In the summer of 2018, our team will be working with faculty and students from the Tauber Bioinformatics Research Center at the University of Haifa, Israel to prepare and deliver expert bioinformatics workshops on biomedical data analysis that combine discussion of topics relevant to the modern biomedical community with exposure to computational analyses such as RNA-seq, variant calling, machine learning and integration of multi-omics data. The bioinformatics workshops are designed to be available for participants of all levels, including those that do not have any coding experience or technical background. Also, these workshops are an opportunity to discuss issues around standard and novel approaches to omics data analysis. During the workshops, Q&A sessions and hands-on assistance with challenges will be included. More about these topics and sign-up can be seen here: https://edu.t-bio.info/workshops/
Our Bioinformatics Workshops are designed to take up to 3 hours for groups of 20-50 participants, and can be delivered on-site or via the web. The workshops focus on explaining the logic behind methodology with clinical or biological examples.
- Differential Gene Expression
- Machine Learning for Transcriptomic Data
- Bioinformatics Education
- Multi-Omics Integration
1. A Critical Approach to Differential Gene Expression: Comparison of Methods in Mapping and Differential Expression Using Practical Examples
In this workshop, we will cover the basics of RNA-seq analysis, typically resulting in a comparison of expression data between well-defined groups. The basic RNA-seq pipeline will be covered using several pre-processing, mapping and genome feature identification techniques. We will also discuss t-test statistics as applied to measuring differential expression between groups, including p-value adjustment for multiple comparison. Finally, we will talk about ways to visualize and present results. The workshop covers a broad range of topics and is intended to provide an immersive experience to participants of all backgrounds. The practical components of the workshop will be done utilizing the T-BioInfo platform where multiple methods can be explored in a short period of time. Curated datasets will be provided at the start of the workshop. Most of the methods covered in this workshop are also explained in detail on the edu.t-bio.info website in the online courses Transcriptomics 1 & 2.
See more about this workshop here: https://edu.t-bio.info/critical-approach-to-differential-gene-expression/
2. Mining Gene Expression Data: Machine Learning for Transcriptomic Data
Transcriptomic data such as the expression measurements of genes, isoforms and other genomic elements are a rich source of information that can be extracted from biological samples. The usual approach of investigating only the most differentially expressed genes does not always provide insight about patterns in the data, sample classification, or the most informative features for sample classification. In this workshop, participants will learn to apply machine learning methods to analyze transcriptomic data, combining unsupervised and supervised approaches to create a workflow that can be extended to other projects. Curated datasets will be provided at the start of the workshop. Most of the methods covered in this workshops are also explained in detail on the edu.t-bio.info website in the course Transcriptomics 3.
See more about this workshop here: https://edu.t-bio.info/mining-gene-expression-data/
3. Genomics Analysis (Germline vs. Somatic Mutations): Algorithmic Comparisons and Considerations for Germline and Somatic Variant Calling with Annotation
Next Generation Sequencing provides a detailed view of DNA, typically sequenced for targeted gene assays, whole exome or whole genome data. This data can be analyzed to identify genomic sequence variations associated with clinical conditions or other traits. In this workshop, we will look at several examples of genomic variation and approaches to analysis of this data for variant calling, segmentation and annotation. Curated datasets will be provided at the start of the workshop. Most of the methods covered in this workshops are also explained in detail on the edu.t-bio.info website in Genomics 1.
See more about this workshop here: https://edu.t-bio.info/genomics-analysis-germline-vs-somatic-mutations/
4. Bioinformatics Education: Combining Biologically Inspired Bioinformatics with Scripting as an Approach to Teaching the Logic of Biomedical Data Analysis.
Bioinformatics is a discipline that requires a combination of skills from the biological, computational, and statistical sciences. Many programs prioritize the technical aspects of bioinformatics over the biology concepts and logic of analysis, thus limiting the the emphasis on critical thinking, problem solving and in-depth inquiry. In the context of bioinformatics, these skills are rarely taught early on, which prompts students to address new challenges with a technical formula-based approach. However, real-world problems found in research and industry require a flexible approach to bioinformatics that is equipped to analyze new types of data and address novel experimental questions. Our curriculum was designed to quickly expose students to complex topics and projects. Skills are developed in a hands-on setting that combines insight into the typical problems addressed by a bioinformatician and exposure to the analysis logic, highlighted by our unique online analysis environment, the T-BioInfo platform (see more at https://t-bio.info/).
See more about this workshop here: https://edu.t-bio.info/bioinformatics-education/
5. Multi-Omics Integration: Informative Omics Data for Precision Medicine Clinical Research and Drug Discovery
From a systems-biology perspective, simple genotype-phenotype relationships are almost always hard to interpret in a direct way due to multiple levels of sub-cellular regulation in living organisms. This is particularly important in many clinical studies where genomic variants, gene expression, micro-RNAs, methylation and other factors all contribute to disease or treatment response. In this workshop, we will introduce several methods for processing and integrating data to build a network of associations between multi-omics features.
See more about this workshop here: https://edu.t-bio.info/multi-omics-integration/
The workshops are developed by the researchers at the Tauber Bioinformatics Research Center at University of Haifa, Israel in collaboration with academic centers across the US. Technical support for the workshops is provided by the Pine Biotech team.
Participants must have a laptop/desktop computer with internet access. Spreadsheet analysis software is used for simple analyses of pipeline results in most of the exercises. A working version of Excel or other spreadsheet analysis software is necessary to follow these examples. Most of the analysis steps will be done using the t-bio.info platform. No coding or statistics background is required to participate in the workshop, however basic cell biology and biostatistics will be beneficial. In preparation for the workshop, everyone is encouraged to complete the online course material available at edu.t-bio.info.
Workshop participants will receive a certificate of participation from the Tauber Bioinformatics Research Center and Pine Biotech. In some cases, the certificate will be recognized by other partner institutions.
Participants will have hands-on experience with omics data, including transcriptomic and genomic Next Generation Sequencing data. For each workshop, we set a number of specific goals and open the discussion to address real-life challenges faced by participants with their own data or workflows for critical review.