@ University of Tennessee Health Science Center

Training

CTC-RG provides plenty of training options in the form of tutorials, webinars, documentation, and access to past meetings.

Index Title/Description Presentation
01

CTC-RG 18th Annual Meeting. Models for precision medicine. Session 1.

  • Welcome and Introduction. - Reinmar Hager. University of Manchester, UK.
  • Genetics, Omics, and Live FAIR+ Data Reanalysis using Workbooks and GeneNetwork. - Robert Williams. University of Tennessee Health Science Center, USA.
  • Genetic control of the pluripotency epigenome determines differentiation bias in mouse embryonic stem cells. - Christoper Baker. The Jackson Laboratory, USA.
  • NIDA center for genetic studies of drug abuse in outbred rats. - Abraham Palmer. University of California San Diego, USA.
  • Identification of regulatory landscape in multiple brain regions of outbred heterogeneous stock rats. - Daniel Munro. University of California San Diego, USA.
02

CTC-RG 18th Annual Meeting. Models for precision medicine. Session 2.

  • Discovery of Heritable Cancer Risk Genes Using Diversity Outbred F1 mice That Express HER2/Neu Oncogene - Wei Wei-Zen. Wayne State University, USA
  • Natural genetic variation alters Alzheimer's-related gene expression modules in mice. - Wells Ann. The Jackson Laboratory, USA.
  • A BALB/c reduced complexity cross identifies Zhx2 as a candidate underlying oxycodone metabolite brain concentration and state-dependent learning. - Beierle Jacob. Boston University, USA
  • Genetic basis of thermal nociceptive sensitivity and brain weight in a BALB/c reduced complexity cross. - Bryant Camron. Boston University, USA.
03

CTC-RG 18th Annual Meeting. Models for precision medicine. Session 3

  • Regulation of protein abundance in genetically diverse mouse populations - Greg Keele. The Jackson Laboratory, USA.
  • Genetic dissection of the pluripotent proteome - Selcan Aydin. The Jackson Laboratory, USA.
  • Power and precision: Evaluation and recommendations of quantitative trait analysis methods for RNA expression levels in the Hybrid Rat Diversity Panel. - Jack Pattee. University of Colorado, USA.
  • Investigating the gut-brain axis in 4,006 P50 Heterogeneous Stock rats. - Amelie Baud. Centre for Genomic Regulation, Spain
  • Differential Mechanisms Dictate Cholesterol Levels in Chow-fed Versus High-fat diet-fed Mice. - Cody Cousineau. University of Michigan, USA.
04

CTC-RG 18th Annual Meeting. Models for precision medicine. Session 4

  • A general hidden Markov model for multi-parent populations - Karl Broman. University of Wisconsin - Madison. WI USA.
  • Integrated transcriptomic analysis reveals unique NASH progression in Leptin deficient rats - Xianmin Zhu. Shanghai Tech University, China.
  • Identification of novel QTL linked to the metabolic syndrome in the Berlin Fat Mouse. - Manuel Delpero. Humboldt University Berlin, Germany.
  • Projecting human and rat GWAS into network space identifies shared genetic control of BMI and height. - Brittany Leger. University of California San Diego, USA.
  • High-fat diet generally exacerbates but is sometimes protective against, cognitive dysfunction in female AD mice depending on genetic background. - Amy Dunn. The Jackson Laboratory, USA.
05

CTC-RG 18th Annual Meeting. Models for precision medicine. Session 5

  • Congenic Mapping and Comparative Genomics of Rat Mammary Carcinoma Susceptibility Locus, Mcs3 - Emily Duderstadt. University of Louisville, USA.
  • Polymorphic SNPs, short tandem repeats, and structural variants cause differential gene expression among inbred C57BL/6 and C57BL/10 substrains - Milad Mortazavi. University of California San Diego, USA.
  • Human-GWAS and rat Mcs1b nominated MIER3 is a causal breast cancer susceptibility gene. - David Samuelson. University of Louisville, USA.
  • Genetic analysis of multiple measures of locomotor activity in 2,325 outbred Heterogeneous Stock rats. - Apurva Chitre. University of California San Diego, USA.
  • Keratinocyte-associated protein 3 impacts eating behavior and adiposity differentially based on environmental influences. - Alexandria Szalanczy. Wake Forest University, USA.
  • Automated high-throughput analysis of gait and whole body posture in JAX-KOMP2 pipeline identifies regulators of motor functions. - Gautam Sabnis - The Jackson Laboratory, USA.
06

CTC-RG 18th Annual Meeting. Models for precision medicine. Session 6

  • Genetic basis for unilateral renal agenesis in heterogenous stock rats. - Leal-Gutierrez Joel David. University of California San Diego, USA
  • Genome-wide association study (GWAS) of complex behavioral traits in larval zebrafish. - Xu Jiale. University of California San Francisco, USA
  • High-throughput genotyping of zebrafish enables GWAS in outbred EKW population. - Polesskaya Oksana. University of California San Diego, USA
  • Rat Genome Database (RGD): A multi-species resource to explore complex disease. - Smith Jennifer. Medical College of Wisconsin, USA
  • RGD - Multi-Ontology Enrichment Tool (MOET) - A Bioinformatics Tool for Ontology Analysis Across Multiple Species and Ontologies. - Vedi Mahima. Medical College of Wisconsin, USA
  • RGD - Rat strain updates at the Rat Genome Database (RGD). - Wang Shur-Jen. Medical College of Wisconsin, USA
  • RGD - Quantitative Data Curation for the Hybrid Rat Diversity Panel (HRDP) in RGD’s PhenoMiner Database. - Kwitek Anne. Medical College of Wisconsin, USA
  • RGD - Comparison of genomic variants discovery in HRDP inbred rat strains with two rat genome references. - Tutaj Monika. Medical College of Wisconsin, USA
  • RGD - Rat Reference mRatBN7.2 Update and Curation. - Demos Wendy. Medical College of Wisconsin, USA
07

CTC-RG 18th Annual Meeting. Models for precision medicine. Session 7.

  • Bayesian modeling of skewed X inactivation in genetically diverse mice reveals a novel Xce allele and hidden properties of embryonic composition. Valdar William, University of North Carolina Chapel Hill, USA
  • Open field nocifensive behavior assay. Chella Krishnan Karthickey, University of Cincinnati, USA
  • Genetic Architecture of Heart Mitochondrial Proteome influencing Cardiac Hypertrophy. Hession Leinani, The Jackson Laboratory, USA
  • Genome-wide association study identifies Taar1 as a candidate gene underlying the response to a Pavlovian reward cues. Meyer Paul, University at Buffalo, USA
08

CTC-RG 18th Annual Meeting. Models for precision medicine. Session 8.

  • Low-Coverage Whole Genome Sequence Genotyping Pipeline for Peromyscus Californicus. Chen Denghui, University of California San Diego, USA
  • mRatBN7 ushers in a new era of rat genomics and genetics research. Chen Hao, University of Tennessee Health Science Center, USA
  • Quantitative trait locus implicates expression of a mismatch repair protein in STR expansion propensity in mice. Maksimov Mikhail, University of California San Diego, USA
  • Genetic Architecture of Transcript Levels in Rats. Im Hae Kyung, University of Chicago, USA
  • Genetics of Unsupervised Learning Based Mouse Behavior Space. Kumar Vivek, The Jackson Laboratory, USA
  • Multi-omics, more than the sum of its parts. Vacher Cora, Illumina, UK
09

CTC-RG 18th Annual Meeting. Models for precision medicine. Session 9.

  • Identifying Protein Complexes Binding to Risk Functional Variants in the Uromodulin Promoter. McBride Martin, University of Glasgow, UK
  • A novel µ-opioid receptor transgenic Cre rat: Cellular and behavioral characterization. Saunders Thom, University of Michigan, USA
  • Comparing different quantification methods for delayed reward discounting. Mitchell Suzanne, Oregon Health & Science University, USA
  • Strain Nomenclature Curation: From Repository to IMSR to MGI. Perry Michelle, The Jackson Laboratory, USA
  • The Bayesian Network Webserver: A tool for network modeling of system genetics data. Ziebarth Jesse, University of Tennessee Health Science Center, USA
  • Investigating the effect of a large deletion in intron 8 of the Bbs7 gene on the Berlin Fat Mouse phenotype. Krause Florian, Humboldt University Berlin, Germany
  • Dominance genetic effects on complex traits in pigs, rats and mice are associated with trans-acting dominance gene expression effects. Cui Leilei, University College London, UK
  • Preliminary Analysis of Cocaine Sensitivity in a Genome-Wide Association Study Involving Heterogeneous Stock Rats. Rakowski Elizabeth, University at Buffalo, USA
  • GWAS on socially acquired nicotine IVSA in heterogeneous stock rats highlights genes implicated in human smoking behavior. Wang Tengfei, University of Tennessee Health Science Center, USA
  • Genome-wide association study on behaviors in an open field in outbred rats identifies multiple loci implicated in psychiatric disorders. Gunturkun Hakan, University of Tennessee Health Science Center, USA
  • QTL mapping in Collaborative Cross mice reveals candidate loci modulating severe coronavirus disease. Risemberg Ellen, University of North Carolina Chapel Hill, USA
  • CTC and Rat Genomics in Colorado 2022. Saba Laura, University of Colorado, USA
  • Close of meeting. Hager Reinmar, The University of Manchester, UK
Index Title/Description Presentation
27

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

26

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

25

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
24

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]
23

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
22

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

21

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

20

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
19

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
18

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

Friday, November 20th 2021 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

16

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).
15

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 2021 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).
14

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

Friday, March 12th 2021 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)
13

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

Friday, March 26th 2021 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)
12

Webinar #15 – Introduction to Metabolomics Platforms and Data Analysis

Friday, April 9th 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 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)
11

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

Friday, April 23rd 2021 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)
10

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

Friday, June 11th 2021 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
09

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

Friday, August 27th 2021 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
08

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

Friday, September 10th 2021 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).
07

Webinar #20 – Organizing data in spreadsheets

Friday, September 24th 2021 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).
06

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

Friday, October 8th 2021 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).
05

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

Friday, October 22nd 2021 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).
04

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

Friday, November 12th 2021 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).
03

Webinar #24 – HiDiver: A Suite of Methods to Merge Magnetic Resonance Histology, Light Sheet Microscopy, and Complete Brain Delineations

Friday, February 25th 2022 at 10am PDT/ 11am MDT/ 12pm CDT/ 1pm EDT

We have developed new imaging and computational workflows to produce accurately aligned multimodal 3D images of the mouse brain that exploit high resolution magnetic resonance histology (MRH) and light sheet microscopy (LSM) with fully rendered 3D reference delineations of brain structures. The suite of methods starts with the acquisition of geometrically accurate (in-skull) brain MRIs using multi-gradient echo (MGRE) and new diffusion tensor imaging (DTI) at an isotropic spatial resolution of 15 μm. Whole brain connectomes are generated using over 100 diffusion weighted images acquired with gradients at uniformly spaced angles. Track density images are generated at a super-resolution of 5 μm. Brains are dissected from the cranium, cleared with SHIELD, stained by immunohistochemistry, and imaged by LSM at 1.8 μm/pixel. LSM channels are registered into the reference MRH space along with the Allen Brain Atlas (ABA) Common Coordinate Framework version 3 (CCFv3). The result is a high-dimensional integrated volume with registration (HiDiver) that has a global alignment accuracy of 10–50 μm. HiDiver enables 3D quantitative and global analyses of cells, circuits, connectomes, and CNS regions of interest (ROIs). Throughput is sufficiently high that HiDiver is now being used in comprehensive quantitative studies of the impact of gene variants and aging on rodent brain cytoarchitecture.

This work was supported by National Institute on Aging (R01AG070913), National Institute of Neurological Disorders and Stroke (R01NS096729), National Institute of Biomedical Engineering (P41EB015897) and National Institute of Health (S10OD010683).

Presented by:
Dr. G Allan Johnson
Charles E Putman Professor of Radiology, Physics, and Biomedical Engineering
Duke University
Durham North Carolina

Link to course material: GHiDiver: A Suite of Methods to Merge Magnetic Resonance Histology, Light Sheet Microscopy, and Complete Brain Delineations

This webinar series is sponsored by the NIDA Center of Excellence in Omics, Systems Genetics, and the Addictome (P30 DA044223).
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Webinar #25 – Mouse Phenome Database: Resources and analysis tools for curated and integrated primary mouse phenotype and genotype data

Friday, April 8th 2022 at 10am PDT/ 11am MDT/ 12pm CDT/ 1pm EDT

Abstract:

The Mouse Phenome Database (MPD; https://phenome.jax.org) is a widely used resource that provides access to primary experimental data, protocols, and analysis tools for mouse phenotyping studies. Data are contributed by investigators around the world and represent a broad scope of phenotyping endpoints and disease-related characteristics in naïve mice and those exposed to drugs, environmental agents, or other treatments. MPD is engineered to facilitate interactive data exploration and quantitative analysis. It encompasses data from inbred strains and other reproducible panels, including HMDP, KOMP, Collaborative Cross (CC), CC-RIX, and founder strains, along with primary data from mapping populations, including historic mapping crosses and advanced high-diversity mouse populations such as Diversity Outbred mice. A new Study Intake Platform (SIP) for data contributors allows domain experts to submit and annotate their own data with relevant ontology terms. Data contributors also provide detailed information for protocols and animal environmental conditions to fulfill ARRIVE guidelines. Data are exposed to analysis tools within MPD and are available through APIs to other systems. We will demonstrate selected MPD tools, including GenomeMUSter (a new imputed SNP grid on 500+ strains of mice, 83+M locations) and a GWAS metanalysis tool.

Funding provided by NIH DA028420, DA045401, AG066346.

Presented by:
Molly Bogue and Robyn Ball
With other senior members of the MPD team: Elissa Chesler, Vivek Philip, Dave Walton
The Jackson Laboratory

This webinar series is sponsored by the NIDA Center of Excellence in Omics, Systems Genetics, and the Addictome (P30 DA044223).
01

Webinar #26 – Genome-wide Association Study Summary Statistics - Where to find them and how to use them

Friday, April 22nd 2022 at 10am PDT/ 11am MDT/ 12pm CDT/ 1pm EDT

Abstract:

This presentation will guide attendees with how to access genome-wide association study summary statistics and showcase resources available for annotating these summary data for follow-up analyses, including gene-based analyses, eQTL, and epigenetic annotation as well as causal variable analysis. We will guide attendees through components of a GWAS summary dataset and two excellent resources - FUMA and MASSIVE - that use these summary files as inputs to generate vast amounts of annotations that can be brought forward to answer translational research questions.

Funding provided by NIH/NIDA: DA054869, T32DA007261, K02DA032573.

Presented by:
Dr. Arpana Agrawal and Dr. Alexander S. Hatoum
Department of Psychiatry
Washington University School of Medicine

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

03

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

Friday, November 20th 2021 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

Title/Description Presentation

Diallel Crosses, Artificial Intelligence, and Mouse Models of Alzheimer’s Disease

David G. Ashbrook
Assistant Professor
University of Tennessee Health Science Center

Introduction to Gene Network

Please note that this tutorial is based on GeneNetwork v1

GeneNetwork is a group of linked data sets and tools used to study complex networks of genes, molecules, and higher order gene function and phenotypes. GeneNetwork combines more than 25 years of legacy data generated by hundreds of scientists together with sequence data (SNPs) and massive transcriptome data sets (expression genetic or eQTL data sets). The quantitative trait locus (QTL) mapping module that is built into GN is optimized for fast on-line analysis of traits that are controlled by combinations of gene variants and environmental factors. GeneNetwork can be used to study humans, mice (BXD, AXB, LXS, etc.), rats (HXB), Drosophila, and plant species (barley and Arabidopsis). Most of these population data sets are linked with dense genetic maps (genotypes) that can be used to locate the genetic modifiers that cause differences in expression and phenotypes, including disease susceptibility.

Users are welcome to enter their own private data directly into GeneNetwork to exploit the full range of analytic tools and to map modulators in a powerful environment. This combination of data and fast analytic functions enable users to study relations between sequence variants, molecular networks, and function.

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

How to search in GeneNetwork


Presented by Rob Williams University of Tennessee Health Science Center

GeneNetwork.org: genetic analysis for all neuroscientists


Presented by David G. Ashbrook Assistant Professor University of Tennessee Health Science Center