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Ideas to implement or to icebox but get out of your head.

Introduction

  • Introduction
  • Preface
  • what is bioinformatics
  • Data Terminology
  • Sequencing Technologies
  • File Formats

Experimental Design

This section could be skipped if they want to start working right away

  • Introduction to Experimental Design
    • Learning Objective
    • What is your biological question?
    • Biological system
    • Sequencing technology
    • Funding and cost
    • prelude to examples
  • Examples
    • Sex determination
      • Seriola 90 fish experiment.
    • Genome Assembly
      • Seriola dorsalis genome
      • Red abalone genome
      • Teosinte genome
      • Wasp genome
      • metagenome
    • Genome Annotation
      • Seriola
      • Wasp
    • 16S

Data Acquisition

  • What dataset will we use throughout this text
    • Why Arabidopsis
    • How to download our primary dataset
  • Where to find and download data? fastq, fasta, genome, etc
  • sra
  • geo
  • ncbi
  • iplant
  • etc
  • How to transfer Data
  • scp
  • Rsync
  • wget
  • globus

Data wrangling

  • Review of fasta/fastq file format
  • Problems and solutions
  • fastq -> fasta
  • fastq quality trimming

Data Analysis

  • Introduction to Data analysis
  • RNA-Seq Analysis (intro)
  • Arabidopsis with a genome
    • Which genes are significant?
  • Arabidopsis without a genome
    • Which genes are significant?
  • Comparison of Arabidopsis with and without a genome.
    • How are the results different?
      • Venn diagram of significant genes.
    • How are they the same?
  • Example 2
  • Example 3
  • Genome Assembly
  • introduction to Genome assembly
  • List of assembly programs
  • How to pick a genome assembly programs
  • Assumptions and limitations of domain and data.

visualization

  • Introduction to R
  • Introduction to iPython
  • Introduction to Cytoscape

Appendix

  • Introduction to Unix and Terminals

Book Format options

  • Choose your own adventure series. Create a storyline that requires the users to solve problems (real world) using sequencing data. Hospital outbreak, Ebola virus spread, etc.
  • Would need them to somehow make choices that would lead them down different paths.

Collection of links to explore