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Genome Annotation using MAKER-P at iPlant Collaboration with Mark Yandell Lab (University of Utah) www.yandell-lab.org iPlant: Josh Stein (CSHL) Matt Vaughn.

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Presentation on theme: "Genome Annotation using MAKER-P at iPlant Collaboration with Mark Yandell Lab (University of Utah) www.yandell-lab.org iPlant: Josh Stein (CSHL) Matt Vaughn."— Presentation transcript:

1 Genome Annotation using MAKER-P at iPlant Collaboration with Mark Yandell Lab (University of Utah) www.yandell-lab.org iPlant: Josh Stein (CSHL) Matt Vaughn (TACC) Dian Jiao (TACC) Zhenyuan Lu (CSHL) Nirav Merchant (U. Arizona) Carson Holt (Ontario Institute Cancer Research) Campbell et al. Plant Physiology. DOI:10.1104/pp.113.230144 Cantarel et al. 2008. Genome Research 18:188 Holt & Yandell. 2011. BMC Bioinformatics 12:491

2 Assembly & Annotation at iPlant

3 What Are Annotations? Annotations are descriptions of features of the genome Structural: exons, introns, UTRs, splice forms etc. Coding & non-coding genes Expression, repeats, transposons Annotations should include evidence trail Assists in quality control of genome annotations Examples of evidence supporting a structural annotation: Ab initio gene predictions ESTs Protein homology

4 Secondary Annotation Protein Domains InterPro Scan: combines many HMM databases GO and other ontologies Pathway mapping E.g. BioCyc Pathway tools

5 Challenges in Plant Genome Annotation Genomes are BIG Highly repetitive Many pseudogenes Assembly contamination Incomplete evidence No method is 100% accurate

6 Options for Protein-coding Gene Annotation Yandell & Ence. Nature Reviews Genetics 13, 329-342 (May 2012) | doi:10.1038/nrg3174

7 Typical Annotation Pipeline Contamination screening Repeat/TE masking Ab initio prediction Evidence alignment (cDNA, EST, RNA-seq, protein) Evidence-driven prediction Chooser/combiner Evaluation/filtering Manual curation

8 MAKER-P Automated Pipeline Ab initio prediction Evidence MPI-enabled to allow parallel operation on large compute clusters

9 Quality Control evaluation of the MAKER-P and TAIR10 datasets using Annotation Edit Distance (AED). Better Quality Worse

10 W559 - Annotation of the Lobolly Pine Megagenome—Jill Wegrzyn 20.15 Gb assembly—split into 40 jobs—216 CPU/job (8640 CPU total)—17 hours P157 - Disease Resistance Gene Analysis on Chromosome 11 Across Ten Oryza Species 10 rice species (each w/12 chromosome pseudomolecules) 96 CPU per chromosome (1152 CPU total) ~ 2hr per genome 10 22,656 CPU cores on1,888 nodes GenomeAssembly Size (Mb) CPU Run Time Arabidopsis thalianaTAIR101206002:44 Arabidopsis thalianaTAIR1012015001:27 Zea maysRefGen_v2206721722:53 TACC Lonestar Supercomputer Campbell et al. Plant Physiology. December 4, 2013, DOI:10.1104/pp.113.230144 PAG 2014: MAKER-P at iPlant

11 Virtual image MPI-enabled for parallel computing Check out with up to 16 CPU Tested with 4 CPU instance (rice chr 1 in 8 hr 45 min) Tutorial:https://pods.iplantcollaborative.org/wiki/display/ sciplant/MAKER-P+Tutorial+%28Atmosphere%29 11 Atmosphere: MAKER_2.28 (emi-F13821D0)

12 Future Plans TACC Lonestar Supercomputer Discovery Environment GUI


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