A fast and efficient colocalization algorithm for identifying shared genetic risk factors across multiple traits

Objectives: The overarching goal was to employ statistical colocalization as a means to elucidate the causal genes and underlying mechanisms implicated in complex diseases. This objective involved bridging the gap between genome-wide association studies (GWAS) and biological interpretations by prioritizing variants likely to be causal, assessing genetic overlap among related traits, and discerning the presence… Continue reading A fast and efficient colocalization algorithm for identifying shared genetic risk factors across multiple traits

MR-Clust: clustering of genetic variants in Mendelian randomization with similar causal estimates

Objectives: The research aimed to utilize Mendelian randomization (MR) as a robust epidemiological technique to investigate and estimate causal relationships between specific risk factors and their resultant outcomes. This study sought to leverage genetic variants as instrumental variables to provide a reliable framework for understanding the underlying causal mechanisms of various health conditions. Ultimately, the… Continue reading MR-Clust: clustering of genetic variants in Mendelian randomization with similar causal estimates