Article

ICONIC: An R Package for Integrating Instrumental Variable- and Negative-Control-Informed Causal Discovery and Diagnostics in Multiomic Studies

2026-08-31

Abstract excerpt

Unmeasured confounding threatens causal inference and replicability in observational multi-omic studies across variable environments. Genetic instrumental variables (Mendelian randomization) and negative-control calibration each address complementary sources of unmeasured confounding, yet no existing framework unifies them for omics-scale mediation analysis. We introduce ICONIC, an R package that embeds genetic in...

Identifiers and source

Literature Corpus work: 1eaeddb5-55a7-53f3-80e5-31f98431908e
DOI: 10.64898/2026.08.26.26361466

Open publication

Related research

Semantic proximity does not establish scientific evidence. Graph snapshot: 2026-09-29.

Click a neighbor to travelStep 1 · 12 closest

ICONIC: An R Package for Integrating Instrumental Variable- and Negative-Control-Informed Causal Discovery and Diagnostics in Multiomic StudiesDOI 10.64898/2026.08.26.26361466Read

Causal inference for multiple risk factors and diseases from genomics data.Semantic proximity Read

Quantifying mediation between omics layers and complex traitsSemantic proximity Read

Uncovering causal relationships in single-cell omic studies with causarraySemantic proximity Read

A Robust Method Uncovers Significant Context-Specific Heritability in Diverse Complex Traits.Semantic proximity Read

Essential Regression - a generalizable framework for inferring causal latent factors from multi-omic human datasetsSemantic proximity Read

A flexible and unified framework for single- and multi-outcome Mendelian randomization using summary statistics.Semantic proximity Read

Causal inference for multiple risk factors and diseases from genomics dataSemantic proximity Read

Direct causal variable discovery leveraging the invariance principle: application in biomedical studiesSemantic proximity Read

METEOR: a data-adaptive Mendelian randomization method for powerful detection of shared and specific exposures underlying multiple outcomes.Semantic proximity Read

High-dimensional confounding in causal mediation: a comparison study of double machine learning and regularized partial correlation networkSemantic proximity Read

Causal Inference Methods to Integrate Omics and Complex Traits.Semantic proximity Read

An integrative multi-context Mendelian randomization method for identifying risk genes across human tissuesSemantic proximity Read