Spring 2023 Semester

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.

ABOUT THE INSTRUCTOR: 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.

Cryogenic electron microscopy (cryo-EM) is an emergent method for biomolecular structure determination. The growth in its popularity is primarily due to technological advancements made in the past decade which have enabled cryo-EM to become a consistent and rapid high-resolution method capable of generating atomic structures. In this course, we provide an overview of the basic principles of single particle cryo-EM along with what our core offers users. We will also discuss the practical applications of cryoEM and what a user will need to perform a successful experiment.

ABOUT THE INSTRUCTOR: 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.

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, electron 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.

ABOUT THE INSTRUCTOR: 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.

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

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

This class will provide an introduction to the resources and support available for clinical and preclinical imaging studies at the BIC, including Magnetic Resonance Imaging (MRI) and Spectroscopy (MRS), Positron Emission Tomography (PET), Computed Tomography (CT) and optical imaging (bioluminescence).

ABOUT THE INSTRUCTOR: Doug Befroy has over 20 years of experience in biomedical imaging with a particular focus on the research applications of MRI and MRS in health and disease spanning both academia and industry. He joined the BIC as Director in January 2021.

This class will provide background on how magnetic resonance images are formed. It will include an overview of the magnetic fields used to generate and receive a signal, and how that signal is used to reconstruct images of anatomy. The typical sequence of steps in an exam will be covered along with the variable imaging parameters to generate images with differing contrasts between different tissues and structures. There are no engineering or physics prerequisites: the class will be geared towards those who wish to use MRI for clinical or translational research.

ABOUT THE INSTRUCTOR: Julie DiCarlo got her PhD in Electrical Engineering from Stanford in quantitative cardiac MRI. She spent 10 years designing imaging studies and analyses for clinical trials. She joined UT’s Center for Computational Oncology in 2018 to work on quantitative MR imaging methods for cancer, and joined the BIC as the MRI Staff Scientist in 2022. Her personal imaging interests include optimizing the tradeoff between spatial and temporal resolution for quantitative imaging, and techniques for mitigating image artifacts and improving image quality and consistency.

This class will provide an introduction to processing images for MRI-based research, without focusing on any one anatomy. The question of what can you measure with MR images will be answered with examples from current research in neuro, oncology, and body imaging. Fast imaging techniques will be introduced along with how to use dynamic imaging to characterize tissue or estimate flow.

ABOUT THE INSTRUCTOR: Julie DiCarlo got her PhD in Electrical Engineering from Stanford in quantitative cardiac MRI. She spent 10 years designing imaging studies and analyses for clinical trials. She joined UT’s Center for Computational Oncology in 2018 to work on quantitative MR imaging methods for cancer, and joined the BIC as the MRI Staff Scientist in 2022. Her personal imaging interests include optimizing the tradeoff between spatial and temporal resolution for quantitative imaging, and techniques for mitigating image artifacts and improving image quality and consistency.

This class will cover the operational principles and methodologies of instrumentation used in proteomics experiments. The fundamentals of mass spectrometry will be explained, and the process of digestion and ionization of peptides. Fragmentation modalities will be explained and how they generate the data needed for peptide sequence determination. Biomolecular separation is achieved through liquid chromatography with descriptions of standard parameters for proteomics experiments.

ABOUT THE INSTRUCTORS: Maria Person got her Ph.D. in molecular dynamics from the University of Chicago. She has been working in proteomics in core facility environments for over 25 years and has been director of the Biological Mass Spectrometry Facility since 2003. The facility has worked with over 100 labs to enable researchers to measure and characterize proteins and metabolites.

Peter Faull specializes in implementing and developing quantitative mass spectrometry-based Proteomics approaches. He obtained a Ph.D. from the University of Edinburgh using mass spectrometry to explore the shape of gas-phase proteins. Peter has previously worked in two core facilities in the UK and aims to provide UT scientists with high quality Proteomics data that will help inform the next step in their research.

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.

ABOUT THE INSTRUCTOR: 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.

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.

ABOUT THE INSTRUCTOR: 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.

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.

ABOUT THE INSTRUCTOR: 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.

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.

ABOUT THE INSTRUCTOR: 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.

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.

ABOUT THE INSTRUCTOR: 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 Ph.D. 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.

Learn the basics of using UNIX from the command line. Introductory topics include the filesystem, the shell, and basic text processing. The course will touch on manipulating text files using standard UNIX utilities, how to string utilities together, and how to output 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.

ABOUT THE INSTRUCTOR: Anna Battenhouse is a member of the Bioinformatics Consulting Group, is a research scientist in the lab of Dr. Edward Marcotte, and leads the Biomedical Research Computing Facility in its mission to support the computational needs of the UT Austin biological sciences community. She has extensive experience writing Bash scripts to process Next Generation Sequencing data and perform other functions.

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 focus on 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.

ABOUT THE INSTRUCTOR: Anna Battenhouse is a member of the Bioinformatics Consulting Group, is a research scientist in the lab of Dr. Edward Marcotte, and leads the Biomedical Research Computing Facility in its mission to support the computational needs of the UT Austin biological sciences community. She has extensive experience writing Bash scripts to process Next Generation Sequencing data and perform other functions.