{ "_id": "6ac22886773a0037682c2cde", "Package": "epiPortrait", "Type": "Package", "Title": "Replicate-Aware Epigenomic Domain Profiling", "Version": "0.99.3", "Authors@R": "c(\nperson(given = \"Ying\", family = \"ZHANG\",\nrole = c(\"aut\", \"cre\"),\nemail = \"12207129@zju.edu.cn\",\ncomment = c(ORCID = \"0009-0005-9644-7062\")),\nperson(given = \"Xingze\", family = \"HUANG\",\nrole = c(\"ctb\"),\nemail = \"22407026@zju.edu.cn\",\ncomment = c(ORCID = \"0009-0002-9286-1344\")),\nperson(given = \"Ye\", family = \"CHEN\",\nrole = \"ctb\",\nemail = \"chenyephd@zju.edu.cn\"),\nperson(given = \"Liang\", family = \"XU\",\nrole = c(\"ctb\", \"fnd\"),\nemail = \"xuliang.phd@zju.edu.cn\",\ncomment = \"This work is funded by the Fundamental Research Funds for the Central Universities (226-2025-00101) and the National Natural Science Foundation of China (32270746, 82203247, 82203415).\")\n)", "Description": "Provides methods for replicate-aware quantitative\nphenotyping and comparison of epigenomic domains from\nnormalized continuous signal tracks and per-sample native\npeak/domain calls (histone-mark ChIP-seq / CUT&Tag as the\nprimary use case; also applicable to ATAC-seq-derived domains).\nIt characterizes each shared genomic domain by integrated\nsignal magnitude (Intensity), sample-specific native peak\nbreadth geometry, and continuous within-domain signal\narchitecture (SignalDispersion). Replicate-level evidence is\nretained and aggregated with specified support rules, enabling\ncondition-specific classification of Intensity-Super,\nBreadth-Super, Dual-Super, Typical, or Uncertain domain states\nwithout using the consensus-domain width as the breadth caller.\nThe package further supports condition transitions, continuous\ndomain-width remodeling, signal quality control, genome-aware\ndomain annotation with a three-level export (per-domain\nsummary, per-domain-gene pair, and raw relationship detail),\noptional BEDPE contact evidence, expression-aware\ncandidate-gene prioritization, differential domain analysis on\ncontinuous BigWig signal using limma, and result visualization.", "License": "GPL (>= 3) + file LICENSE", "Encoding": "UTF-8", "Roxygen": "list(markdown = TRUE)", "RoxygenNote": "7.3.3", "Config/testthat/edition": "3", "biocViews": "ChIPSeq, ATACSeq, Epigenetics, Coverage, Normalization,\nDifferentialExpression, GenomeAnnotation, QualityControl,\nVisualization, PrincipalComponent", "URL": "https://github.com/zying106/epiPortrait", "BugReports": "https://github.com/zying106/epiPortrait/issues", "VignetteBuilder": "knitr", "Config/pak/sysreqs": "make libbz2-dev liblzma-dev libpng-dev libxml2-dev\nlibssl-dev xz-utils zlib1g-dev", "Repository": "https://biocstaging.r-universe.dev", "Date/Publication": "2026-09-04 00:02:14 UTC", "RemoteUrl": "https://github.com/BiocStaging/epiPortrait", "RemoteRef": "HEAD", "RemoteSha": "6dd14984eba9dfb38708b30501b2edd85b6dcbf9", "NeedsCompilation": "no", "Packaged": { "Date": "2026-10-04 10:11:12 UTC", "User": "root" }, "Author": "Ying ZHANG [aut, cre] (ORCID: ),\nXingze HUANG [ctb] (ORCID: ),\nYe CHEN [ctb],\nLiang XU [ctb, fnd] (This work is funded by the Fundamental Research\nFunds for the Central Universities (226-2025-00101) and the\nNational Natural Science Foundation of China (32270746, 82203247,\n82203415).)", "Maintainer": "Ying ZHANG <12207129@zju.edu.cn>", "_user": "biocstaging", "_type": "src", "_file": "epiPortrait_0.99.3.tar.gz", "_fileid": "https://r2.ropensci.org/57dc5ac9bf773c73932ab38d4bb811aec791ab6141c8a64abe51dc83344f81d8", "_filesize": 2257892, "_sha256": "57dc5ac9bf773c73932ab38d4bb811aec791ab6141c8a64abe51dc83344f81d8", "_expires": "2027-01-12T10:20:53.000Z", "_created": "2026-10-04T10:11:12.000Z", "_published": "2026-10-04T10:20:54.790Z", "_bioccheck": { "error": 0, "warning": 0, "note": 4 }, "_host": "GitHub-Actions", "_buildurl": "https://github.com/r-universe/biocstaging/actions/runs/37194221942", "_status": "success", "_upstream": "https://github.com/BiocStaging/epiPortrait", "_commit": { "id": "6dd14984eba9dfb38708b30501b2edd85b6dcbf9", "author": "Ying Zhang <12207129@zju.edu.cn>", "committer": "Ying Zhang <12207129@zju.edu.cn>", "message": "Bump version to 0.99.3; add NEWS entries for 0.99.2/0.99.3\n", "time": 1788480134 }, "_maintainer": { "name": "Ying ZHANG", "email": "12207129@zju.edu.cn", "login": "zying106", 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"epiPortrait-package", "epiPortrait" ] }, { "page": "example_se", "title": "Example Epigenetic Portrait Dataset", "topics": [ "example_se" ] }, { "page": "export_epiportrait_results", "title": "Export Complete epiPortrait Results to Disk", "topics": [ "export_epiportrait_results" ] }, { "page": "filter_blacklist", "title": "Filter ENCODE Blacklist Regions", "topics": [ "filter_blacklist" ] }, { "page": "filter_promoter_peaks", "title": "Filter Peaks by Genomic Annotations (Promoter Exclusion)", "topics": [ "filter_promoter_peaks" ] }, { "page": "find_hockey_inflection", "title": "Find the Hockey-Stick Inflection Point", "topics": [ "find_hockey_inflection" ] }, { "page": "get_call_provenance", "title": "Extract Super-Domain Call Provenance", "topics": [ "get_call_provenance" ] }, { "page": "get_call_results", "title": "Extract Call Results as a Flat Table", "topics": [ "get_call_results" ] }, { "page": "get_combined_class_results", "title": "Extract Combined Class Results", "topics": [ 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Hockey Stick Curve for Super-Domain Identification", "topics": [ "plot_hockey_stick" ] }, { "page": "plot_peak_track", "title": "Plot Physical Coverage Profile for a Specific Peak (Track View)", "topics": [ "plot_peak_track" ] }, { "page": "plot_portrait_correlation", "title": "Sample Correlation Heatmap for epiPortrait Features", "topics": [ "plot_portrait_correlation" ] }, { "page": "plot_portrait_pca", "title": "Exploratory PCA Plot for epiPortrait Features", "topics": [ "plot_portrait_pca" ] }, { "page": "plot_replicate_support", "title": "Plot Replicate-Support Distribution", "topics": [ "plot_replicate_support" ] }, { "page": "plot_uncertain_cause", "title": "Plot the Cause Composition of Uncertain Calls", "topics": [ "plot_uncertain_cause" ] }, { "page": "save_epiportrait_figure", "title": "Save an epiPortrait Figure in Vector or Raster Format", "topics": [ "save_epiportrait_figure" ] }, { "page": "stitch_epi_peaks", "title": "Stitch Proximal Epigenetic Peaks", "topics": [ 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candidate-domain universe is required", "1.2 Consensus peaks from your peak-caller output", "1.3 Optionally stitch into macro-domains", "1.4 Build the portrait matrix", "Custom features", "Module 2: Normalization", "Module 3: Super-Domain Calling", "3.1 Inflection methods", "3.2 log-transform is optional", "3.3 Modes", "3.4 Cutting on breadth: peak-level Breadth-Super", "3.5 Combined taxonomy", "Module 4: Condition Transitions", "Module 5: Annotation & Visualization", "5.1 Domain-aware annotation", "5.2 Hockey-stick plot", "5.3 Single-domain feature profile", "5.4 PCA and correlation QC", "5.5 Result visualizations", "5.6 Saving and reusing an analysis", "5.7 Differential domain analysis on continuous signal", "5.8 Score-aware BEDPE/3D annotation", "5.9 Per-sample time-course transitions", "Module 6: Mark-Specific Interpretation", "6.1 H3K4me3: promoter breadth and transcriptional state", "6.2 H3K27ac: enhancer-domain magnitude versus regulatory territory", "6.3 H3K27me3 / H3K9me3: 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