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stat.ME2022
Bayesian Mendelian randomization testing of interval causal null hypotheses: ternary decision rules and loss function calibration
Linyi Zou, Teresa Fazia, Hui Guo +1
Our approach to Mendelian Randomization (MR) analysis is designed to increase reproducibility of causal effect "discoveries" by: (i) using a Bayesian approach to inference; (ii) re…
q-bio.MN2022
Discovery methods for systematic analysis of causal molecular networks in modern omics datasets
Jack Kelly, Carlo Berzuini, Bernard Keavney +2
With the increasing availability and size of multi-omics datasets, investigating the casual relationships between molecular phenotypes has become an important aspect of exploring u…