The OmicsLogic Transcriptomics program will introduce real-world applications of RNA-seq and provide participants with hands-on skills and logical background to the full RNA-seq analysis approach. We will review methods of quantitative and qualitative analysis of mRNA expression in a sample. Other session will focus on how data is generated using Next Generation Sequencing. Practical sessions will guide participants to use the methods we review on several project datasets to practice generating a table of expression from raw FASTq files and perform subsequent analysis of this table of gene and isoform expression.
Biology of RNA Overview of the entire course, Overview of the tools and resources for this program (edu.t-bio.info courses, projects and datasets, and the...
Session 2: Transcriptomics 1 A: Processing short-read sequencing and building a Bioinformatics Pipeline
Session Topics: The Logic of RNA-seq Analysis Role of pre-processing in standard RNA-seq pipelines (Trimmomatic and PCR-clean) Mapping techniques: mapping on the transcriptome, mapping...
Session Topics: Quantification and Generating a table of expression: RSEM Technical Details on Methods We Used Conclusion and Review Associated online course/resource: Transcriptomics 1
Session 4: Transcriptomics 2A: Differential Gene Expression and Statistical Analysis using Patient Derived Xenograft Models for tumor microenvironment studies
Session Topics: Review Quantification and Generating a table of expression: RSEM, HTSeq, and Sailfish Statistical Analysis: Filtering, removing noise and Normalization Techniques Associated online...
Session Topics: Correlation – detecting correlation of features and factors Regression, factors, and features – Factor Regression Analysis overview Biological Interpretation Associated online course/resource:Transcriptomics...
Session 6: Transcriptomics 3A: Introduction to Data Mining for RNA-seq data Dataset-Breast Cancer cell transcriptome
Session Topics: Introduction to unsupervised machine learning Dimensionality Reduction: PCA, H-Clust, K-means Result Interpretation Associated online course/resource: Transcriptomics 3
Session Topics: Introduction to Supervised Machine Learning Predictive Analysis: Random Forest, SVM, LDA. Feature Selection and expanding the list of features Biological Interpretation Associated...
Session 8: Project examples and publicly available RNA-Seq datasets on NCBI, GEO, SRA, examples in oncology, infectious diseases, and agriculture
Session Topics: Infectious Diseases Specialization track: Transcriptomics Profiling of Host pathogen interaction Agriculture Specialization Track: Forest Conservation: RNA Seq analysis of fungal pathogen Grosmannia...
Session 9: Project examples from Neurobiology: Alzheimer Disease: Transcriptomics Profiling of Alzheimer’s Disease
Session Topics: Whole-genome sequencing Data Repositories How to find data and understand project metadata Planning your project, Case Studies & Publications, Datasets. Associated online...
Session Topics: Review of Project Proposal, Expert feedback for peer review poster presentation Next steps and Mentor Guidance Vote of thanks Associated online course/resource:...
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