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Next-Gen Sequence Analysis Workshop (2019)
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¶
1. Next-Gen Sequence Analysis Workshop (2019)
1.1. 3 Rooms & lead instructors!
1.2. Schedule, in brief:
1.3. Second week: July 8-13, 2019.
2. Workshop Code of Conduct
2.1. Introduction
2.2. The Quick Version
2.3. The Less Quick Version
3. Guidelines & Expectations for ANGUS 2019 Events
3.1. Introduction
3.2. Workshop Guidelines
3.3. Link to feedback form
3.4. Expectations of event learners
3.5. Expectations of instructors and helpers
3.6. Expectations of workshop organizers
3.7. Expectations in the lecture hall
4. Intro to cloud computing
4.1. Learning Objectives:
4.2. Rationale
4.3. What is the Cloud?
4.4. Popular Cloud/HPC resources
4.5. Let’s connect to the cloud
5. Command Line BLAST
5.1. Basic Local Alignment Search Tool
5.2. Running command-line BLAST
6. An introduction to the shell
6.1. Some terminology
6.2. Why learn the command line?
6.3. So let’s get to it!
7. Accessing The Jetstream Cloud
7.1. Learning Objectives:
7.2. Login & Launch Instance
7.3. SSH Secure-Login
7.4. Instance Maintenance
7.5. Additional Features
8. Environment management with Conda
8.1. Learning objectives
8.2. Why should I use a package and environment management system?
8.3. What is an environment?
8.4. What is Conda?
8.5. How does Conda work
8.6. Benefits of Conda
8.7. Installing & Activating Conda
8.8. Adding a new environment
8.9. Activating and leaving (deactivating) an environment
8.10. What are Conda channels?
8.11. A note on the management Conda Environments
8.12. More Reading on Conda
9. Short read quality and trimming
9.1. Getting started
9.2. Data source
10. RNA-seq read quantification with salmon
10.1. Boot up a Jetstream
10.2. Introduction to Salmon (adapted from salmon documentation)
10.3. Install software
10.4. Make a new working directory and link the quality trimmed data
10.5. Download the yeast transcriptome:
10.6. Index the yeast transcriptome:
10.7. Run salmon on all the samples:
11. R and RStudio introduction
11.1. Using RStudio on Jetstream
11.2. Installing on your own computer:
11.3. Introduction to R and RStudio
11.4. Basic concepts
11.5. Starting with tabular data
11.6. Making plots with ggplot2
11.7. Acknowledgements
11.8. More material
12. Differential Expression and Visualization in R
12.1. Getting started on Jetstream
12.2. Importing gene-level counts into R using tximport
12.3. Why do we need to normalize and transform read counts
12.4. Differential Expression with
DESeq2
12.5. Visualization of RNA-seq and Differential Expression Results
12.6. Further Notes
13. Mapping and variant calling on yeast transcriptome
13.1. Boot up a Jetstream
13.2. Install software
13.3. Change to a new working directory and map data
13.4. Variant Calling Workflow
13.5. Map data
13.6. Visualize mapping
14. Automating workflows using bash
14.1. Objectives
14.2. Accessing our JetStream instances
14.3. Setting up our environment
14.4. Our first bash script!
14.5. Grabbing some data
14.6. Constructing a bash script
15. Workflow Management using Snakemake
15.1. Objectives
15.2. Accessing our JetStream intances
15.3. Automation with BASH
15.4. Introduction to Snakemake
15.5. Starting with Snakemake
15.6. Creating a pipeline with snakemake
15.7. Using Snakemake to process multiple files
15.8. Snakemake Additional Features
15.9. Resources
16. Adding onto our snakemake workflow
17. De novo genome assembly
17.1. Accessing our JetStream instances
17.2. Setting up our working environment
17.3. The data
17.4. Quality trimming/filtering
17.5. FastQC
17.6. Trimmomatic
17.7. Read-error correction
17.8. Assembly
17.9. SPAdes
17.10. MEGAHIT
17.11. Comparing assemblies
17.12. What about when we don’t have a reference?
18. De novo genome exploration
18.1. The data
18.2. Exploring our assembly with anvi’o
18.3. Epilogue
19. Some more practical use of Unix
19.1. Objectives
19.2. Accessing our JetStream instances
19.3. Setting up a new conda environment
19.4. Setting up our working directory
19.5. Making a blast database of our reference
19.6. Blasting our assembly against the reference
19.7. What didn’t align?
19.8. What did we get?
20. Version Control with Github
20.1. Setup
20.2. What is Github?
20.3. What Is Git?
20.4. Git terms
20.5. Git-Specific Commands
20.6. Setting Up GitHub And Git For The First Time
20.7. Creating Your Online Repository
20.8. Creating Your Local Repository
20.9. Connect Your Local Repository To Your GitHub Repository Online
20.10. Collaborating via GitHub
20.11. Host Websites & Blogs on GitHub
20.12. Sources for this tutorial & Additional Git Resources
21. Microbial Ecology - a discussion and overview of amplicon sequencing and metagenomics
21.1. Amplicon sequencing utility
21.2. Metagenomics utility
22. General workflows
22.1. Amplicon overview
22.2. Metagenomics overview
23. De novo transcriptome assembly
23.1. Download and trim the data
23.2. Generate a
de novo
assembly
23.3. Run the assembler
23.4. Looking at the assembly
23.5. Suggestions for next steps
24. Annotating and evaluating a
de novo
transcriptome assembly
24.1. Annotation with dammit
24.2. Evaluation with BUSCO
25. Quick Insights from Sequencing Data with sourmash
25.1. Getting started
25.2. Objectives
25.3. Introduction to k-mers
25.4. Why k-mers, though? Why not just work with the full read sequences?
25.5. Long k-mers are species specific
25.6. Using k-mers to compare samples
25.7. Installing sourmash
25.8. Creating signatures
25.9. Compare many RNA-seq samples quickly
25.10. Detect Eukaryotic Contamination in Raw RNA Sequencing data
25.11. Compare reads to assemblies
25.12. Make and search a database quickly.
25.13. What’s in my metagenome?
25.14. Final thoughts on sourmash
26. RNA-seq Analysis
26.1. Some basics
26.2. Installations
26.3. Bioconductor
26.4. A simple RNA-seq flow
26.5. DESeq2
26.6. Continue the lesson in RMarkdown
26.7. More resources
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