Explore a comprehensive lecture on inferring causal cell types driving human disease and complex traits in this Medical and Population Genetics Primer. Delve into the integration of genome-wide association studies (GWAS) with functional genomics data to identify disease-associated cell types. Learn about colocalization of expression quantitative trait loci (eQTLs) with GWAS variants and its importance in implicating disease-critical genes and tissues. Discover the concept of transcriptome-wide association studies (TWAS) and their role in performing polygenic colocalization of genes with diseases. Examine the Tissue-Corrected Score Causal (TCSC) method, its power, calibration, and application to real gene expression and trait data. Gain insights into visualizing multivariate regression in TCSC and understand the importance of eQTL sample size in trait analyses. Explore how TCSC identifies causal tissue-trait pairs and performs under violated model assumptions. Learn how to get started with TCSC and access relevant data through the TCSC Repository.
Inferring Causal Cell Types Driving Human Disease and Complex Traits - MPG Primer 2023
Overview
Syllabus
Intro
Disease-associated cell types can be identified by integrating GWAS with functional genomics data
Colocalization of eQTLs with GWAS variants can implicate disease-critical genes and tissues
This is analogous to the need for fine-mapping GWAS variants
We want a method that can identify the causal tissues among many tagging tissues
Transcriptome-wide association studies (TWAS) perform polygenic colocalization of genes with disease
TWAS association statistics are proportional to the amount of tagged causal effects due to co-regulation
Co-regulation across tissues and genes can be estimated using gene expression prediction models and a reference panel
Visualization of multivariate regression in TCSC
TCSC is powerful, well-calibrated, and unbiased in simulations
TCSC power is modest but can improve by modifying certain parameters
eQTL sample size is an important consideration for real trait analysis
Applying TCSC to real gene expression and trait data
TCSC identifies causal tissue-trait pairs
TCSC performs well when model assumptions are violated
Getting started with TCSC
Data access provided on the TCSC Repo
Taught by
Broad Institute
