Spring 2024 Semester

Course Closes: March 1, 2024

Modality: Hybrid, but in-person encouraged

Description:

Python is a simple and popular programming language that can be used across platforms, and is useful for a wide variety of tasks.

This short course is a basic introduction to scripting using Python. Skills taught will include data structures, loops, conditional statements, function definitions, and if time permits, file input and output. These tools will be useful for researchers in many fields for data management, automating tedious computational tasks, and handling “big data.” This course is taught at an introductory level and is appropriate for students with no programming experience, but will contain material and techniques helpful to moderately experienced programmers new to Python.

Instructor Bio:

Dhivya Arasappan has 12 years experience analyzing NGS data from multiple platforms: Illumina, PacBio and SOLiD. Her areas of expertise include: de novo genome assembly, particularly using hybrid sequencing data, RNA-Seq analysis, exome analysis, and benchmarking of bioinformatics tools. She is the research educator for the Big Data in Biology Freshman Research Initiative stream and teaches an RNA-Seq course as part of the Summer School for Big Data in Biology.

Course Closes: March 11, 2024

Modality: Hybrid

Description:

This course provides an overview of how the Microscopy and Imaging Facility can help researchers answer their scientific questions. It will cover the instruments and services available at the MIF, including advanced fluorescence microscopes, flow cytometers, and cell sorters; the types of experiments that could be conducted using our instruments; an introduction to our staff scientists; and details about how to access our resources.

Instructor Bio:

Before becoming director of the Microscopy and Imaging Facility in 2021, Anna Webb was the light microscopy specialist at the MIF for 5 years and has worked in light microscopy support in core facilities for 15 years.

Course Closes: March 15, 2024

Modality: Hybrid

Description:

This domain non-specific course is designed for Python programmers who have basic experience with the language. Learners are expected to be familiar with control flow and basic Python data structures (variable assignment, lists, dictionaries). This course will cover the knowledge to make code modular, readable and reproducible. A major focus will be object-oriented programming and Python’s implementation of the object-oriented paradigm.

Instructor Bio:

Dennis Wylie joined the Bioinformatics group in 2015. He has experience in NGS data analysis including variant calling and RNA-Seq-based biomarker discovery and predictive modeling (classification, regression, etc.). Prior to UT, he earned a PhD in Biophysics from UC Berkeley applying stochastic simulation methods to problems in immunology, did postdoctoral work modeling the transmission of infectious disease, and spent six years as a bioinformatician in industry.

Course Closes: March 22, 2024

Modality: In-person

Description:

This course will offer an introduction into the services provided by the Genomic Sequencing and Analysis Facility available to researchers at the University of Texas. The course will cover the platforms and services available, best practices and how to submit samples to the core.

Instructor Bio:

Jessica Podnar joined the GSAF in 2010, prior to UT she worked at a biotech company focused on drug discovery and telomere biology. She has 15 years experience in cell and molecular biology and has been part of the rapidly changing field of Next Generation Sequencing for most of her career. She is familiar with an assortment of NGS technologies and is always ready to support new projects.

Course Closes: March 22, 2024

Modality: Hybrid, but in-person encouraged

Description:

This course will build up on the concepts covered in the Introduction to Python and Intermediate Python courses. We will introduce the use of Pandas Data frames to read in, subset, analyze and visualize RNA-Seq gene expression data.

Instructor Bio:

Dhivya Arasappan has 12 years experience analyzing NGS data from multiple platforms: Illumina, PacBio and SOLiD. Her areas of expertise include: de novo genome assembly, particularly using hybrid sequencing data, RNA-Seq analysis, exome analysis, and benchmarking of bioinformatics tools. She is the research educator for the Big Data in Biology Freshman Research Initiative stream and teaches an RNA-Seq course as part of the Summer School for Big Data in Biology.

Course Closes: March 25, 2024

Modality: Hybrid

Description:

This course will dive more into how the Microscopy and Imaging Facility’s instruments work and some best practices for getting data. We will discuss the fundamentals of fluorescence, image resolution, and the principles and operation of flow cytometers, cell sorters, and light microscopes.

Instructor Bio:

The course intro will be taught by Anna Webb, the Microscopy and Imaging Facility Director. The main sections will be taught by the MIF’s technical staff: Richard Salinas, flow cytometry and cell sorting specialist, and Paul Oliphint, light microscopy specialist.

Course Closes: March 29, 2024

Modality: Hybrid, but in-person encouraged

Description:

Tag Seq is a method of sequencing the 3′ ends of mRNA in order to identify differential gene expression using a significantly cost-effective method. This course is an introduction to this Tag Seq method as well as the bioinformatics involved in analyzing a Tag Seq dataset. We will discuss library prep, quality assessment, read mapping, gene quantification, differential expression analysis and downstream analysis. There are no prerequisites for taking this course.

Instructor Bio:

Dhivya Arasappan has 12 years experience analyzing NGS data from multiple platforms: Illumina, PacBio and SOLiD. Her areas of expertise include: de novo genome assembly, particularly using hybrid sequencing data, RNA-Seq analysis, exome analysis, and benchmarking of bioinformatics tools. She is the research educator for the Big Data in Biology Freshman Research Initiative stream and teaches an RNA-Seq course as part of the Summer School for Big Data in Biology.

Course Closes: April 5, 2024

Modality: Hybrid

Description:

Transmission Electron Microscopy (TEM) and Cryogenic electron microscopy (cryo-EM)are versatile methods for biological structural characterization. Technological advancements made in the past decade have enabled cryo-EM to become an approachable high-resolution method capable of generating atomic structures.

The course will be divided into three sections: an initial 45-minute section taught by Michelle Mikesh focusing on the room temperature (classical) EM services offered by the core; followed by two sections taught by Axel Brilot: an overview of the basic principles of single particle cryo-EM along the related services our core offers users, split into two approximately one hour sections with breaks between all sections. We will also discuss the practical applications of cryoEM and what a user will need to perform a successful experiment.

Instructor Bio:

Axel Brilot obtained his Ph.D. in Biophysics and Structural Biology developing and applying cryo-EM methods for single-particle reconstruction. He has 15 years’ experience in the cryo-EM field and has been the facility director of the Sauer Structural Biology Laboratory since 2021.

Michelle Mikesh brings a practical approach to teaching and microscopy. Prior roles in neurobiology and development led her to electron microscopy 20 years ago, publishing work in the fields of synapse development and peripheral nerve repair. Michelle now helps the UT community in fields like microbiology and synthetic biology with TEM and SEM and looks forward to expanding the cryoEM services in the Sauer Core lab.

Course Closes: April 5, 2024

Modality: Hybrid

Description:

This course provides an introduction to the bioinformatics analysis of single-cell RNA-seq (scRNA-seq) data, with a particular focus on methods especially appropriate for analysis of 10X Genomics data. Differences between bulk RNA-seq and scRNA-seq will be discussed in order to develop understanding of both what new methods are required versus what established RNA-seq analysis methods can be retained. Students interested in following along in class should bring their own laptops to the course with R (with Seurat, https://cran.r-project.org/web/packages/Seurat/index.html) installed.

Instructor Bio:

Dennis Wylie joined the Bioinformatics group in 2015. He has experience in NGS data analysis including variant calling and RNA-Seq-based biomarker discovery and predictive modeling (classification, regression, etc.). Prior to UT, he earned a PhD in Biophysics from UC Berkeley applying stochastic simulation methods to problems in immunology, did postdoctoral work modeling the transmission of infectious disease, and spent six years as a bioinformatician in industry.

Course Closes: April 12, 2024

Modality: Hybrid

Description:

This course will detail strategies for establishing, validating, and maintaining mutant mouse lines and describe workflows for initial phenotypic analysis, including guidance on assessing mice with embryonic, perinatal, and postnatal phenotypes and mice with “no phenotype.” The course will also discuss getting around embryonic lethal phenotypes using chimeras and breeding strategies using conditional alleles to analyze tissue- and cell-specific gene function.

Instructor Bio:

Bill Shawlot received his Ph.D. from the Baylor College of Medicine and did his post-doctoral training with Richard Behringer at the M.D. Anderson Cancer Center. He was an Assistant Professor in the Department of Genetics, Cell Biology, and Development at the University of Minnesota, studying mammalian embryogenesis before joining the Texas A&M Institute for Genomic Medicine (TIGM) to help lead TIGM’s efforts in the International Knockout Mouse Consortium program. He has over 30 years of experience in the transgenic mouse field and serves on the External Advisory Committee for the NIH’s Mutant Mouse Resource and Research Center program.

Course Closes: April 19, 2024

Modality: Hybrid

Description:

Learn the basics of using UNIX from the command line. Introductory topics include manipulating text files using standard UNIX utilities, how to string utilities together, and how to output the results to files. The goal of the course is to develop some basic comfort at the command line, get a sense of what’s possible, and learn how to find help.

Instructor Bio:

Anna Battenhouse is a research scientist in the lab of Dr. Edward Marcotte, is a Bioinformatics Consultant, and leads the Biomedical Research Computing Facility in its mission to support the IT and computational needs of the UT Austin biomedical research community. She has extensive experience working with NGS data, develops and maintains analysis scripts for the Bioinformatics Consulting Group, and teaches the Introduction to NGS Tools course in the Big Data in Biology Summer School as well as several CBRS short courses.

Preferred or Prerequisite Skills:

Prior exposure to programming language concepts is helpful but not required.

Students can use their own laptops to access coding examples in a shared computing environment.

Course Closes: April 26, 2024

Modality: Hybrid

Description:

Learn more about using UNIX/Linux from the command line. Topics will build on those in the introductory course, including more on the filesystem, the Bash shell, and text processing. The course will emphasize manipulating text using standard Linux utilities and stringing commands together using pipes. We’ll also introduce some of the powerful Linux utilities such as cut, sort, grep and awk, with the goal of continuing the climb up the steep Linux learning curve.

Instructor Bio:

Anna Battenhouse is a research scientist in the lab of Dr. Edward Marcotte, is a Bioinformatics Consultant, and leads the Biomedical Research Computing Facility in its mission to support the IT and computational needs of the UT Austin biomedical research community. She has extensive experience working with NGS data, develops and maintains analysis scripts for the Bioinformatics Consulting Group, and teaches the Introduction to NGS Tools course in the Big Data in Biology Summer School as well as several CBRS short courses.

Preferred or Prerequisite Skills:

Completion of the Introduction to UNIX CBRS course or equivalent basic command line experience.

Students can use their own laptops to access coding examples in a shared computing environment.

Course Closes: May 3, 2024

Modality: Hybrid

Description:

This course will cover advanced topics in writing Bash shell scripts, providing tips, examples and best practices for creating robust “pipeline scripts” that execute multiple processing steps. Topics include defining functions, argument processing and defaulting, error checking, effective use of utilities such as awk and grep, as well as subtleties of UNIX streams and text manipulation.

Instructor Bio:

Anna Battenhouse is a research scientist in the lab of Dr. Edward Marcotte, is a Bioinformatics Consultant, and leads the Biomedical Research Computing Facility in its mission to support the IT and computational needs of the UT Austin biomedical research community. She has extensive experience working with NGS data, develops and maintains analysis scripts for the Bioinformatics Consulting Group, and teaches the Introduction to NGS Tools course in the Big Data in Biology Summer School as well as several CBRS short courses.

Preferred or Prerequisite Skills:

This is not an introductory course. Attendees must be comfortable performing basic tasks on the Linux command line. Suggested background is completion of the CBRS Introduction to UNIX and Intermediate UNIX courses, or substantial command-line experience.

Students can use their own laptops to access coding examples in a shared computing environment.