Workshop Schedule

Pre-requisite for this workshop: The Basic Data Skills Introduction to the command-line interface workshop or a working knowledge of the command line and cluster computing.

Pre-reading

• Shell basics review
• Best Practices in Research Data Management (RDM)
• Introduction to RNA-seq

Day 1

Time	Topic	Instructor
09:30 - 09:45	Workshop Introduction	Meeta
09:45 - 10:25	Working in an HPC environment - Review	Meeta
10:25 - 11:05	Project Organization (using Data Management best practices)	Will
11:05 - 11:45	Quality Control of Sequence Data: Running FASTQC	Jihe
11:45 - 12:00	Overview of self-learning materials and homework submission	Jihe

Before the next class:

1. Please study the contents and work through all the code within the following lessons:

• Experimental design considerations
• Quality Control of Sequence Data: Running FASTQC on multiple samples

• Quality Control of Sequence Data: Evaluating FASTQC reports

  NOTE: To run through the code above, you will need to be logged into FAS-RC and working on a compute node (i.e. your command prompt should have the word compute in it).

  1. Log in using ssh username@login.rc.fas.harvard.edu and enter your password (replace username with your username).
  2. Once you are on the login node, use salloc -p test -t 0-2:30 --mem 8G to get on a compute node or as specified in the lesson.
  3. Proceed only once your command prompt does not have the word login in it.
  4. If you log out between lessons (using the exit command twice), please follow points 1. and 2. above to log back in and get on a compute node when you restart with the self learning.

1. Complete the exercises:
   • Each lesson above contain exercises; please go through each of them.
   • Copy over your code from the exercises into a text file.
   • Upload the saved text file to Dropbox the day before the next class.

Questions?

• If you get stuck due to an error while runnning code in the lesson, email us
• Post any conceptual questions that you would like to have reviewed in class here.

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Day 2

Time	Topic	Instructor
09:30 - 10:30	Self-learning lessons review	All
10:30 - 11:10	Sequence Alignment Theory	Meeta
11:10 - 11:50	Quantifying expression using alignment-free methods (Salmon)	Will
11:50 - 12:00	Review of workflow	Meeta

Before the next class:

1. Please study the contents and work through all the code within the following lessons:

• Quantifying expression using alignment-free methods (Salmon on multiple samples)
• QC with Alignment Data

• Documenting Steps in the Workflow with MultiQC

  NOTE: To run through the code above, you will need to be logged into FAS-RC and working on a compute node (i.e. your command prompt should have the word compute in it).

  1. Log in using ssh username@login.rc.fas.harvard.edu and enter your password (replace username with your username).
  2. Once you are on the login node, use salloc -p test -t 0-2:30 --mem 8G to get on a compute node or as specified in the lesson.
  3. Proceed only once your command prompt does not have the word login in it.
  4. If you log out between lessons (using the exit command twice), please follow points 1. and 2. above to log back in and get on a compute node when you restart with the self learning.

1. Complete the exercises:
   • Each lesson above contain exercises; please go through each of them.
   • Copy over your code from the exercises into a text file.
   • Upload the saved text file to Dropbox the day before the next class.

Questions?

• If you get stuck due to an error while runnning code in the lesson, email us
• Post any conceptual questions that you would like to have reviewed in class here.

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Day 3

Time	Topic	Instructor
09:30 - 10:10	Self-learning lessons review	All
10:10 - 10:45	Troubleshooting RNA-seq Data Analysis	Will
10:45 - 11:45	Automating the RNA-seq workflow	Meeta
11:45 - 12:00	Wrap up	Will

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• Downloadable Answer Keys (Day 2 exercises):
  • Experimental design (one possible solution)
  • sbatch script to run FASTQC for all samples
  • .out file
  • .err file.
• Downloadable Answer Keys (Day 3 exercises):
  • sbatch script to run salmon for all samples
• Automation Script

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Resources

• Video about statistics behind salmon quantification
• Obtaining reference genomes or transcriptomes
• Training materials from FAS-RC

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Building on this workshop

• Introduction to R workshop materials
• Introduction to Differential Gene Expression analysis (bulk RNA-seq) workshop materials

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These materials have been developed by members of the teaching team at the Harvard Chan Bioinformatics Core (HBC). These are open access materials distributed under the terms of the Creative Commons Attribution license (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.