Blog

Date Title Description
Dec 4, 2018 7 Tips for making presentations We’ve compiled some quick tips that our lab finds useful when putting together presentations!
March 13, 2018 Identifying causal paths from SNP to chromatin to gene expression (Pathfinder) A paper recently published in our lab by Roytman et al. “Methods for fine-mapping with chromatin and expression data” presents a fine-mapping framework which computes posterior probabilities for causal paths from SNP to gene expression through chromatin.
March 05, 2018 Finding genes associated with disease through multiple-trait-colocalization (MOLOC) MOLOC, a method recently developed in our lab by Giambartolomei et al. (A Bayesian Framework for Multiple Trait Colocalization from Summary Association Statistics) integrates GWAS summary data with molecular phenotypes such as gene expression (expression QTL or eQTL) and DNA methylation (methylation QTL or mQTL).
February 16, 2018 Explaining Missing Heritability Using Gaussian Process Regression (Reader’s Digest) The paper “Explaining Missing Heritability Using Gaussian Process Regression” by Sharp et al. tries to tackle the problem of missing heritability and the detection of higher-order interaction effects through Gaussian process regression, a technique widely used in the machine learning community.
February 08, 2018 Insights from ‘zooming in’ to look at Local Genetic Correlation using Summary Statistics (ρ-HESS) Rho-HESS, a method recently developed in our lab by Shi et al. 2017 (Local genetic correlation gives insights into the shared genetic architecture of complex traits), quantifies the correlation between pairs of traits due to genetic variation at a small region in the genome.
February 02, 2018 Tips for Formatting A Lot of GWAS Summary Association Statistics Data This page aims to provide some tips, guidelines, and protocols that I find useful for formatting a lot of GWAS summary statistics data to help prevent pitfalls in post-GWAS analyses.
January 25, 2018 Visualizing fine-mapping studies with CANVIS CANVIS is a command line tool that generates publication-ready figures within ~30-60 seconds and is great for providing a visual summary of an integrative fine-mapping experiment.