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Tuesday

Tuesday

Jul 30, 2015

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Lecture: Genome Assembly - Haibao Tang (8:30-10:00)

  • Assembly preparation – reads, libraries, etc.

  • Assembly algorithms - OLC assemblers vs. de Bruijn (K-mer) graph assemblers

  • Assembly QC - Gather assembly statistics and identify issues

  • Assembly curation - Further scaffolding, build chromosomes using mapping evidence

Slides: https://drive.google.com/file/d/0Bx3KTjwwBb0rQUhWM2JQYnA5RmM/edit?usp=sharing

Break (10:00-10:15)

Hands-On: Assemble a chromosome of baker's yeast (10:15-12:00)

Group Projects

  1. You are pre-assigned to one of 5 groups, each working on a different dataset

  2. We will discuss approaches and results in a group setting

  3. Present results as a group

de novo assembly hands-on guide: https://docs.google.com/document/d/1gm30phBGHukScFGx-dv2piTiGQpVK-iHoK_Z6cGpajI/edit?usp=sharing

  1. Use three algorithms to assemble your data set (VELVET, ABYSS, SOAP)

    1. Know how to change K-mer in assembler option, and try different K-mers

    2. Available via OSU HPC and iPlant DE

  2. Identify which assembly has best metrics

    1. Length stats (N50, sum) and plots with QUAST

    2. Dot plot to a reference genome with NUCMER

  3. Group discussion: Best assembly for the fungal dataset (10 m)

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Lecture: Read mapping and genetic variants - Haibao Tang (1:00-2:30)

  • Read mapping

  • Variant calling

  • Variant annotation

  • Clinical applications

Slides: https://drive.google.com/file/d/0Bx3KTjwwBb0rMTdZSHRMVGRMeUE/edit?usp=sharing

Break (2:30-2:45)

Hands-On: Identify and annotate genetic variants of a mutant yeast 2:45-5:00

Genome mapping hands-on guide: https://docs.google.com/document/d/1H2d1d9cp35ajLu-IlN_dnLEqBKjIWZOHPzoTW4Qek6s/edit?usp=sharing

  1. Compare two methods of finding SNPs - mapping assembly vs. mapping reads (preferred)

  2. Understand and run the SNP calling pipeline (BWA -> MPILEUP)

  3. Visualize read alignments and variants in IGV genome browser (instructions on how to run IGV in manual)

  4. Determine possible effect of a few best quality SNPs

  5. Understand how to categorize the SNPs according to locations and effects

  6. Group discussion: Best approach and criteria to call SNPs; discuss the significance of the SNPs called

Wrap-up (5:00- )

Link to download Megan 5.3:

http://ab.inf.uni-tuebingen.de/data/software/megan5/download/MEGAN_windows-x64_5_5_3.exe