Biomedical datasets like RNA-Seq are rich with potential for knowledge discovery, especially when analyzed properly. In this workshop, expert bioinformaticians will share examples and practical approaches that you can put to use immediately utilizing the versatile and flexible T-BioInfo Bioinformatics platform (t-bio.info). The platform has dedicated sections to analyze Exome-Seq, RNA-Seq, Metagenomics and other data types. With a visual an intuitive interface that eliminates the need for coding, any clinician or biologist can prepare complex processing pipelines and deploy powerful machine learning algorithms to extract meaningful insights from large datasets. The approaches tested on this platform can be deployed independently and extended in a familiar environment like Excel or R for post-processing. Learn more and subscribe at: https://edu.t-bio.info/mastering-rnaseq/
This workshop will address critical issues related to Transcriptomics data:
Processing raw Next Generation Sequencing (NGS) data:
1. Next Generation Sequencing data preprocessing:
- Trimming technical sequences
- Removing PCR duplicates
2. RNA-seq based quantification of expression levels:
- Conventional pipelines (looking at known transcripts)
- Identification of novel isoforms
Analysis of Expression Data Using Machine Learning:
3. Unsupervised analysis of expression data:
- Principal Component Analysis
- Clustering
4. Supervised analysis:
- Differential expression analysis
- Classification, gene signature construction
5. Gene set enrichment analysis
The workshop will include hands-on exercises utilizing public domain datasets: breast cancer cell lines transcriptomic profiles (https://genomebiology.biomedcentral.com/articles/10.1186/gb-2013-14-10-r110), patient-derived xenograft (PDX) mouse model of tumor and stroma transcriptomic profiles (http://www.oncotarget.com/index.php?journal=oncotarget&page=article&op=view&path[]=8014&path[]=23533), and processed data from The Cancer Genome Atlas samples (https://cancergenome.nih.gov/).
Team: The workshops are designed 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.
