Webinar #01 - Introduction to Quantitative Trait Loci (QTL) Analysis

Friday, May 8th, 2020
10am PDT/ 11am MDT/ 12pm CDT/ 1pm EDT

Goals of this webinar (trait variance to QTL):

• Define quantitative trait locus (QTL)
• Explain how genome scans can help find QTL

Presented by:
Dr. Saunak Sen
Professor and Chief of Biostatistics
Department of Preventative Medicine
University of Tennessee Health Science Center

Link to course material

Webinar #02 - Mapping Addiction and Behavioral Traits and Getting at Causal Gene Variants with GeneNetwork

Friday, May 22nd. 2020 10am PDT/ 11am MDT/ 12pm CDT/ 1pm EDT

Goals of this webinar (QTL to gene variant):

• Demonstrate mapping a quantitative trait using GeneNetwork (GN)
• Explore GN tools to identify genes and genetics variants related to a QTL

Presented by:
Dr. Rob Williams
Professor and Chair
Department of Genetics, Genomics, and Informatics
University of Tennessee Health Science Center

Link to course material

Webinar #03 - Introduction to expression (e)QTL and their role in connecting QTL to genes and molecular networks

Friday, June 12, 2020 10am PDT/ 11am MDT/ 12pm CDT/ 1pm EDT

Goals of this webinar (QTL to gene/molecular networks):

• Define eQTL
• Examine the role of eQTL in the relationship of genes and molecular networks with phenotypic QTL
• eQTL for co-expression networks

Presented by:
Dr. Laura Saba
Associate Professor
Department of Pharmaceutical Sciences
University of Colorado Anschutz Medical Campus

Webinar flyer (pdf)
Link to course material

Webinar #04 - From Candidate Genes to Causal Variants—Strategies for and Examples of Identifying Genes and Sequence Variants in Rodent Populations

Friday, June 26, 2020 10am PDT/ 11am MDT/ 12pm CDT/ 1pm EDT

Goals of this webinar (candidate genes to causal variants):

• To understand when it is practical or (just as often) not practical to try to "clone" the gene or nucleotide variant modulating trait variants
• To understand that defining the crucial causal nucleotide variant is usually a bonus and often not for the translational or even mechanistic utility of discoveries.
• To review new sequence-based methods to identify common and rare variants—the reduced complexity cross and epoch-effects in reference populations

Presented by:
Dr. Rob Williams
Professor and Chair
Department of Genetics, Genomics, and Informatics
University of Tennessee Health Science Center

Link to course material
Link to course material in powerpoint pptx: [P30_Webinar_on_QTGenes_26Jun2020v3.pptx]

Webinar #05 - Identifying genes from QTL using RNA expression and the PhenoGen website (http://phenogen.org)

Friday, August 28, 2020 10am PDT/ 11am MDT/ 12pm CDT/ 1pm EDT
1-hour presentation followed by 30 minutes of discussion

Goals of this webinar (candidate genes to causal variants):

Demonstrate how to use the PhenoGen website to identify transcripts:

• Physically located within a QTL
• Physically located within a QTL and expressed in brain
• With a brain cis eQTL within the QTL
• With any brain eQTL within the QTL
• Within a co-expression network controlled from the same region as the QTL

Presented by:
Dr. Laura Saba
Associate Professor
Department of Pharmaceutical Sciences
University of Colorado Anschutz Medical Campus

Link to course material

Webinar #06 - Sex as a Biological Covariate in QTL Studies

Friday, September 11th, 2020 10am PDT/ 11am MDT/ 12pm CDT/ 1pm EDT
1-hour presentation followed by 30 minutes of discussion

Goals of this webinar (trait variance to QTL):

• Review QTL mapping
• Understand the role of sex in QTL study design
• Use sex as a covariate in QTL analysis
• Understand X chromosome segregation in crosses
• Make adjustments for X chromosome in QTL analysis

Presented by:
Dr. Saunak Sen
Professor and Chief of Biostatistics
Department of Preventative Medicine
University of Tennessee Health Science Center

Link to course material

Webinar #07 - Introduction to Weighted Gene Co-expression Network Analysis

Friday, September 25th at 10am PDT/ 11am MDT/ 12pm CDT/ 1pm EDT
1-hour presentation followed by 30 minutes of discussion

Goals of this webinar (molecular networks):

• Introduction and motivation for co-expression network analysis
• Basics of weighted gene co-expression network analysis
• Step-by-step guide to WGCNA using the wgcna package in R.

Background reading available at: http://bit.ly/osga_wgcna

Presented by:
Dr. Laura Saba
Associate Professor
Department of Pharmaceutical Sciences
University of Colorado Anschutz Medical Campus

Link to course material

Webinar #08 - Using genetic and non-genetic covariates in QTL studies

Friday, October 9th at 10am PDT/ 11am MDT/ 12pm CDT/ 1pm EDT
1-hour presentation followed by 30 minutes of discussion

Goals of this webinar (quantitative trait to genetic loci):

• Identify covariates and mediators in QTL studies
• Adjust for covariates in QTL scans
• Review genetic relatedness in segregating populations
• Adjust for genetic relatedness using linear mixed models

Presented by:
Dr. Saunak Sen
Professor and Chief of Biostatistics
Department of Preventative Medicine
University of Tennessee Health Science Center

Link to course material

Webinar #09 - Introduction to GeneWeaver: Integrating and analyzing heterogeneous functional genomics data

Friday, October 23th at 10am PDT/ 11am MDT/ 12pm CDT/ 1pm EDT
1-hour presentation followed by 30 minutes of discussion

Goals of this webinar:

• Compare a user's gene list with multiple functional genomics data sets
• Compare and contrast gene lists with data currently available and integrated in GeneWeaver
• Explore functional relationships among genes and disease across species

Presented by:
Dr. Elissa Chesler
Professor The Jackson Laboratory

Dr. Erich Baker
Professor and Chair
Department of Computer Science
Baylor University

Link to course material

Webinar #10 - Sketching alternate realities: An introduction to causal inference in genetic studies

Friday, November 20th at 10am PDT/ 11am MDT/ 12pm CDT/ 1pm EDT
1-hour presentation followed by 30 minutes of discussion

Goals of this webinar:

Determination of cause is an important goal of biological studies, and genetic studies provide unique opportunities. In this introductory lecture we will frame causal inference as a missing data problem to clarify challenges, assumptions, and strategies necessary for assigning cause. We will survey the use of directed acyclic graphs (DAGs) to express causal information and to guide analytic strategies.

• Express causal inference as a missing data problem (counterfactual framework)
• Outline assumptions needed for causal inference
• Express causal information as (directed acyclic) graphs
• Outline how to use graphs to guide analytic strategy

Presented by:
Dr. Saunak Sen
Professor and Chief of Biostatistics
Department of Preventative Medicine
University of Tennessee Health Science Center

Link to course material

Webinar #11 - Beginner's guide to bulk RNA-Seq analysis

Friday, February 12th, 2021 at 10am PDT/ 11am MDT/ 12pm CDT/ 1pm EDT
1-hour presentation followed by 30 minutes of discussion

Goals of this webinar:

The use of high throughput short read RNA sequencing has become common place in many scientific laboratories. The analysis tools for quantitating a transcriptome have matured becoming relatively simple to use. The goals of this webinar are:

• To give a general overview of the popular Illumina technology for sequencing RNA.
• To outline several of the key aspects to consider when designing an RNA-Seq study
• To provide guidance on methods and tools for transforming reads to quantitative expression measurements.
• To describe statistical models that are typically used for differential expression and why these specialized models are needed.

Presented by:
Dr. Laura Saba
Associate Professor
Department of Pharmaceutical Sciences
University of Colorado Anschutz Medical Campus

Link to course material

Webinar flyer (pdf)

This webinar series is sponsored by the NIDA Center of Excellence in Omics, Systems Genetics, and the Addictome (P30 DA044223) and the NIAAA-funded PhenoGen Website (R24 AA013162).

Webinar #12 - From GWAS to gene: What are the essential analyses and how do we bring them together using heterogeneous stock rats?

Friday, February 26th at 10am PST/ 11am MST/ 12pm CST/ 1pm EST
1-hour presentation followed by 30 minutes of discussion

Goals of this webinar:

Heterogeneous stock (HS) rats are an outbred population that was created in 1984 by intercrossing 8 inbred strains. The Center for GWAS in Outbred Rats (www.ratgenes.org) has developed a suite of analysis tools for analyzing genome wide association studies (GWAS) in HS rats

• Explain the HS rat population and their history
• Describe the automated pipeline that performs GWAS in HS rats
• Explore the fine mapping of associated regions and explain the various secondary analyses that we use to prioritize genes within associated intervals

Presented by:
Abraham A. Palmer, Ph.D.
Professor & Vice Chair for Basic Research
Department of Psychiatry
University of California San Diego

Webinar flyer (pdf)

Link to course material

Link to course material in pptx: Palmer_talk_2-26-21.pptx

There is no fee associated with this webinar, but users are asked to register to receive the Zoom link and password. Registration: http://bit.ly/osga_2021-02-26

This webinar series is sponsored by the NIDA Center of Excellence in Omics, Systems Genetics, and the Addictome (P30 DA044223) and the NIDA-funded Center for GWAS in Outbred Rats (P50 DA037844).

Webinar #13 - Become a UseR: A brief tour of R

Friday, March 12th at 10am PST/ 11am MST/ 12pm CST/ 1pm EST
1-hour presentation followed by 30 minutes of discussion

We will introduce R programming language and outline the benefits of learning R. We will give a brief tour of basic concepts and tasks: variables, objects, functions, basic statistics, visualization, and data import/export. We will showcase a practical example demonstrating statistical analysis.

Goals of this webinar:

• Why should one use/learn R?
• How to install R/Rstudio
• Learn about R basics: variables, programming, functions
• Learn about the R package ecosystem that extends its capabilities
• See a basic statistical analysis example
• Learn about additional resources

Presented by:
Gregory Farage, PhD and Saunak Sen, PhD
Department of Preventive Medicine
University of Tennessee Health Science Center

Link to course material

Webinar flyer (pdf)

Webinar #14 - Landing on Jupyter: A guided tour of interactive notebooks

Friday, March 26th at 10am PDT/ 11am MDT/ 12pm CDT/ 1pm EDT
1-hour presentation followed by 30 minutes of discussion

Jupyter is an interactive interface to data science and scientific computing across a variety of programming languages. We will present the Jupyter notebook, and explain some key concepts (e.g., kernel, cells). We will show how to create a new notebook; modify an existing notebook; save, export, and publish a notebook. We will discuss several possible use cases: developing code, writing reports, taking notes, and teaching/presenting.

Goals of this webinar:

• Learn what Jupyter notebooks are
• Learn how to install, configure, and use Jupyter notebooks
• Learn how to use Jupyter notebooks for research, teaching, or code development

Presented by:
Gregory Farage, PhD and Saunak Sen, PhD
Department of Preventive Medicine
University of Tennessee Health Science Center

Link to course material

Webinar flyer (pdf)

Webinar #15 – Introduction to Metabolomics Platforms and Data Analysis

Friday, April 9th at 10am PDT/ 11am MDT/ 12pm CDT/ 1pm EDT
1-hour presentation followed by 30 minutes of discussion

Goals of this webinar:

The use of metabolomics to profile small molecules is now widespread in biomedical research. The goals of this webinar are:

• To describe research questions that can be addressed using metabolomics
• To give a general overview of metabolomics technologies
• To outline steps in a metabolomics data analysis pipeline
• To provide information on common resources and databases

Presented by:
Katerina Kechris, PhD
Professor
Department of Biostatistics and Informatics
Colorado School of Public Health
University of Colorado Anschutz Medical Campus

Link to course material

Webinar flyer (pdf)

Webinar #16 – Introduction to the Hybrid Rat Diversity Panel: A renewable rat panel for genetic studies of addiction-related traits

Friday, April 23rd at 10am PDT/ 11am MDT/ 12pm CDT/ 1pm EDT
1-hour presentation followed by 30 minutes of discussion

Goals of this webinar:

The Hybrid Rat Diversity Panel (HRDP) is an inbred panel of rats that included two recombinant inbred panels and a panel of classic inbred strains.

• To describe hybrid diversity panels, in particular the HRDP, including advantages and disadvantages when studying the role of genetics is substance use disorders, e.g., renewable genomes and the accumulation of behavioral and physiological phenotypes and high throughput omics data.
• To outline current resources and resources that are being generated.
• To demonstrate the utility of a renewable genetically diverse rodent population when exploring the interaction between genetics, drug exposure, and behavior.

Presented by:
Hao Chen, PhD
Associate Professor
Department of Pharmacology, Addiction Science, and Toxicology
University of Tennessee Health Science Center

Dr. Laura Saba
Associate Professor
Department of Pharmaceutical Sciences
University of Colorado Anschutz Medical Campus

Link to course material

Webinar flyer (pdf)

Webinar #17 – Identifying sample mix-ups in eQTL data

Friday, June 11th at 10am PDT/ 11am MDT/ 12pm CDT/ 1pm EDT
1-hour presentation followed by 30 minutes of discussion

Goals of this webinar:

Sample mix-ups interfere with our ability to detect genotype-phenotype associations. However, the presence of numerous eQTL with strong effects provides the opportunity to not just identify sample mix-ups, but also to correct them.

• To illustrate methods for identifying sample duplicates and errors in sex annotations.
• To illustrate methods for identifying sample mix-ups in DNA and RNA samples from experimental cross data.

Presented by:
Karl Broman, PhD
Professor
Department of Biostatistics & Medical Informatics
University of Wisconsin-Madison

Webinar flyer (pdf)

Link to course material:kbroman.org/Talk_OSGA2021

Webinar #18 – Introduction to the Methylome: Technologies and Analysis

Friday, August 27th at 10am PDT/ 11am MDT/ 12pm CDT/ 1pm EDT
1-hour presentation followed by 30 minutes of discussion

Goals of this webinar:

Studying DNA methylation is widespread in biomedical research. The goals of this webinar are:

• To describe research questions that can be explored by profiling the methylome
• To give a general overview of DNA methylation profiling technologies
• To outline steps in DNA methylation analysis pipeline
• To provide information on common resources and databases

Presented by:
Katerina Kechris, PhD
Professor
Department of Biostatistics and Informatics
Colorado School of Public Health
University of Colorado Anschutz Medical Campus

Webinar flyer (pdf)

Link to course material: Introduction to DNA Methylation Platforms and Data Analysis

Webinar #19 – A Rube Goldbergian Approach to Scheduling Rodent Behavior Experiments and Data Collection

Friday, September 10th at 10am PDT/ 11am MDT/ 12pm CDT/ 1pm EDT
1-hour presentation followed by 30 minutes of discussion

Summary of this webinar:
Large-scale rodent behavioral experiments with complicated testing procedures conducted over several years (e.g., genetic mapping of operant drug taking) need rigorous control on the quality of the data. This webinar will discuss methods used in my lab where we generate ready to use MedPC macros from a spreadsheet for new test sessions, cell phone notification on the completion of behavioral tests, nightly automated data assembly, daily notification of procedural changes for individual animals. Potential errors are checked automatically at several points with messages sent to the users. This system is put together using a relational database (sqlite), several ad hoc computer programs (perl, python, or shell), a cloud storage service (Dropbox), and a messaging system (slack). By turning much of the experiment planning and error checking procedure into computer code, we improve experimental efficiency and data quality.

Presented by:
Hao Chen, PhD
Associate Professor
Department of Pharmacology, Addiction Science, and Toxicology
University of Tennessee Health Science Center

Webinar flyer (pdf)

Link to course material: A Rube Goldbergian Approach to Scheduling Rodent Behavior Experiments and Data Collection

This webinar series is sponsored by the NIDA Center of Excellence in Omics, Systems Genetics, and the Addictome (P30 DA044223).

Webinar #20 – Organizing data in spreadsheets

Friday, September 24th at 10am PDT/ 11am MDT/ 12pm CDT/ 1pm EDT
1-hour presentation followed by 30 minutes of discussion

Summary of this webinar:
Spreadsheets are widely used software tools for data entry, storage, analysis, and visualization. Focusing on the data entry and storage aspects, this presentation will offer practical recommendations for organizing spreadsheet data to reduce errors and ease later analyses. The basic principles are: be consistent, write dates like YYYY-MM-DD, do not leave any cells empty, put just one thing in a cell, organize the data as a single rectangle (with subjects as rows and variables as columns, and with a single header row), create a data dictionary, do not include calculations in the raw data files, do not use font color or highlighting as data, choose good names for things, make backups, use data validation to avoid data entry errors, and save the data in plaintext files. Broman KW, Woo KH (2018) Data organization in spreadsheets. The American Statistician 78:2–10
(https://doi.org/gdz6cm)

Presented by:
Karl Broman, PhD
Professor
Department of Biostatistics & Medical Informatics
University of Wisconsin-Madison

Webinar flyer (pdf)

Link to course material: https://github.com/OSGA-OPAR/quant-genetics-webinars/tree/master/2021-09-24

This webinar series is sponsored by the NIDA Center of Excellence in Omics, Systems Genetics, and the Addictome (P30 DA044223).

Webinar #21 – A Primer on Brain Proteomics and protein-QTL Analysis for Substance Use Disorders

Friday, October 8th at 10am PDT/ 11am MDT/ 12pm CDT/ 1pm EDT
1-hour presentation followed by 30 minutes of discussion

Goals of this webinar:

• To give a general introduction to proteomics technologies and data processing/normalization
• To present a pipeline for correcting sample mix-ups in proteomic data.
• To discuss rat brain proteome and protein QTL analysis for Substance Use Disorders.

Presented by:
Xusheng Wang, PhD
Assistant Professor
Department of Biology
University of North Dakota

Dr. Rob Williams
Professor and Chair
Department of Genetics, Genomics, and Informatics
University of Tennessee Health Science Center

This webinar series is sponsored by the NIDA Center of Excellence in Omics, Systems Genetics, and the Addictome (P30 DA044223).

Webinar #22 – Guide to evaluating the application of machine learning methods in genetics literature

Friday, October 22nd at 10am PDT/ 11am MDT/ 12pm CDT/ 1pm EDT

Goals of this webinar:

• To describe the relationship between artificial intelligence (AI), machine learning (ML), and deep learning (DL).
• To describe general scenarios when ML is appropriate.
• To understand methods for comparing the performance of different ML algorithms
• To layout general criteria to examine when evaluating literature that includes machine learning algorithms

Presented by:
Dr. Laura Saba
Associate Professor
Department of Pharmaceutical Sciences
University of Colorado Anschutz Medical Campus

Webinar flyer (pdf)

Link to course material: Guide to evaluating the application of machine learning methods in genetics literature

This webinar series is sponsored by the NIDA Center of Excellence in Omics, Systems Genetics, and the Addictome (P30 DA044223).

Webinar #23 – Julia: a fast, friendly, and powerful language for data science

Friday, November 12th at 10am PDT/ 11am MDT/ 12pm CDT/ 1pm EDT

Julia is a high-level dynamic programming language that is gaining popularity. The Julia language is designed for scientific computing and offers several attractive features for data science applications. In this webinar, we will make a case for why a data scientist might consider taking a serious look at Julia. We will show code examples and point the audience to further resources.

Goals of this webinar:

• To articulate why Julia is attractive for data scientists
• To provide an overview of Julia language syntax and design
• To provide additional resources about the Julia language and ecosystem

Presented by:
Gregory Farage, PhD
Post-Doctoral Fellow
Department of Preventive Medicine
University of Tennessee Health Science Center

Dr. Saunak Sen
Professor and Chief of Biostatistics
Department of Preventative Medicine
University of Tennessee Health Science Center

Webinar flyer (pdf)

This webinar series is sponsored by the NIDA Center of Excellence in Omics, Systems Genetics, and the Addictome (P30 DA044223).

Webinar 1 UCSD – NIDDK Information Network (dkNET)

03/22/2019

The dkNET team is announcing exciting new changes to the dkNET Portal. The newly designed web portal now includes many new tools and reporting systems to enable researchers to easily navigate large amounts of data and information about research resources-reagents, tools, organisms, grants and other services. The new portal makes it easier to find and use information about the tools you use in your research. An exciting new feature is the Hypothesis Center, which analyzes large amounts of ‘omics data to provide new insights into the pathways involved in DK diseases.

In this webinar, we gave you an overview of services and tools provided at dkNET portal, and show you how to create a detailed research resource report, how to navigate NIH mandates and policies, FAIR data services, Hypothesis Center and more!

Presented by:
Dr. Jeffrey Grethe, University of California San Diego.

Bonus 1 - Data structure, disease risk, GXE, and causal modeling

Friday, November 20th at 9am PDT/ 11pm CDT/ 12pm EDT
1-hour presentation followed by 30 minutes of discussion

Human disease is mainly due to complex interactions between genetic and environmental factors (GXE). We need to acquire the right "smart" data types—coherent and multiplicative data—required to make accurate predictions about risk and outcome for n = 1 individuals—a daunting task. We have developed large families of fully sequenced mice that mirror the genetic complexity of humans. We are using these Reference Populations to generate multiplicatively useful data and to build and test causal quantitative models of disease mechanisms with a special focus on diseases of aging, addiction, and neurological and psychiatric disease.

Speaker Bio: Robert (Rob) W. Williams received a BA in neuroscience from UC Santa Cruz (1975) and a Ph.D. in system physiology at UC Davis with Leo M. Chalupa (1983). He did postdoctoral work in developmental neurobiology at Yale School of Medicine with Pasko Rakic where he developed novel stereological methods to estimate cell populations in brain. In 2013 Williams established the Department of Genetics, Genomics and Informatics at UTHSC. He holds the UT Oak Ridge National Laboratory Governor’s Chair in Computational Genomics. Williams is director of the Complex Trait Community (www.complextrait.org) and editor-in-chief of Frontiers in Neurogenomics. One of Williams’ more notable contributions is in the field of systems neurogenetics and experimental precision medicine. He and his research collaborators have built GeneNetwork (www.genenetwork.org), an online resource of data and analysis code that is used as a platform for experimental precision medicine.

Presented by:
Dr. Rob Williams
Professor and Chair
Department of Genetics, Genomics, and Informatics
University of Tennessee Health Science Center