4 papers
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…
Overlapping-sample Mendelian randomisation with multiple exposures: A Bayesian approach
Linyi Zou, Hui Guo, Carlo Berzuini
Background: Mendelian randomization (MR) has been widely applied to causal inference in medical research. It uses genetic variants as instrumental variables (IVs) to investigate pu…
Mendelian Randomization with Incomplete Exposure Data: a Bayesian Approach
Teresa Fazia, Leonardo Egidi, Burcu Ayoglu +9
We expand Mendelian Randomization (MR) methodology to deal with randomly missing data on either the exposure or the outcome variable, and furthermore with data from nonindependent…
Bayesian Mendelian Randomization identifies disease causing proteins via pedigree data, partially observed exposures and correlated instruments
Teresa Fazia, Leonardo Egidi, Burcu Ayoglu +7
Background In a study performed on multiplex Multiple Sclerosis (MS) Sardinian families to identify disease causing plasma proteins, application of Mendelian Randomization (MR) met…