": "e26b82107672140bf9e637de7940db3468e14c6a5cac64cbfcb3482f4bc92f62", "status": "failure", "check": "ERROR", "buildurl": "https://github.com/r-universe/bioc/actions/runs/26676230423" }, { "r": "4.5.3", "os": "win", "version": "1.27.0", "date": "2026-05-30T10:01:56.000Z", "commit": "d40e5bcd1e4eabefd5812f7951a2b2f95f036d9d", "fileid": "2d81bfb883622562a0ab7c853c5a1d38034bfc891e974eeca0e0b7fe2aac8545", "status": "failure", "check": "ERROR", "buildurl": "https://github.com/r-universe/bioc/actions/runs/26676230423" }, { "r": "4.6.0", "os": "win", "version": "1.27.0", "date": "2026-05-30T10:01:50.000Z", "commit": "d40e5bcd1e4eabefd5812f7951a2b2f95f036d9d", "fileid": "07875cd20b98c05f3b4cb62026fe085c3365d2f3e2ce7e7d51622920deb5fe6a", "status": "failure", "check": "ERROR", "buildurl": "https://github.com/r-universe/bioc/actions/runs/26676230423" } ] }