An online program on next generation sequencing (NGS) Data Analysis in application to gene expression data with project examples from infectious diseases, cancer & neuroscience hosted by Pine Biotech
This online program will introduce real-world applications of RNA-seq data analysis in biomedical research and provide participants with hands-on skills and logical background to extract insights from gene expression data. We will review methods and history of quantitative and qualitative analysis of mRNA expression. 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.
Transcriptomics Project Examples:
○ Mapping raw reads to reference genome and transcriptome
○ Detecting junctions and assembly of isoforms
○ Quantification of mRNA: Gene, isoform and exon expression table
○ DIfferential gene and isoform expression
○ Hypothesis testing, p-values, and normalization
○ Multivariate analysis using regressio
○ Data exploration using dimensionality reduction and clustering
○ Classification and discriminant analysis for labeled datasets
○ Cancer subtypes based on gene expression (breast cancer classification)
○ Techniques and protocols for scRNA-seq data preparation
○ Major analytical steps for processing raw single cell sequencing data
○ Analytical techniques to visualize and cluster scRNA-seq data
Program Syllabus : Transcriptomics
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Introduction to NGS Transcriptomics
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Processing Transcriptomics Data
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Precision Medicine Projects
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Loading RNA-Seq data in R and Python
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Normalization and Preparation for Analysis
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Data Visualization in R and Python
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Exploratory Analysis
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Differential Gene Expression
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Regression Analysis
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Biological Interpretation
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Single Cell RNA-Seq methods and analysis approaches for cell type decomposition
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Case Studies
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Register for the Upcoming Webinar Session:
Resources and Training Session Examples
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Learn how to analyze RNA-Seq data on the T-BioInfo platform | Understand methods and approaches for RNA-seq | Start running R code for visualization and analysis | Learn Python code for visualization and analysis | Explore Project Case Studies in various topics |


