No packages match

dmsa - Directional Methylation Set Analysis

Aligns probe-level methylation effects to their predicted effect on gene expression and, for system-level analysis, to each gene's curated polarity with respect to the system's activation tone (e.g. NR3C1 opposes HPA-axis activation). Pools the aligned coefficients with fixed-sign or expected-sign estimators and reports coverage and activation/brake balance per set. Ships the Project Alpha gene-system map, a gene-to-system polarity table carrying a stated source and review flag on every row, and a curated system > module > gene > probe selection cascade whose module labels carry literature-audited evidence tiers and citations; genes without a polarity entry must be specified by the user.

Last updated

dnamethylationdifferentialmethylationmethylationarraygenesetenrichmentgeneexpressionepigeneticsmicroarraycoveragestatisticalmethodmultiplecomparisonregressionsoftware

3.70 score

cpgdirectionData - Data Layers for the cpgdirection Package (ExperimentHub)

ExperimentHub companion to the cpgdirection package. Serves the eight data layers too large to ship inside a Bioconductor software package: the three tissue catalogue lookup tables (blood, nasal epithelium, solid tissue; hg19), the SMR causal-direction table, the EPIC v2 hg19 probe positions, the brain SMR directions, the genome-wide saliva bridge scores, and the multi-source EPIC v2 probe-to-gene annotation (five cross-validated annotation tracks with per-track support flags). Each resource is a serialized data.frame retrieved from ExperimentHub on first use and cached locally thereafter. The cpgdirection package consumes these resources transparently; direct use is possible through the accessors documented here.

Last updated

experimentdataexperimenthubhomo_sapiens_datamicroarraydatamethylationarraydatatissuemicroarraydatatissuegenome

3.48 score 1 dependents

cpgdirection - Predict the Direction of CpG-Gene Expression Associations

Assigns a direction to the association between DNA methylation at a CpG site and the expression of a nearby gene, for CpGs that have no measured expression quantitative trait methylation (eQTM) record. Predictions come from a precomputed table of 3,105,697 CpG-gene pairs covering 761,445 CpGs, assembled from four sources of evidence: directly measured eQTMs, summary-data Mendelian randomisation using genetic instruments, gradient-boosted models of genomic context and local catalogue structure fitted separately in blood, nasal epithelium and solid tissue, and a distance prior. Each call returns a direction, a calibrated probability, an evidence tier and an expected accuracy, and abstains where the evidence is insufficient. Predictions estimate direction conditional on the CpG being an eQTM; they do not establish that an effect exists.

Last updated

dnamethylationgeneexpressiongeneregulationgenetargetepigeneticsannotation

3.40 score

tewas - Unit-Level Multiple Testing for Epigenome-Wide Association Studies with an Anchor-Calibrated Knowledge Prior

A multiple-testing engine for DNA methylation arrays (engine v1.6) and a frame layer for the designs of behavioral epigenetics. Probes are grouped into genomic-run units; each unit is tested with four complementary statistics (dense sum, coherence-gated flip, Simes, kernel matched filter) whose null distributions come from one shared permutation stream with a calibrated exponential tail below the permutation floor; the arm p-values are combined by the Cauchy combination and units are selected by weighted Benjamini-Hochberg with cross-fitted structural weights and, optionally, a per-probe knowledge prior from longitudinal within-person change measured in an external cohort. Anchor probes carried in the scan measure whether the prior is licensed (the lens) and whether the scan's null is calibrated (the inflation guard, read on an alive null ruler); the prior is tempered toward zero when it is not, and nothing is corrected. The frame layer declares a design (moderation, curvature, threshold, acceleration, methylation as predictor or as outcome), runs every arm through the same engine, merges selected units into regions with coordinates, annotates the probes with their target genes, and writes tables, trajectory figures and a self-declaring summary. Unit-level FDR is controlled under the stated assumptions; probe-level false discovery and the calibration of every arm were measured in registered simulations whose readings the package prints beside its results. The anchor panel and the alive ruler are shipped under inst/extdata as per-probe summaries only. Input is a beta matrix or a SummarizedExperiment (a minfi GenomicRatioSet included); selected regions, units and probes are returned as GRanges on request.

Last updated

dnamethylationmethylationarrayepigeneticsmultiplecomparisonstatisticalmethoddifferentialmethylationgeneregulationsoftware

2.70 score