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1. Welcome to Data Carpentry Genomics Workshop at University of Nevada, Reno!
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Table of contents
Table of contents
¶
1. Welcome to Data Carpentry Genomics Workshop at University of Nevada, Reno!
1.1. Instructors
1.2. Schedule in brief
1.3. Other info
2. Workshop Code of Conduct
2.1. Need Help?
2.2. The Quick Version
2.3. The Less Quick Version
3. Introductions
3.1. Here are your instructors for the workshop:
4. Accessing The Atmosphere Cloud
5. Login & Launch Instance
6. SSH Secure-Login
7. Instance Maintenance
7.1. Atmosphere Dashboard
7.2. Suspend Instance
7.3. Delete Instance
8. Additional Features
8.1. Did you know you can access a shell terminal and a web-desktop via your browser ???
9. Advanced Topics
9.1. Atmosphere Advanced Topics
10. Using the command line
10.1. Goals
10.2. Background
10.3. What does it look like?
10.4. Usage
10.5. Navigating Files and Directories
10.6. Creating files and folders
10.7. Piping
10.8. Grep, tr, wc, mv and many others
11. Working with Bioconda.
11.1. What is bioconda?
11.2. What problems does conda (and therefore bioconda) solve?
11.3. Installing conda and enabling bioconda
11.4. Using conda
11.5. Using bioconda
11.6. Rstudio - Getting started
12. Short read quality and trimming
12.1. Data source
12.2. Check that your data is where it should be
12.3. Quality trimming and light quality filtering
13. GitHub: How not to lose your entire analysis!
13.1. Why Version Control?
13.2. What is Git and why use it?
13.3. Options in Git
13.4. Git-GitHub Overview
13.5. Exploring Github
13.6. Collaborating via GitHub
13.7. Look at others’ repositories:
13.8. Host Websites & Blogs on GitHub
13.9. Suggestions for good Git Usage:
14. De novo transcriptome assembly
14.1. Link in the trimmed data
14.2. Run the assembler
14.3. Looking at the assembly
14.4. Suggestions for next steps
15. Read Quantification
15.1. Make a new working directory and link the trimmed reads and assembly
15.2. Index the assembly:
15.3. Run salmon on all the samples:
15.4. Take a look at quant output
15.5. Look at all the mapping rates:
15.6. More reading
16. Differential expression analysis with DESeq2
16.1. Move salmon output quant files to their own directory
16.2. Copy a previously-made gene and transcript id relationship file to your home directory
16.3. Grab a special script plotPCAWithSampleNames.R
16.4. Rstudio reminder
16.5. Working in Rstudio:
17. Advanced Topics
18. Transferring Data to and from an Instance
18.1.
Transferring Data using iCommands
19. Creating custom Atmosphere Images
20. ssh-rsa-key for password-less login
21. Tmux & Screen
22. SSH Remote host ID Changed Error
23. Backup files
23.1. Input raw fastq data
23.2. Trimmed reads
23.3. Transcriptome assembly
23.4. Annotation, created with this annotation lesson
23.5. Salmon quantification files
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2019-UNR-omics 0.0.1 documentation
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