On the public citation graph
Bayesian network analysis incorporating genetic anchors complements conventional Mendelian randomization approaches for exploratory analysis of causal relationships in complex data
0 signed · 67 inferred · view as graph
Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.
Is this your work? Sign in with ORCID and put your name on the
claims that are yours.
Reference health. See whether every reference in this work resolves to a
known work and none has been retracted — and get a dated CiteStamped
badge you can embed.
What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1002/gepi.21758openalex-snapshot
Mendelian Randomization Analysis With Multiple Genetic Variants Using Summarized Data
inferredcites →https://doi.org/10.1002/gepi.22061openalex-snapshot
A comparison of methods for inferring causal relationships between genotype and phenotype using additional biological measurements
inferredcites →https://doi.org/10.1002/gepi.22120openalex-snapshot
A multiple mediator analysis approach to quantify the effects of the ADH1B and ALDH2 genes on hepatocellular carcinoma risk
inferredcites →https://doi.org/10.1002/sim.3308openalex-snapshot
Is Mendelian randomization ‘lost in translation?’: Comments on ‘Mendelian randomization equals instrumental variable analysis with genetic instruments’ by Wehby et al.
inferredcites →https://doi.org/10.1002/sim.7221openalex-snapshot
A framework for the investigation of pleiotropy in two‐sample summary data Mendelian randomization
inferredcites →https://doi.org/10.1007/978-0-387-77318-6openalex-snapshot
Applied Econometrics with R
inferredcites →https://doi.org/10.1007/978-1-4612-2748-9openalex-snapshot
Causation, Prediction, and Search
inferredcites →https://doi.org/10.1007/978-1-4614-6446-4openalex-snapshot
Bayesian Networks in R: with Applications in Systems Biology
inferredcites →https://doi.org/10.1007/978-3-319-21296-8_3openalex-snapshot
Probabilistic Computational Causal Discovery for Systems Biology
inferredcites →https://doi.org/10.1007/s10654-015-0011-zopenalex-snapshot
Using published data in Mendelian randomization: a blueprint for efficient identification of causal risk factors
inferredcites →https://doi.org/10.1007/s10654-016-0149-3openalex-snapshot
Statistical tests, P values, confidence intervals, and power: a guide to misinterpretations
inferredcites →https://doi.org/10.1016/0270-0255(86)90088-6openalex-snapshot
A new approach to causal inference in mortality studies with a sustained exposure period—application to control of the healthy worker survivor effect
inferredcites →https://doi.org/10.1016/b978-0-08-051489-5.50008-4openalex-snapshot
BAYESIAN INFERENCE
inferredcites →https://doi.org/10.1016/j.ajhg.2011.11.029openalex-snapshot
Five Years of GWAS Discovery
inferredcites →https://doi.org/10.1016/j.jbi.2016.01.012openalex-snapshot
Generating a robust statistical causal structure over 13 cardiovascular disease risk factors using genomics data
inferredcites →https://doi.org/10.1038/d41586-018-01023-3openalex-snapshot
Robust research needs many lines of evidence
inferredcites →https://doi.org/10.1038/ijo.2010.137openalex-snapshot
C-reactive protein levels and body mass index: elucidating direction of causation through reciprocal Mendelian randomization
inferredcites →https://doi.org/10.1038/ncomms11122openalex-snapshot
Genome-wide study for circulating metabolites identifies 62 loci and reveals novel systemic effects of LPA
inferredcites →https://doi.org/10.1038/ng.2608openalex-snapshot
A meta-analysis identifies new loci associated with body mass index in individuals of African ancestry
inferredcites →https://doi.org/10.1038/ng.2795openalex-snapshot
Common variants associated with plasma triglycerides and risk for coronary artery disease
inferredcites →https://doi.org/10.1038/ng.2982openalex-snapshot
An atlas of genetic influences on human blood metabolites
inferredcites →https://doi.org/10.1038/ng.686openalex-snapshot
Association analyses of 249,796 individuals reveal 18 new loci associated with body mass index
inferredcites →https://doi.org/10.1038/s41467-018-05512-xopenalex-snapshot
Genome‐wide mapping of plasma protein QTLs identifies putatively causal genes and pathways for cardiovascular disease
inferredcites →https://doi.org/10.1038/s41467-019-10936-0openalex-snapshot
Mendelian randomization integrating GWAS and eQTL data reveals genetic determinants of complex and clinical traits
inferredcites →https://doi.org/10.1038/s41467-019-13870-3openalex-snapshot
Selecting likely causal risk factors from high-throughput experiments using multivariable Mendelian randomization
inferredcites →https://doi.org/10.1038/s41467-020-17117-4openalex-snapshot
Avoiding dynastic, assortative mating, and population stratification biases in Mendelian randomization through within-family analyses
inferredcites →https://doi.org/10.1038/s41586-018-0579-zopenalex-snapshot
The UK Biobank resource with deep phenotyping and genomic data
inferredcites →https://doi.org/10.1038/s41588-018-0099-7openalex-snapshot
Detection of widespread horizontal pleiotropy in causal relationships inferred from Mendelian randomization between complex traits and diseases
inferredcites →https://doi.org/10.1038/s41588-018-0255-0openalex-snapshot
Distinguishing genetic correlation from causation across 52 diseases and complex traits
inferredcites →https://doi.org/10.1038/srep43434openalex-snapshot
Untangling the role of one-carbon metabolism in colorectal cancer risk: a comprehensive Bayesian network analysis
inferredcites →https://doi.org/10.1080/00031305.2016.1154108openalex-snapshot
The ASA Statement on p -Values: Context, Process, and Purpose
inferredcites →https://doi.org/10.1093/aje/kwu283openalex-snapshot
Multivariable Mendelian Randomization: The Use of Pleiotropic Genetic Variants to Estimate Causal Effects
inferredcites →https://doi.org/10.1093/bioinformatics/bty769openalex-snapshot
Mixed graphical models for integrative causal analysis with application to chronic lung disease diagnosis and prognosis
inferredcites →https://doi.org/10.1093/bioinformatics/btz285openalex-snapshot
Multi-SNP mediation intersection-union test
inferredcites →https://doi.org/10.1093/hmg/ddu328openalex-snapshot
Mendelian randomization: genetic anchors for causal inference in epidemiological studies
inferredcites →https://doi.org/10.1093/hmg/ddy163openalex-snapshot
Evaluating the potential role of pleiotropy in Mendelian randomization studies
inferredcites →https://doi.org/10.1093/hmg/ddy210openalex-snapshot
Systematic Mendelian randomization framework elucidates hundreds of CpG sites which may mediate the influence of genetic variants on disease
inferredcites →https://doi.org/10.1093/ije/30.1.1openalex-snapshot
Epidemiology—is it time to call it a day?
inferredcites →https://doi.org/10.1093/ije/dyg070openalex-snapshot
‘Mendelian randomization’: can genetic epidemiology contribute to understanding environmental determinants of disease?*
inferredcites →https://doi.org/10.1093/ije/dyr207openalex-snapshot
Cohort Profile: TwinsUK and Healthy Ageing Twin Study
inferredcites →https://doi.org/10.1093/ije/dyr233openalex-snapshot
Two-step epigenetic Mendelian randomization: a strategy for establishing the causal role of epigenetic processes in pathways to disease
inferredcites →https://doi.org/10.1093/ije/dyu176openalex-snapshot
Network Mendelian randomization: using genetic variants as instrumental variables to investigate mediation in causal pathways
inferredcites →https://doi.org/10.1093/ije/dyv080openalex-snapshot
Mendelian randomization with invalid instruments: effect estimation and bias detection through Egger regression
inferredcites →https://doi.org/10.1093/ije/dyw314openalex-snapshot
Triangulation in aetiological epidemiology
inferredcites →https://doi.org/10.1093/ije/dyx028openalex-snapshot
Two-sample Mendelian randomization: avoiding the downsides of a powerful, widely applicable but potentially fallible technique
inferredcites →https://doi.org/10.1093/ije/dyy262openalex-snapshot
An examination of multivariable Mendelian randomization in the single-sample and two-sample summary data settings
inferredcites →https://doi.org/10.1101/476085openalex-snapshot
MR-TRYX: A Mendelian randomization framework that exploits horizontal pleiotropy to infer novel causal pathways
inferredcites →https://doi.org/10.1136/bmj.k601openalex-snapshot
Reading Mendelian randomisation studies: a guide, glossary, and checklist for clinicians
inferredcites →https://doi.org/10.1146/annurev-genom-090314-050016openalex-snapshot
Mendelian Randomization: New Applications in the Coming Age of Hypothesis-Free Causality
inferredcites →https://doi.org/10.1159/000078209openalex-snapshot
An integrative genomics approach to the reconstruction of gene networks in segregating populations
inferredcites →https://doi.org/10.1177/0962280206077743openalex-snapshot
Mendelian randomization as an instrumental variable approach to causal inference
inferredcites →https://doi.org/10.1177/0962280215597579openalex-snapshot
A review of instrumental variable estimators for Mendelian randomization
inferredcites →https://doi.org/10.1201/9781420011579.ch23openalex-snapshot
Estimation of the causal effects of time-varying exposures
inferredcites →https://doi.org/10.1371/journal.pbio.1001301openalex-snapshot
Stitching together Multiple Data Dimensions Reveals Interacting Metabolomic and Transcriptomic Networks That Modulate Cell Regulation
inferredcites →https://doi.org/10.1371/journal.pgen.1007081openalex-snapshot
Orienting the causal relationship between imprecisely measured traits using GWAS summary data
inferredcites →https://doi.org/10.1371/journal.pone.0195719openalex-snapshot
Evaluation of the relationship between plasma lipids and abdominal aortic aneurysm: A Mendelian randomization study
inferredcites →https://doi.org/10.18637/jss.v008.i20openalex-snapshot
deal: A Package for Learning Bayesian Networks
inferredcites →https://doi.org/10.2337/db15-0996openalex-snapshot
DNA Methylation and BMI: Investigating Identified Methylation Sites at HIF3A in a Causal Framework
inferredcites →https://doi.org/10.3389/fgene.2019.00460openalex-snapshot
Learning Causal Biological Networks With the Principle of Mendelian Randomization
inferredcites →https://doi.org/10.4238/gmr.15038987openalex-snapshot
Detecting the potential cancer association or metastasis by multi-omics data analysis
inferredcites →https://doi.org/10.48550/arxiv.1212.2468openalex-snapshot
Large-Sample Learning of Bayesian Networks is NP-Hard
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1016/j.ijrobp.2020.04.015openalex-snapshot
Gut Microbiome Composition Is Associated with a Pathologic Response After Preoperative Chemoradiation in Patients with Rectal Cancer
inferred← citeshttps://doi.org/10.1038/s41467-021-26970-wopenalex-snapshot
Simultaneous estimation of bi-directional causal effects and heritable confounding from GWAS summary statistics
inferred← citeshttps://doi.org/10.1186/s12859-020-03753-6openalex-snapshot
Differential gene regulatory pattern in the human brain from schizophrenia using transcriptomic-causal network
Editorial review for independent work. ICSAC — the Institute for Complexity
Science and Advanced Computing — runs a structured editorial panel for researchers
publishing outside journals, and publishes on CiteStamp rails. Submission is free
and goes through ORCID: icsacinstitute.org/submit.