Free online training in bioinformatics and biostatistics!

Many biomedical research graduate programs have been compelled to “go online” with little or no notice due to the COVID-19 pandemic. Since many professors are distinctly uncomfortable in front of a camera, students may not get exposure to some of the topics that they might have expected. Since my move to South Africa in 2015, I have tried to deposit video on YouTube (and PDFs of the slides to Google Drive) every time I have delivered a lecture for students. Since I teach a fairly broad range of coursework, the catalog of topics may be useful for students working from home or for departments that are trying to ensure their students get the training they need. This page indexes the series of lectures I have made available. I hope you enjoy watching them as much as I have enjoyed creating them! (Please see the note about copyright and attribution at the bottom.)

Sequencing Bioinformatics

DNA Replication, courtesy of Wikimedia Commons

I would like to start with the core part of my curriculum. Most of the researchers I train need help to analyze the reams of data coming from massively parallel sequencing experiments. I have delivered these five lectures in a variety of revisions at three different universities in the Western Cape. This year I chose a new structure to put mapping and assembly right up front and to give myself a bit more room for some of the other topics. The amplicon lecture started at the University of the Western Cape but now has evolved strongly enough in the microbiome direction that it will be taught at my own campus, as well.

Title	Slides	Length
Sequencing, Mapping, and Assembly	PDF	1:29:58
Gene-Finding and Sequence Alignment	PDF	1:30:00
Hands On: Recognizing protein orthologs with DIAMOND	none	0:26:46
Genetic Variants, Phenotype, and GWAS	PDF	1:08:20
Gene Expression and Differentiation	PDF	1:20:14
Amplicon and Microbiome Informatics	PDF	1:15:28
Hands On: Oligo7 Primer Design Software	none	0:06:01

Bioinformatics Beyond Sequences

fluorescence microscopy of mitotic LLC-PK1 cells, courtesy of Wikimedia Commons

Of course, bioinformatics is critical for producing information from all kinds of data, not just those from sequencers. I feel it is important for bioinformatics students to learn about basics like ASCII and the representation of image data in memory. An emphasis on the essentials of biological pathways always finds its way into my teaching line-up; I feel grateful that my colleague Bing Zhang was willing to explain so much of this topic to me!

Title	Slides	Length
Computer Science Concepts in Bioinformatics	PDF	1:14:21
Image Analysis and Flow Cytometry	PDF	0:55:34
Relational Databases and Repositories	PDF	0:52:43
What does this gene do?	PDF	0:49:33
Biological Pathways and Networks	PDF	1:16:48

Bottom-Up Proteomics

The ATP synthase complex, courtesy of the Protein Data Bank Molecule of the Month

For twenty years, I have been publishing in the field of proteomics, and its rich informatics is something I want to share with every student! Frequently, though, I find that proteomics content is reduced to just a single lecture for our division’s B.Sc. Honours students. I was pleased as I looked back through my YouTube channel to discover lectures on a much broader range of subjects. The identification of MS/MS to peptide sequences continues to be my “wheelhouse,” but many aspects of this field fascinate me just as much today as they did a decade ago.

Title	Slides	Length
Why Bother with Proteomics?	PDF	0:28:03
Peptide and Protein Identification from MS/MS Data	PDF	1:27:14
Hands On: MSFragger Database Search with IDPicker Protein Assembly	none	1:10:16
Hands On: MSFragger Database Search with Philosopher Protein Assembly	none	0:42:08
Identification of Post-Translational Modifications	PDF	0:58:14
Proteomic Quantitation	PDF	0:57:42
Seven basic tools of quality for biological MS	PDF	0:56:56
Proteomic Quality Control	PDF	0:49:07
Adventures at the Proteome-Genome Boundary	PDF	0:46:02
Proteogenomics in Mycobacteria	PDF	0:48:13
The Secret Lives of Amino Acids	none	0:42:34

Top-Down Proteomics

This Fragment Map illustrates the extent of MS/MS evidence for a particular proteoform from H. pylori

Many biological questions can only be answered if we measure intact proteoforms without use of digestive enzymes. These “top-down” proteomics strategies have emerged from specialist laboratories to become more broadly applied; some MS facilities are beginning to offer top-down analysis as a service. These training videos explain why top-down proteomics offers special challenges. They also examine why the process of identification is more daunting in these MS/MS collections. The demonstrations of deconvolution in FreeStyle and visualizing PrSMs are intended to support users of targeted or inclusion-list experiments.

Title	Slides	Length
Top-down proteome informatics	PDF	1:13:23
Top-down proteomics applications	PDF	1:08:35
Protein Structure Determination and Estimation	PDF	1:00:04
Hands On: Creating a subset database in MSFragger and Philosopher	none	0:41:58
Hands On: Identifying MS/MS experiments with pTop 1.2	none	0:30:54
Hands On: Identifying MS/MS experiments with TopPIC Suite	none	0:39:07
Hands On: Interpreting TopPIC and TopMG Proteoforms	none	1:03:25
Hands On: Top-Down Deconvolution in Thermo FreeStyle	none	0:53:58
Hands On: Visualizing Proteoform-Spectrum Matches in ProSight Lite and ClipsMS	none	0:49:01
Hands On: Conducting searches in ProSight Proteome Discoverer	none	0:45:30

Metabolomics

Cell membrane diagram showing phospholipids and complex carbohydrates from Wikimedia Commons

I am definitely a visitor in the field of metabolomics, but only recently have enough researchers been available in this field that departments who want this emphasis can hire a professor in the space. In my final year at Vanderbilt University (2015), I organized a course demonstrating two of the most widely used tools in the field: XCMS and METLIN. From what I have read in metabolomics papers, 2015 is essentially before the last ice age. Still, I felt these lectures could be useful to newcomers in the field.

Title	Slides	Length
The Origin and Tools of the ProteoWizard Project	PDF	0:40:46
Advanced Options in ProteoWizard msConvert	PDF	0:40:30
XCMS Feature Finding and Retention Time Warping	PDF	0:41:30
Statistics of differentiation	PDF	0:35:55
METLIN and MassBank	PDF	0:46:55
Lipid Identification with Greazy and LipidLama	PDF	0:32:51

Clinical Biomarkers

96 well plate image from Wikimedia Commons

The Department of Biotechnology at University of the Western Cape sought to broaden the medical content available in their B.Sc. Honours curriculum, so I teamed with talented post-doc Dr. Caroline Beltran to create a module. 2020 will represent the third year the course is presented; in 2019, when this was filmed, Dr. Byron Reeve assisted by teaching the gene expression segment.

Title	Slides	Length
Introduction to Biomarker Research	PDF	0:48:14
Proteomics for Biomarker Discovery	PDF	0:47:46
Immunoassays	PDF	0:50:26
Luminex Data Analysis	PDF	0:48:36
Inborn and Acquired Genetic Biomarkers	PDF	1:18:15
Gene Expression Biomarkers	PDF	1:02:31
Receiver Operating Characteristic Curves	PDF	0:47:27
Introduction to Machine Learning	PDF	1:08:59

Statistically Speaking

This 1930s poster from the Eugenics Society demonstrates the language used to make their forced sterilization policies palatable. (courtesy of Wellcome Library)

Many students experience statistics as a very dry topic. When the University of the Western Cape asked me in 2017 to assemble a course in biostatistics, I decided it was a good opportunity to “decolonize” the subject. Many of the great advances in statistics came from researchers who had strong ties to the burgeoning eugenics movement. As I felt more comfortable at the helm over the twelve-week course, I incorporated more and more of the social context in which these researchers were laboring. Source scripts can be found in Google Drive. [Sept. 28, 2021: I updated the links to PDFs of slides to reflect a change in Google Drive security.]

Title	Slides	Length
Measurements and Distributions	PDF	1:03:14
Spread and Conformance	PDF	0:51:12
Correlation is not Causation	PDF	0:50:11
Linear Regression	PDF	0:56:07
Difference Tests	PDF	0:44:52
ANOVA and the Tukey HSD Test	PDF	0:58:33
Contingency Tables	PDF	0:57:49
Two-way ANOVA and Repeated Measures	PDF	1:01:46
Dimensionality Reduction and Principal Components Analysis	PDF	0:57:44
Agglomerative and Divisive Hierarchical Clustering	PDF	1:00:08
Multiple Testing Correction	PDF	1:07:40
Power Analysis	PDF	00:51:34
Hands On: Create a Histogram and Boxplot in Excel	Inputs	0:25:06
Hands On: Create a Histogram and Boxplot in GraphPad Prism	Inputs	0:14:42
Hands On: Create a Histogram and Boxplot in R	Inputs	0:15:45

Introduction to R Statistical Environment

The R logo, from CRAN

The free R language has become one of the most commonly used for biostatistics because of its inherent parallelism and ability to incorporate libraries of advanced functionality, particularly the “Tidyverse.” This five-part series is designed to teach the “first rung of the ladder” to newcomers. The scripts to support the class can be found in Google Drive.

Title	Slides	Length
Why bother learning R? and basics	PDF	1:06:42
Reading and Writing Files	PDF	0:39:34
Conditional Execution, Looping, and Functions	PDF	0:45:33
Visualizing Data with GGPlot2 Library	PDF	0:43:38
Interpreting Difference Tests	PDF	0:51:48

Introduction to Python for Bioinformatics

Biopython represents a powerful suite of tools for computational biology.

Python is still quite a new language for me, but it clearly has a lot of momentum on its side! For students who want to create software of broader capability than what R can support, Python is a great choice. I decided to build my six-session workshop on the project of reading a FASTA file and evaluating and visualizing the frequencies of amino acids. It’s a helpful way to get started with the basics of this very powerful language! The Python code can be found in Google Drive.

Title	Slides	Length
Why Python? and Essential Concepts	PDF	0:47:41
Sets and Iterating Loops	PDF	0:42:00
Reading Files	PDF	0:28:22
Exceptions and the Collections Data Structure	PDF	0:40:28
Data Structures and Plotting	PDF	0:43:22
BioPython and NumPy	PDF	0:42:06

Careers in Research

Scientists from iEmoji.com

From time to time, I get the chance to help graduate students with some of the essential skills of being a scientist. Perhaps my favorite of these talks is the first, which explains that going to graduate school is not a mistake, even for someone who decides that they will not stay in biomedical research afterwards! Researchers can really benefit from encouragement, just like anybody else.

Title	Slides	Length
Research Skills for a Stronger South Africa	PDF	0:38:36
The Unholy Trinity of Research Ethics	PDF	0:43:59
Creating a solid research poster	PDF	0:37:13
Preparing and Delivering Scientific Presentations	PDF	0:51:12
Zotero Citation Manager	none	0:49:48
Social Media for Scientists	none	0:45:36

Copyright and Usage Information

If you are a professor using these lectures as part of a class, you are welcome! Please let me know that you are using them by email (I am dtabb over at sun.ac.za) or by a comment below. If you need to use a slide or two from my presentations, I am willing to send you the PPTX rather than leaving you to copy images from the PDF.

I choose to license these materials as Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0), meaning “You are free to:
Share — copy and redistribute the material in any medium or format
Adapt — remix, transform, and build upon the material
The licensor cannot revoke these freedoms as long as you follow the license terms.”

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