Scalable Solutions for DNA Sequence Analysis
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1 Scalable Solutions for DNA Sequence Analysis Michael Schatz Dec 4, 2009 JHU/UMD Joint Sequencing Meeting
2 The Evolution of DNA Sequencing Year Genome Technology Cost 2001 Venter et al. Sanger (ABI) $300,000, Levy et al. Sanger (ABI) $10,000, Wheeler et al. Roche (454) $2,000, Ley et al. Illumina $1,000, Bentley et al. Illumina $250, Pushkarev et al. Helicos $48, Drmanac et al. Complete Genomics $4,400 (Pushkarev et al., 2009) Critical Computational Challenges: Alignment and Assembly of Huge Datasets
3 Alignment Research Highlights Assembly Crossbow Searching for SNPs with Cloud Computing (Langmead, Schatz, Lin, Pop, Salzberg, 2009) Hawkeye Assembly Visualization & Analytics (Schatz, Phillippy, Shneiderman, Salzberg, 2007) CloudBurst Highly Sensitive Read Mapping with MapReduce (Schatz, 2009) AutoEditor & AutoJoiner Improving Genome Assemblies without Resequencing (Gajer, Schatz, Salzberg, 2004) (Carlton et al., 2007) MUMmerGPU High Throughput Sequence Alignment Using GPUs (Schatz, Trapnell, Varshney, Delcher, 2007) (Trapnell, Schatz, 2009) Assembly Forensics Finding the Elusive Mis-assembly (Phillippy, Schatz, Pop, 2008)
4 Short Read Assembly Reads de Bruijn Graph Genomes AAGA ACTT ACTC ACTG AGAG CCGA CGAC CTCC CTGG CTTT CCG TCC AAGACTCCGACTGGGACTTT CGA CTC AAGACTGGGACTCCGACTTT AAG AGA GAC ACT CTT TTT GGA CTG GGG TGG! Genome assembly as finding an Eulerian tour of the de Bruijn graph! Human genome: ~3B nodes, ~10B edges! The new short read assemblers require tremendous computation! Velvet (Zerbino & Birney, 2008) on human > 2 TB of RAM! ABySS (Simpson et al., 2009) on human ~4 days on 168 cores
5 Hadoop MapReduce! MapReduce is the parallel distributed framework invented by Google for large data computations.! Data and computations are spread over thousands of computers, processing petabytes of data each day (Dean and Ghemawat, 2004)! Indexing the Internet, PageRank, Machine Learning, etc! Hadoop is the leading open source implementation! Benefits! Scalable, Efficient, Reliable! Easy to Program! Runs on commodity computers! Challenges! Redesigning / Retooling applications! Not SunGrid, Not MPI! Everything in MapReduce
6 K-mer Counting with MapReduce! Application developers focus on 2 (+1 internal) functions! Map: input! key, value pairs! Shuffle: Group together pairs with same key! Reduce: key, value-lists! output Map, Shuffle & Reduce All Run in Parallel ATGAACCTTA! ATG,1! AAC,1! CTT,1! TGA,1! ACC,1! TTA,1! GAA,1! CCT,1! ACA -> 1! ATG -> 1! CAA -> 1,1! GCA -> 1! TGA -> 1! TTA -> 1,1,1! ACA:1! ATG:1! CAA:2! GCA:1! TGA:1! TTA:3! GAACAACTTA! GAA,1! CAA,1! CTT,1! AAC,1! AAC,1! TTA,1! ACA,1! ACT,1! ACT -> 1! AGG -> 1! CCT -> 1! GGC -> 1! TTT -> 1! ACT:1! AGG:1! CCT:1! GGC:1! TTT:1! TTTAGGCAAC! map TTT,1! AGG,1! CAA,1! TTA,1! GGC,1! AAC,1! TAG,1! GCA,1! shuffle AAC -> 1,1,1,1! ACC -> 1! CTT -> 1,1! GAA -> 1,1! TAG -> 1! reduce AAC:4! ACC:1! CTT:2! GAA:2! TAG:1!
7 Genome Assembly with MapReduce! Challenges! Nodes stored on different computers! Node only knows immediate neighbors! Randomized List Ranking! Randomly assign H / T to each compressible node! Compress H -> T links Randomized Speed-ups in Parallel Computation. Vishkin U. (1984) ACM Symposium on Theory of Computation
8 Contrail!"#$%%&'()*+,-./,'01'2*&34'*530(3)6 Genome Assembly with MapReduce 1.! Build Compressed de Bruijn Graph 2.! Correct Errors & Resolve Short Repeats 3.! Cloud Surfing: Mate directed repeat resolution & scaffolding (a) Compression (b) Bubble Popping (c) Repeat Analysis (d) Cloud Surfing x r a b r d y c r 1 a r b r c r d x+y r 2 (Chaisson, 2009) Assembly of Large Genomes with Cloud Computing. Schatz MC, Sommer D, Pop M, et al. In Preparation.
9 Summary 1.! Managing the tidal wave of NextGen sequence data is a central challenge in biology 2.! Hadoop is well suited towards scaling up biological computation 3.! Cloud computing is an attractive platform to augment resources 4.! Look for many cloud computing & MapReduce solutions this year
10 Advisor Steven Salzberg Acknowledgements UMD Faculty Mihai Pop, Art Delcher, Amitabh Varshney, Carl Kingsford, Ben Shneiderman, James Yorke, Jimmy Lin, Dan Sommer CBCB Students Adam Phillippy, Cole Trapnell, Saket Navlakha, Ben Langmead, James White, David Kelley
11 Thank You!
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