Next-Gen Sequence Analysis Workshop (2016)

This is the schedule for the 2016 MSU NGS course. All course communications will be organized around the Slack channel.

This workshop has a Workshop Code of Conduct, do read it!

Download all of these materials or visit the GitHub repository.

Meal Times: Breakfast 7:45-8:45, Lunch 12-1, Dinner 6-7 (Unless noted below). See HERE for the menu and other info.

Day	Schedule
Monday 8/8	1:30pm lecture: Welcome! (Meg and Matt) 2:30pm: Getting Started with AWS Getting started with Amazon EC2 (Matt) 4pm: Intro to Linux Setup your AWS instance and UNIX Toolkit and Online Tutorial (Matt) 7pm tutorial, background PDF BLAST Running command-line BLAST (Meg) 8pm: Instructor and TA Research presentations, socialize
Tuesday 8/9	Tutorial Day 2 – Intro to Linux & Quality control 9:15am lecture: Sequencing basics (Matt) 11:00am Assessment (Bob Drost) 1:15pm tutorial, background PDF and Quality Trimming (Matt) 3:00pm Opionated guide to making a computational notebook. (Matt and other people) Evening firepit social
Wed 8/10	9:15am lecture, mapping and variant calling lecture (Meg) 10:00am practical Variant Calling, Variant calling (Meg) 1:15pm LinuxBrew slides (Shaun) 1:45pm practical, Installing Linuxbrew on AWS Ubuntu 14 Install Linuxbrew on your AWS instance (Torst) 2:15pm tutorial, BASH for genomics, BASH for Genomics (Amanda) 7:00pm Mapping Quest Map Quest (All) 8:30pm student presentations (Part 1 ~3 minutes each)
Thursday 8/11	9:15am lecture, Intro to genome assembly (Torst) 10:15am Genome assembly practical (Shaun) 1:15pm Genome assembly practical (continued) 2:15pm lecture, De Bruijn graph assembly (Shaun) 7:15pm Assembly challenge Assembly Quest (Matt)
Friday 8/12	9:15am Debrief of Assembly Quest marathon (Matt) 9:30am lecture, Bacterial genome annotation (Torst) 10:00am practical Prokka Bacterial genome annotation using Prokka (Torst) 11:00am practical Species identification with Kraken Species identification with Kraken (Torst) 1:15pm tutorial, Intro to R Intro to R (Amanda) 6:00pm Thai food take out at Mcrary Hall 7:30pm Mars Rover Challenge! (Shaun) 8:30pm Finish up student presentations
Saturday 8/13	9:15am Population genetics lecture and practical (Sonal) 10:30am practical, Population Genetics Tutorial (Sonal) 1:15pm lecture, long read sequencing (Torst) 2:00pm practical, Assessing and Assembling Nanopore data (Lisa) 6:00pm BBQ on the island if nice out, in the classroom if not
Sunday 8/14	Free Day Brunch at McCrary 12pm - 1pm* Dinner field trip to Kalamazoo
Monday 8/15	9:15am , Transcriptome assembly & evaluation lecture and Trinity and Transcriptome Evaluation (Matt) 1:15pm Alignment / Mapping lecture and practical (Rob) 6:30pm LATER DINNER TIME 7:45pm: Twitter, Blogging and Bioinformatics (All) 8:30pm: Finish up student presentations! (All)
Tuesday 8/16	9:15am Transcript quantification lecture (Rob) 10:30am practical Using Salmon for read counts (Rob) 11:45pm lecture, mRNAseq differential expression (Ian) 12:30pm Lunch (new later time) 1:15pm Visualizing RNA-Seq counts with Degust (Torst) 1:45pm mRNA stats (Ian) 2:45pm practical Using DEseq2 for DGE (Ian) 6:00pm Dinner (back to original time) 7:15pm Optional Arabidopsis - De novo assembly vs Reference Guided Assembly
Wed 8/17	9:15am lecture and Sourcing NCBI data including SRA practical (Meg) 10:15am More fun with R (Ming) 12:00 Lunch Bonus Routes Through Differential Expression Analysis 1:00pm UNIX Stuff UNIX Toolkit (All) [tentative] 6:00pm Dinner 7:15pm Work on your own data, ask questions..
Thursday 8/18	9:15am Open source your scripts with GitHub (Lisa) Using GitHub repositories to store your scripts 11:30 Jupyter Notebook (Lisa) Jupyter notebook demo 1:15pm Assessment (Bob Drost) Meet outside classroom after assessment for group photo 2pm: Functional Annotation slides and Functional Annotation (Meg) 6:00pm Dinner Evening: Ask the Expert (All)
Friday 8/19	9:15-9:45 Closing Lecture! (Meg and Matt) 10am discussion about class; more stuff Links: Opinionated guides to NGS / Software Carpentry Data Carpentry

Dramatis personae

Instructors:

• Meg Staton @HardwoodGenomic.
• Matt MacManes @macmanes.
• Torsten Seemann @torstenseemann.
• Shaun Jackman @sjackman.
• Rob Patro @nomad421.
• Ian Dworkin @IanDworkin.
• Sonal Singhal
• Amanda Charbonneau @procrastinomics.

TAs:

• Lisa Cohen @monsterbashseq.
• Will Pitchers @steeljawpanda.
• Ming Chen

She Who Drives Many Places:

• Kate MacManes

Genome Assembly References

• Ben Langmead Resources
• How do we assemble genomes (videos)

Papers and References

Books

• Bioinformatics Data Skills

• Practical Computing for Biologists

  These books, especially the 1st, are highly recommended book for people looking for a systematic presentation on shell scripting, programming, UNIX, etc.

RNAseq

• Differential gene and transcript expression analysis of RNA-seq experiments with TopHat and Cufflinks, Trapnell et al., Nat. Protocols.

  One paper that outlines a pipeline with the tophat, cufflinks, cuffdiffs and some associated R scripts.

• Statistical design and analysis of RNA sequencing data., Auer and Doerge, Genetics, 2010.

• A comprehensive comparison of RNA-Seq-based transcriptome analysis from reads to differential gene expression and cross-comparison with microarrays: a case study in Saccharomyces cerevisiae. Nookaew et al., Nucleic Acids Res. 2012.

• Challenges and strategies in transcriptome assembly and differential gene expression quantification. A comprehensive in silico assessment of RNA-seq experiments Vijay et al., 2012.

• Computational methods for transcriptome annotation and quantification using RNA-seq, Garber et al., Nat. Methods, 2011.

• Evaluation of statistical methods for normalization and differential expression in mRNA-Seq experiments., Bullard et al., 2010.

• A comparison of methods for differential expression analysis of RNA-seq data, Soneson and Delorenzi, BMC Bioinformatics, 2013.

• Measurement of mRNA abundance using RNA-seq data: RPKM measure is inconsistent among samples., Wagner et al., Theory Biosci, 2012. Also see this blog post explaining the paper in detail.

Computing and Data

• A Quick Guide to Organizing Computational Biology Projects, Noble, PLoS Comp Biology, 2009.
• Willingness to Share Research Data Is Related to the Strength of the Evidence and the Quality of Reporting of Statistical Results, Wicherts et al., PLoS One, 2011.
• Got replicability?, McCullough, Economics in Practice, 2007.

Also see this great pair of blog posts on organizing projects and research workflow.

Links

Humor

• Data Sharing and Management Snafu in 3 Short Acts

Resources

• Biostar

  A high quality question & answer Web site.

• SEQanswers

  A discussion and information site for next-generation sequencing.

• Software Carpentry lessons

  A large number of open and reusable tutorials on the shell, programming, version control, etc.

Blogs

• http://www.genomesunzipped.org/

  Genomes Unzipped.

• http://ivory.idyll.org/blog/

  Titus’s blog.

• http://bcbio.wordpress.com/

  Blue Collar Bioinformatics

• http://massgenomics.org/

  Mass Genomics

• http://blog.nextgenetics.net/

  Next Genetics

• http://gettinggeneticsdone.blogspot.com/

  Getting Genetics Done

• http://omicsomics.blogspot.com/

  Omics! Omics!

• http://lab.loman.net/

  Nick Loman’s lab notebook

• http://TheGenomeFactory.blogspot.com/

  The Genome Factory (Torsten Seemann)

Material from previous years

• Day 1 - Getting started with Amazon
  • Getting started with Amazon EC2
    • Details!
      • Start up an EC2 instance
        • Log in
        • Select your zone
        • Select the machine operating system to boot
        • Choose the machine size
        • Change the size of the hard drive
        • Confirm and launch
        • (First time through) generate a new key pair
        • (Next times through) select an existing key pair
        • Click on View Instances
        • Select the public DNS name for later use
      • Logging into your new instance “in the cloud” (Windows version)
        • Install mobaxterm
        • Start a new session
        • Fill in session settings
        • Specify the session key
        • Click OK
      • Logging into your new instance “in the cloud” (Mac version)
      • Terminating your instance
      • Amazon Web Services reference material
  • Running command-line BLAST
    • Install software
    • Get Data
    • BLAST
    • Summary
• Day 2 – Intro to Linux & Quality control
• Variant calling
  • Booting an Amazon AMI
  • Install software
  • Download data
  • Rename the reference
  • Read mapping
  • Visualizing alignments
  • Statistics of alignments
  • Calling SNPs
  • Using IGV for Visualization
  • Student Exercise
• Interval Analysis and Visualization
  • Data collection
• Running bedtools
• Understanding the SAM format
• Control Flow and loops in R
  • Control Flow
    • The standard if else
  • ifelse()
  • Other vectorized ways of control flow.
  • Simple loops
    • while() function..
  • for loop
  • So for the for loop we would do the following:
  • More avoiding loops
  • The step above creates a vector of n NA’s. They will be replaced sequentially with the random numbers as we generate them (using a function like the above one).
• Variant calling and exploration of polymorphisms
  • ## Getting the data and installing extra packages
  • Let’s do another round of variant calling
  • Variant exploration with Bioconductor
  • Quality control
• A complete de novo assembly and annotation protocol for mRNASeq
  • Switching to root
  • Updating the software on the machine
  • Downloading the sample data
  • Starting on the protocols
  • Actually using the BLAST Web server
• Assembly with SOAPdenovo-Trans
• Mapping and Counting
• Analyzing RNA-seq counts with DESeq
• RNA-seq: mapping to a reference genome with tophat and counting with HT-seq
• RNA-seq: mapping to a reference genome with BWA and counting with HTSeq
• Booting an Amazon AMI
• Updating the operating system
• Install software
• Preparing the reference
• Mapping
  • Optional - Script these steps
• Genome comparison and phylogeny
  • Interactive visual genome comparison with Mauve
  • Running a genome alignment
  • Booting an Amazon AMI
  • Logging in & updating the operating system
  • Packages to install
  • Getting the E. coli genome data
  • What is the nearest reference genome?
  • Ordering the assembly contigs against a nearby reference
  • Making a phylogeny of many E. coli assemblies
  • From tree file to figures
• Automation, scripts, git, and GitHub
  • Automation and scripts
  • Some git koans
    • Forking a repository on github
    • Create a new file on github and edit it, then pull
    • Edit local file and push to github
    • Create a new repository; add some files to it.
• MG-RAST and its API
  • Example Usage
  • Exercise - Download
  • Working with Annotations
  • A note on JSON
  • Exercise - linking MG-RAST to taxonomy
• So you want to get some sequencing data out of NCBI?
  • The challenge
  • What is an API and how does it relate to NCBI?
  • Automating with an API
  • Exercise - Downloading data
  • Comment on Genbank files
  • Challenge:
• Looking at k-mer abundance distributions
• PacBio Tutorial
• RNASeq Transcript Mapping and Counting (BWA and HtSeq Flavor)
  • Booting an Amazon AMI
  • Updating the operating system
  • Install software
• Evaluating the quality of your short reads, and trimming them
  • Logging in
  • Packages to install
  • Getting some data
  • Trimming and quality evaluation of your sequences
• Getting started with Amazon EC2
  • Details!
    • Start up an EC2 instance
      • Log in
      • Select your zone
      • Select the machine operating system to boot
      • Choose the machine size
      • Change the size of the hard drive
      • Confirm and launch
      • (First time through) generate a new key pair
      • (Next times through) select an existing key pair
      • Click on View Instances
      • Select the public DNS name for later use
        • Next steps
    • Logging into your new instance “in the cloud” (Windows version)
      • Install mobaxterm
      • Start a new session
      • Fill in session settings
      • Specify the session key
      • Click OK
    • Logging into your new instance “in the cloud” (Mac version)
    • Terminating your instance
    • Amazon Web Services reference material
• Instructor’s Guide to ANGUS Materials
  • Licensing
• Workshop Code of Conduct
  • Need Help?
  • The Quick Version
  • The Less Quick Version

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LICENSE: This documentation and all textual/graphic site content is licensed under the Creative Commons - 0 License (CC0) -- fork @ github. Presentations (PPT/PDF) and PDFs are the property of their respective owners and are under the terms indicated within the presentation.

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