Chapter 8: Post-GWAS Bioinformatics
Chapter goals:
Be able to define SNP heritability and understand how it is calculated
Understand the concept of “missing” heritability and explanations for why it is “missing”
Understand methods of determining genetic overlap through calculations of genetic correlation
Understand methods for performing gene-trait association tests, and methods for defining gene sets and gene set enrichment.
Understand the concept of fine-mapping and tools for performing fine-mapping of GWAS loci.
Be able to define expression quantitative trait loci (eQTL) and methods for eQTL detection.
Understand conceptually transcriptome- and phenome-wide association studies and methods for performing them.
8.1 SNP Heritability
In this video by Dr. Price, we get a comprehensive overview of heritability, as defined through twin studies and SNP heritability as defined with genetic analyses. The video touches on the idea of “missing” heritability, with a comprehensive delve into possible explanations for missing heritability, and how to measure heritability through different methods.
Title: Heritability and SNP Heritability
Presenter(s): Alkes Price, PhD (Department of Epidemiology, Harvard School of Public Health)
Level: Intermediate
Length: 56:27
Link to video transcript here. Tradução para o português disponível aqui.
8.2 Genetic Correlations and Partitioned LDSC
In this video, Dr. Turley gives a brief introduction into the concept of genetic overlap and methods of estimating the relationship of two traits through genetic correlation.
Title: Genetic Correlation and Partitioning
Presenter(s): Patrick Turley, PhD (Analytic and Translational Genetics Unit, The Broad Institute of Harvard and MIT)
Level: Beginner friendly
Length: 12:11
Link to video transcript here. Tradução para o português disponível aqui.
8.3 Gene association analysis
In the first video, Dr. Posthuma gives a brief introduction to gene set annotation and pathway analysis with the MAGMA tool, discussing the various models and analyses that can be implemented with MAGMA. In the second video, Dr. Watanabe gives an introduction to the FUnctional Mapping and Annotation (FUMA) tool for annotating GWAS results: connecting SNPs to genes and then genes to functional annotations.
MAGMA
Title: How do we go from genetic discoveries from GWAS/WGS/WES to mechanistic disease insight?
Presenter(s): Danielle Posthuma, PhD (Department of Complex Trait Genetics, Vrije Universiteit Amsterdam)
Level: Beginner friendly
Length: 9:53
Link to video transcript here. Tradução para o português disponível aqui.
Link to MAGMA software download and tutorial.
FUMA
Title: FUMA: Functional mapping and annotation of genetic associations
Presenter(s): Kyoko Watanabe, PhD (Regeneron)
Level: Beginner friendly
Length: 14:19
Link to video transcript here. Tradução para o português disponível aqui.
Link to FUMA Website, GitHub, and Tutorial.
8.4 Gene Set Analysis
This video by Dr. Posthuma is the same from Section 8.3, giving an overview of gene set analysis in MAGMA.
Title: How do we go from genetic discoveries from GWAS/WGS/WES to mechanistic disease insight?
Presenter(s): Danielle Posthuma, PhD (Department of Complex Trait Genetics, Vrije Universiteit Amsterdam)
Level: Beginner friendly
Length: 9:53
Link to video transcript here.
8.5 Fine-Mapping
In this video, Dr. Finucane gives a comprehensive introduction to fine-mapping of genetic loci to determine potential causal variants, including discussing posterior inclusion probabilities (PIPs) and credible sets, and gives examples of different fine-mapping methods such as FINEMAP, SuSiE, Caviar, and DAP-G.
Title: Introduction to fine-mapping methods
Presenter(s): Hilary Finucane, PhD (Broad Institute of Harvard and MIT)
Level: Beginner/Intermediate
Length: 52:12
Link to video transcript here.
8.6 Quantitative Trait Loci (QTLs)
Goals of this section:
Be able to define GWAS and understand the general genetic architecture of common risk variants
Be able to define an eQTL (Expression Quantitative Trait Loci) and how they may be useful to interpreting GWAS results
Obtain a solid understanding of eQTLs and related analytical approaches.
Examine the role of eQTLs in the relationship of genes and molecular networks with phenotypic QTLs (pQTLs).
Understand eQTLs for co-expression networks.
This first short video by Dr. Liu briefly reviews GWAS studies and the GWAS catalog resource in order to discuss a main caveat of GWAS - that most significant trait associated variants lay in non-coding regions of the genome with putative regulatory function. The video then presents expression quantitative trait loci (eQTLs) as a method to connect SNPs to gene regulatory effects in a tissue-specific manner.
The second video by Dr. Auget introduces expression quantitative trait loci (eQTL) analysis, discusses how to address batch effects and covariate correction, and control for false discovery rate.
The third video by Dr. Saba explains the concepts of transcriptome-wide association studies, gene expression prediction related to phenotypes of interest, and accompanying statistical tests.
In the fourth video, Drs. O’Connor and Weiner discuss the relevance of gene regulation in GWAS, explains transcriptome-wide association studies and co-localization of GWAS with eQTLs as methods to link SNPs to gene expression and trait associations, discusses proximity and the abstract mediation model, and covered combining multiple SNP-to-gene strategies based on the Nature Genetics Publication: “Combining SNP-to-gene linking strategies to identify disease genes and assess disease omnigenicity”.
Title: GWAS Studies and eQTL Analysis
Presenter(s): Xiaole Shirley Liu, PhD (GV20 Therapeutics)
Level: Beginner
Length: 14:23
Link to video transcript here.
TItle: MPG Primer: Introduction to expression quantitative trait loci (2021).
Presenter(s): Francois Auget, PhD (Illumina’s Artificial Intelligence Laboratory)
Level: intermediate (the content will be easier to follow by those who already went through some introductory materials on GWAS and gene expression)
Length: 52:43
Link to video transcript here.
Title: Introduction to expression (e)QTL & their role in connecting QTL to genes and molecular networks.
Presenter(s): Laura Saba, PhD (Department of Pharmaceutical Sciences, University of Colorado)
Level: Intermediate (the content will be easier to follow by those who already went through some introductory materials on GWAS and gene expression)
Length: 1:26:43 ***Please note that the audio cuts out for approximately 3 minutes starting at minute 5.
Link to video transcript here.
Title: Linking SNPs with genes in GWAS.
Presenter(s):
Luke O’Connor, PhD (Department of Biomedical Informatics, Harvard Medical School)
Dan Weiner, PhD (Broad Institute of Harvard and MIT)
Level: Intermediate (the content will be easier to follow by those who already went through some introductory materials on GWAS and gene expression)
Length: 47:52
Link to video transcript here.
8.7 TWAS
In the following videos, we will explore Transcriptome-Wide Association Studies, or TWAS, including various TWAS methods. In the first video, Dr. Gusev explains the concepts of transcriptome-wide association studies, gene expression prediction related to phenotypes of interest, and accompanying statistical tests. In the second video, Dr. Gusev provides a tutorial for conducting a TWAS, using FUSION software.
Title: Understanding GWAS mechanisms with Transcriptome-Wide Association Studies
Presenter(s): Sasha Gusev, PhD (Dana-Farber Cancer Institute, Harvard Medical School)
Level: Intermediate (the content will be easier to follow by those who already went through some introductory materials on GWAS and gene expression)
Length: 41:01
Link to video transcript here.
Title: PGC TWAS Primer
Presenter(s): Sasha Gusev, PhD (Dana-Farber Cancer Institute, Harvard Medical School)
Level: Beginner to Intermediate
Length: 16:39
Link to video transcript here.
Link to FUSION TWAS website.
8.8 PheWAS
The following videos provide an overview of the Phenone-Wide Association Study (PheWAS). The first video by Dr. Denny talks about how PheWAS and GWAS could work in concert with each other and what data are used for the phenome. After 9:45, Dr. Josh Denny pivots the focus from PheWAS to phenotypic risk score (PheRS). In the second video, Dr. Davis gives an example of PheWAS and how to interpret the PheWAS results (starting 28:15). Note: There is no current video on Laboratory-Wide Association Studies (LabWAS) yet, but the concept is similar to PheWAS and in this Youtube video, Dr. Lea Davis talked briefly on the QC of the lab results in the BioVU Biobank (starting 39:00).
Title: PheWAS: Discovering gene-disease associations
Presenter(s): Joshua Denny, MD, MS (All of Us Research Program)
Level: Intermediate
Length: 13:40
Link to video transcript here.
Title: Using EHR-based genomic approaches to understand the relationship between mental and physical health
Presenter(s): Lea Davis, PhD (Department of Medicine, Vanderbilt University Medical Center)
Level: Intermediate
Length: 58:40
Link to video transcript here.