Class Schedule

If notebooks won’t load view them in nbviewer

Pre-Class

• Set up your TSCC account
  • Intructions Mac Windows
  • Practice UNIX here
  • Download Anaconda using these instructions

Sep 23 (Mon) 9am – 1pm

Intro to Sequencing, Unix, Data Download, Fastqc

• Notebooks
  • 1 Intro to bash commands
  • 2 TSCC login and Downloads
  • 3 Data downloads and quality checks
• Lecture
  • Intro to Bootcamp and RNA-seq

Sep 24 (Tue) 9am – 11am

Submitting Jobs to Cluster Intro to Alignment, STAR alignment

• Notebooks
  • 4 STAR index and alignment
• Tutorial
  • TSCC Job submission
• Lecture
  • STAR Alignment and TSCC Job submission

Sep 25 (Wed) 9am – 1pm

Samtools and FeatureCounts

• Notebooks
  • 5 Samtools
  • 6 FeatureCounts1
  • 7 FeatureCounts2
  • 8 Python demo - Counts and Conditions
  • 9 Functions example RPKM and TPM
• Tutorials
  • Set up Jupyter Notebooks
• Lecture
  • Samtools, FeatureCounts, RPKM/TPM Lecture

Sep 26 (Thurs) 11am-1pm

Differential Expression

• Notebooks for running DESeq2 in R Kernel
  • 10 DESeq2 Installs
  • 11 DESeq2 Analysis
• Notebooks for running DESeq2 in RStudio (on local computer)
  • 10 RStudio Install Instructions
  • 11 RStudio DESeq2 Analysis
• Lecture
  • DESeq2 and gene expression

Oct 2 (Wed) 9am – 1pm

GO Term Analysis, Data Visualization, and Group Presentations

• Notebooks
  • 12 Plotting in Python
  • 13 Pathway Analysis
• Lecture
  • [Pathway Analysis(https://github.com/macatbu/biom200_bootcamp_2019/blob/master/lectures/Bootcamp%20Day%205.pdf)

This years bootcamp is based off of materials prepared for past years by Emily Wheeler 2017 Ryan Marina 2018

Office Hours

On Slack, email mcburns@ucsd.edu for access.

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Group Project

Project example

Genome information for human reference genome

Project description: In your groups find a published RNA-seq data set on human cells. Use the skills you learned in class to process and analyze the data. Tell us what the results tell us about the biological question. Create a 8 slide, ~10 minute presentation on it.

In your presentation include: Where is this dataset from? What question were they answering in this experiment? Generate a PCA plot and heatmap to compare the samples. Show a volcano plot showing differential expression.

In class on Wednesday we will do more data analysis and plotting using Python. Keep your clean_counts.csv file and share it with everyone in your group. Graphs you generate in the last class can be added to the end of your presentation.

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