This project was supported by funds from the National Science Foundation (NSF; PGRP-1810468, ABI-1661152).
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GEN242 Spring 2018 - Home
- Internal
- Schedule
-
Lecture Slides
- Course Introduction
- Molbiol Basics
- Databases and Software
- DNA Sequencing
- Introduction to R
- Sequence Alignments
- Programming in R
- Multiple Alignments
- Short Read Alignments
- NGS Analysis Basics
- Gene Expression Analysis
- NGS Workflows
- ChIP-Seq Overview
- VAR-Seq Overview
- Gene Annotation and Ontologies
- Sequence Assembly
- Cluster Analysis
- Profile HMMs
- Introduction to Phylogenetics
- Homework
- GitHub
- Linux & HPCC Cluster
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Introduction to R
- 1. Overview
- 2. R Package Repositories
- 3. Installation of R Packages
- 4. Getting Around
- 5. Basic Syntax
- 6. Data Types
- 7. Data Objects
- 8. Important Utilities
- 9. Operators and Calculations
- 10. Reading and Writing External Data
- 11. Useful R Functions
- 12. dplyr Environment
- 13. SQLite Databases
- 14. Graphics in R
- 15. Analysis Routine
- 16. R Markdown
- 17. Shiny Web Apps
- 18. Session Info
- 19. References
- Programming in R
- NGS Analysis Basics
- NGS Workflow Overview
- RNA-Seq Workflow
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ChIP-Seq Workflow
- 1. Introduction
- 2. Generate workflow environment
- 3. Read preprocessing
- 4. Alignments
- 5. Utilities for coverage data
- 6. Peak calling with MACS2
- 7. Annotate peaks with genomic context
- 8. Count reads overlapping peaks
- 9. Differential binding analysis
- 10. GO term enrichment analysis
- 11. Motif analysis
- 12. Version Information
- 13. Funding
- 14. References
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VAR-Seq Workflow
- 1. Introduction
- 2. Generate workflow environment
- 3. Read preprocessing
- 4. Alignments
- 5. Variant calling
- 6. Filter variants
- 7. Annotate filtered variants
- 8. Combine annotation results among samples
- 9. Summary statistics of variants
- 10. Venn diagram of variants
- 11. Plot variants programmatically
- 12. Version Information
- 13. Funding
- 14. References
- Graphics and Visualization
- Cluster Analysis
- Paper Presentations
- Course Projects
10. Funding
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