{ "_id": "6ab40e193d719c1f84094111", "Package": "exposomeSC", "Title": "Single-Cell Exposome-Wide Association Studies with Cross-Omic\nNetwork Inference", "Version": "0.99.1", "Authors@R": "person(given = \"Cuiwei\",\nfamily = \"Gao\",\nemail = \"48gaocuiwei@gmail.com\",\nrole = c(\"aut\", \"cre\"))", "Description": "A framework for cell-type-specific exposome-wide\nassociation studies (sc-ExWAS) that bridges donor-level\nenvironmental exposures with single-cell resolution gene\nexpression. The package extends SingleCellExperiment to store\nexposure measurements alongside transcriptomic data, and\nimplements donor-level raw-count pseudobulk inference to avoid\ncellular pseudoreplication (Squair et al. 2021\n). The default workflow uses\nrobust edgeR quasi-likelihood models, exposure-independent\nexpression-support filtering, complete-transcriptome offsets,\ndesign-rank diagnostics, and global multiplicity correction.\nAdditional modules support dose-response modelling, exposure\nmixtures, cross-cohort synthesis, and cell-level gene-protein\ncoupling. Exploratory decomposition and mediation utilities\nreport model-based associations; they do not by themselves\nidentify causal effects.", "License": "Artistic-2.0", "Config/testthat/edition": "3", "biocViews": "SingleCell, GeneExpression, DifferentialExpression,\nTranscriptomics, CellBiology, StatisticalMethod, Network,\nNetworkInference, Regression", "URL": "https://github.com/CuiweiG/exposomeSC", "BugReports": "https://github.com/CuiweiG/exposomeSC/issues", "Encoding": "UTF-8", "RoxygenNote": "7.3.3", "VignetteBuilder": "knitr", "Collate": "'AllClasses.R' 'AllGenerics.R' 'below-lod.R' 'build-scee.R'\n'bridge.R' 'utils.R' 'causal-mediation.R' 'cell-coupling.R'\n'composition.R' 'data-docs.R' 'dose-response.R' 'enrichment.R'\n'erd-interventional.R' 'exposomeSC-package.R' 'gam-dr.R'\n'glmm-inference.R' 'iers.R' 'interaction.R' 'mediation.R'\n'meta-analysis.R' 'methods.R' 'mixture.R' 'sc-exwas.R'\n'multi-exwas.R' 'network-utils.R' 'network-build.R'\n'network-compare.R' 'network-differential.R'\n'network-mediation.R' 'network-plots.R' 'network-simulate.R'\n'network-temporal.R' 'power.R' 'qgcomp-mixture.R' 'spatial.R'\n'state-coupling.R'", "Config/pak/sysreqs": "zlib1g-dev", "Repository": "https://biocstaging.r-universe.dev", "Date/Publication": "2026-09-23 11:56:39 UTC", "RemoteUrl": "https://github.com/BiocStaging/exposomeSC", "RemoteRef": "HEAD", "RemoteSha": "349221639c2f7d246a61c527939db1e69c58d5d4", "NeedsCompilation": "no", "Packaged": { "Date": "2026-09-23 17:24:14 UTC", "User": "root" }, "Author": "Cuiwei Gao [aut, cre]", "Maintainer": "Cuiwei Gao <48gaocuiwei@gmail.com>", "_user": "biocstaging", "_type": "src", "_file": "exposomeSC_0.99.1.tar.gz", "_fileid": "https://r2.ropensci.org/9ff65933351510c983831ad47286a4ced2d33e5bf4ddd06dcacf1a3943c49976", "_filesize": 1244900, "_sha256": "9ff65933351510c983831ad47286a4ced2d33e5bf4ddd06dcacf1a3943c49976", "_expires": "2027-01-01T17:36:23.000Z", "_created": "2026-09-23T17:24:14.000Z", "_published": "2026-09-23T17:36:25.103Z", "_bioccheck": { "error": 0, "warning": 0, "note": 7 }, "_host": "GitHub-Actions", "_buildurl": "https://github.com/r-universe/biocstaging/actions/runs/35894775637", "_status": "success", "_upstream": "https://github.com/BiocStaging/exposomeSC", "_commit": { "id": "349221639c2f7d246a61c527939db1e69c58d5d4", "author": "CuiweiG <48gaocuiwei@gmail.com>", "committer": "CuiweiG <48gaocuiwei@gmail.com>", "message": "fix: keep the slope-heterogeneity test estimable when a variance component is zero\n\nThe first Bioconductor build of 0.99.0 failed on both macOS platforms\nand nowhere else: test-coupling-examples.R expected a finite p-value\nfrom run_state_coupling()'s slope-heterogeneity test and got NA. The\ntest fits one multilevel meta-regression over all donor-by-bin\ncorrelations, with a random donor effect and a residual term. For the\nexample data both variance components are estimated at zero, and\nwhether nlminb stops there cleanly depends on the platform: it did on\nLinux and Windows, and on macOS metafor raised its non-convergence\nerror, which the tryCatch turned into \"not estimable\".\n\nThe fit now tries nlminb, then optim with BFGS, then optim with\nNelder-Mead, and keeps the first result whose coefficients are all\nfinite. If the F-test's coefficient covariance is still unusable, the\nsame question is put as a likelihood-ratio test between the full and\nthe additive model, both fitted by maximum likelihood, which needs no\ncovariance. The method field of the slope_heterogeneity attribute\nnames the test that was used, and the documentation says so. The test\nnow also checks that the statistic is finite and the p-value lies in\n[0, 1].\n\nVersion 0.99.1.\n", "time": 1790164599 }, "_maintainer": { "name": "Cuiwei Gao", "email": "48gaocuiwei@gmail.com", "login": "cuiweig", "mastodon": "@cuiweigao@mastodon.social", "twitter": "@CuiweiG23", "description": "R package developer · Biostatistics · Mechanical engineering · Data analysis", "uuid": 199837382 }, "_distro": "resolute", "_jobs": [ { "job": 107298027079, "time": 236, "config": "bioc-checks", "r": "4.6.1", "check": "NOTE", "artifact": "10767346473" }, { "job": 107298027042, "time": 446, "config": "linux-devel-x86_64", "r": "4.7.0", "check": "OK", "artifact": "10767411163" }, { "job": 107298027113, "time": 448, "config": "linux-release-x86_64", "r": "4.6.1", "check": "OK", "artifact": "10766478249" }, { "job": 107298027162, "time": 222, "config": "macos-oldrel-arm64", "r": "4.5.3", "check": "OK", "artifact": "10766738541" }, { "job": 107298027111, "time": 250, "config": 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