Now “Now” generation sequencing has drastically changed the traditional costs and infrastructure within the sequencing community. There are several technologies, platforms and algorithms that show promise, but it is not always intuitive where to start. This uncertainty is compounded by the fact that commonly used analysis tools are difficult to build, maintain, and run effectively. Sample acquisition and preparation is quickly becoming a bottleneck as projects move from small sample sizes to hundreds or even thousands of samples. We will present case studies highlighting information, methods, challenges and opportunities in leveraging large scale high throughput sequencing and bioinformatics. Specifically we will highlight a recent genome-wide study of methylation patterns in 1575 individuals with Schizophrenia. We will also discuss several cancer transcriptome and exome sequencing projects as well as a human pathogen transcriptome characterization project consisting of multiple organisms and almost a billion reads. The Future The Ion Torrent PGM machine is a very promising, rapid throughput, ultra scalable sequencer that could play an integral part in future human health studies. Applications such as microbial whole genome sequencing, metagenomic characterization of environmental and microbiome sample, and targeted resequencing projects stand to benefit from this technology over time. To date we have completed more than 25 runs on a single PGM and will comment on the setup as well as sequence data and analysis.

1. Enabling Large Scale Sequencing Studies through Science as a Service (ScaaS) Justin H. Johnson Director of Bioinformatics EdgeBio Washington DC, USA

2. Agenda Who We Are NGS at 30K Challenges and Enabling Through ScaaS Transcriptome Projects Exome Projects Ion Torrent Data

4. Life Tech Service Provider

5. Contract Research Division Five SOLiD4 sequencing platforms One Life Techologies 5500XL Two Ion Torrent PGMs Automation thru Caliper Sciclone& BiomekFX Life Technologies Preferred Service Provider Agilent Certified Service Provider Commercial partnerships with companies such as CLCBio, DNANexusand Genologics MD/PhD & Masters Level Scientists and Bioinformaticians IT Infrastructure of >100 CPUs and >100TB storage

6. Edge BioServ Scientific Advisory Board Elaine Mardis, Ph.D. Co-Director, Genome Sequencing Center Washington University School of Medicine Sam Levy, Ph.D. Director of Genome SciencesScripps Translational Science Institute Scripps Genomic Medicine Michael Zody, M.S. Chief Technologist Broad Institute Ken Dewar, Ph.D. Assistant Professor McGill University and Genome Quebec Steven Salzberg, Ph.D. Director, Center for Bioinformatics and Computational Biology University of Maryland Gabor Marth, Ph.D. Professor of Bioinformatics Boston College Elliott Margulies, Ph.D. Investigator Genome Informatics Section National Human Genome Research Institute National Institutes of Health

8. Machines and Vendors GnuBio

9. Obligatory NGS Exponential Growth Slide Nature Biotechnology Volume 26 Number10 October2008

10. Ultra High Throughput + Lower Cost = Broader Applications

14. Choice of Library Construction

15. Depth of coverage

16. Re$ources

17. Number of Replicates

18. Number of Samples and Control

20. Flexibility with Standards and Scale Then (CE) – The Norm 10 Machines, 30 – 360 Days, 1 Project Now (Illumina/SOLiD/454) – Scale 1 machine, 14 Days, 30 Projects Now (Ion Torrent) - Flexibility 1 machine, 1 Day, 1 Project. Future (CLCBio, Nexus, Open Source) Standardization of analysis

21. Partial List of Mappers * BFAST - Blat-like Fast Accurate Search Tool. Written by Nils Homer, Stanley F. Nelson and Barry Merriman at UCLA.* Bowtie - Ultrafast, memory-efficient short read aligner. It aligns short DNA sequences (reads) to the human genome at a rate of 25 million reads per hour on a typical workstation with 2 gigabytes of memory. Uses a Burrows-Wheeler-Transformed (BWT) index. Link to discussion thread here. Written by Ben Langmead and Cole Trapnell. Linux, Windows, and Mac OS X.* BWA - Heng Lee's BWT Alignment program - a progression from Maq. BWA is a fast light-weighted tool that aligns short sequences to a sequence database, such as the human reference genome. By default, BWA finds an alignment within edit distance 2 to the query sequence. C++ source.* ELAND - Efficient Large-Scale Alignment of Nucleotide Databases. Whole genome alignments to a reference genome. Written by Illumina author Anthony J. Cox for the Solexa 1G machine.* Exonerate - Various forms of pairwise alignment (including Smith-Waterman-Gotoh) of DNA/protein against a reference. Authors are Guy St C Slater and Ewan Birney from EMBL. C for POSIX.* GenomeMapper - GenomeMapper is a short read mapping tool designed for accurate read alignments. It quickly aligns millions of reads either with ungapped or gapped alignments. A tool created by the 1001 Genomes project. Source for POSIX.* GMAP - GMAP (Genomic Mapping and Alignment Program) for mRNA and EST Sequences. Developed by Thomas Wu and Colin Watanabe at Genentec. C/Perl for Unix.* gnumap - The Genomic Next-generation Universal MAPper (gnumap) is a program designed to accurately map sequence data obtained from next-generation sequencing machines (specifically that of Solexa/Illumina) back to a genome of any size. It seeks to align reads from nonunique repeats using statistics. From authors at Brigham Young University. C source/Unix.* MAQ - Mapping and Assembly with Qualities (renamed from MAPASS2). Particularly designed for Illumina with preliminary functions to handle ABI SOLiD data. Written by Heng Li from the Sanger Centre. Features extensive supporting tools for DIP/SNP detection, etc. C++ source* MOSAIK - MOSAIK produces gapped alignments using the Smith-Waterman algorithm. Features a number of support tools. Support for Roche FLX, Illumina, SOLiD, and Helicos. Written by Michael Strömberg at Boston College. Win/Linux/MacOSX* MrFAST and MrsFAST - mrFAST & mrsFAST are designed to map short reads generated with the Illumina platform to reference genome assemblies; in a fast and memory-efficient manner. Robust to INDELs and MrsFAST has a bisulphite mode. Authors are from the University of Washington. C as source.* MUMmer - MUMmer is a modular system for the rapid whole genome alignment of finished or draft sequence. Released as a package providing an efficient suffix tree library, seed-and-extend alignment, SNP detection, repeat detection, and visualization tools. Version 3.0 was developed by Stefan Kurtz, Adam Phillippy, Arthur L Delcher, Michael Smoot, Martin Shumway, Corina Antonescu and Steven L Salzberg - most of whom are at The Institute for Genomic Research in Maryland, USA. POSIX OS required.* Novocraft - Tools for reference alignment of paired-end and single-end Illumina reads. Uses a Needleman-Wunsch algorithm. Can support Bis-Seq. Commercial. Available free for evaluation, educational use and for use on open not-for-profit projects. Requires Linux or Mac OS X.* PASS - It supports Illumina, SOLiD and Roche-FLX data formats and allows the user to modulate very finely the sensitivity of the alignments. Spaced seed intial filter, then NW dynamic algorithm to a SW(like) local alignment. Authors are from CRIBI in Italy. Win/Linux.* RMAP - Assembles 20 - 64 bp Illumina reads to a FASTA reference genome. By Andrew D. Smith and Zhenyu Xuan at CSHL. (published in BMC Bioinformatics). POSIX OS required.* SeqMap - Supports up to 5 or more bp mismatches/INDELs. Highly tunable. Written by Hui Jiang from the Wong lab at Stanford. Builds available for most OS's.* SHRiMP - Assembles to a reference sequence. Developed with Applied Biosystem's colourspace genomic representation in mind. Authors are Michael Brudno and Stephen Rumble at the University of Toronto. POSIX.* Slider- An application for the Illumina Sequence Analyzer output that uses the probability files instead of the sequence files as an input for alignment to a reference sequence or a set of reference sequences. Authors are from BCGSC. Paper is here.* SOAP - SOAP (Short Oligonucleotide Alignment Program). A program for efficient gapped and ungapped alignment of short oligonucleotides onto reference sequences. The updated version uses a BWT. Can call SNPs and INDELs. Author is Ruiqiang Li at the Beijing Genomics Institute. C++, POSIX.* SSAHA - SSAHA (Sequence Search and Alignment by Hashing Algorithm) is a tool for rapidly finding near exact matches in DNA or protein databases using a hash table. Developed at the Sanger Centre by Zemin Ning, Anthony Cox and James Mullikin. C++ for Linux/Alpha.* SOCS - Aligns SOLiD data. SOCS is built on an iterative variation of the Rabin-Karp string search algorithm, which uses hashing to reduce the set of possible matches, drastically increasing search speed. Authors are Ondov B, Varadarajan A, Passalacqua KD and Bergman NH.* SWIFT - The SWIFT suit is a software collection for fast index-based sequence comparison. It contains: SWIFT — fast local alignment search, guaranteeing to find epsilon-matches between two sequences. SWIFT BALSAM — a very fast program to find semiglobal non-gapped alignments based on k-mer seeds. Authors are Kim Rasmussen (SWIFT) and Wolfgang Gerlach (SWIFT BALSAM)* SXOligoSearch - SXOligoSearch is a commercial platform offered by the Malaysian based Synamatix. Will align Illumina reads against a range of Refseq RNA or NCBI genome builds for a number of organisms. Web Portal. OS independent.* Vmatch - A versatile software tool for efficiently solving large scale sequence matching tasks. Vmatch subsumes the software tool REPuter, but is much more general, with a very flexible user interface, and improved space and time requirements. Essentially a large string matching toolbox. POSIX.* Zoom - ZOOM (Zillions Of Oligos Mapped) is designed to map millions of short reads, emerged by next-generation sequencing technology, back to the reference genomes, and carry out post-analysis. ZOOM is developed to be highly accurate, flexible, and user-friendly with speed being a critical priority. Commercial. Supports Illumina and SOLiD data. Courtesy of SeqAnswers.com

22. Evolving Sequencing & Analysis Methods to Enable Genomic Research

24. Tracking (LIMS)

25. QC (Automation and Standardization)

27. CLC Bio and Genologics

28. Custom Algorithms

29. HPC and Storage

30. Onsite 100 TB NAS

33. tiRNA ATG AAA AAA ATG ATG ATG AAA AAA ATG ATG AAA ATG AAA genomic DNA Mammalian transcriptional complexity Mammalian Transcriptome Complexity TSS TSS TSS pA pA pA ATG ATG TSS pA PASR TASR miRNA AAA spliced intron microRNAs TSS pA polyadenylation signal transcription start site protein coding regions AAA translation start site polyadenylation non-coding regions ATG Courtesy of Life Technologies

35. Yet based on well-established methodologies

36. Substantial Benefits over Hybridization-Based Methods

37. Better quantitative gene expression performance (DGE)

38. In addition, can allow a comprehensive view of transcription (Whole Transcriptome)

39. Transcriptome projects overview

40. Identification of imprinted genes contributing to specific brain regions by whole transcriptome sequencing

41. 24 sample cohort for basic human expression and variant analysis in diseased patients.

42. 32 Sample cohort looking at novel splice junctions, gene fusions, and differential expression of colon cancer samples over a time series

44. Sample Sourcing for Transcriptome Projects Blood: Large quantities of sample available, but with limited utility in transcriptome analysis Tissue: Needle biopsy most common, but sample quantity very low Surgical section: Larger quantities available, but limited utility; need laser capture microdissection to provide useful results, sample quantity very low FFPE Slides: Very useful in clinical research but amount of sample and quality low.

45. Unamplified vs Amplified Prostate Cancer Cell Line (Vcap) from CPDR Well characterized Differential Expression upon the addition of androgens. Compared transcriptome from a single pool of RNA Unamplified, ribosomally depleted (Ribominus™) Amplified, no ribosomal depletion required Two Pipelines for analysis

46. Amplification Gives Different Results Gene Expression in Unstimulated Cells Unamp Amplified 14,075 2112 1071

47. Spearman’s Correlation from 2 Pipelines

49. RNA-Seq Analysis Between Pipelines is Either Concordant Amplified, Stimulated, Pipe A Amplified, Stimulated, Pipe B

50. Or not… Unamplified, Stimulated, Pipe A Unamplified, Stimulated, Pipe B

51. Even if you remove all SNORA and SNORD Unamplified, Stimulated, Pipe A Unamplified, Stimulated, Pipe B

52. NM refseq NR refseq Histones (circles) SNORD/SNORA rRNA dots PolyA Selection vs Ribosomal Depletion Courtesy of Life Technologies

55. Join discordance

56. Scripting

57. Visualization

60. Fine map a region

61. Capturing and interrogating the exome

62. Catalogue variants for downstream filtering and identification of causative mutation(s)

63. Exome and Targeted Resequencing projects overview

64. Identification of the genetic basis of colorectal cancer through exome sequencing

65. 600+ sample cohort to identify the genetic basis of a novel syndrome

66. Exome sequencing of Tumor/Normal Leukemia patients to identify novel mutations present in tumor samples

68. Targeted Capture Technologies NimblegenSeqCap EZ Agilent SureSelect NimblegenSeqCap EZ FebitHybSelect Agilent SureSelect LR-PCR Raindance Technologies Fluidigm 20Kb 1 MB 2 MB 3 MB 4 MB 5 MB 30-50MB Exome Genomic Region Captured

70. Ultimately Comes to Variation Coverage Project Design Cohorts Cancer Algorithms a Solved Problem? Single open source pipelines Single commercial pipelines Proprietary internal algorithms. A mixture?

71. Ultimately Comes to Variation Coverage Project Design Cohorts Cancer Algorithms Solved Problem? Single open source pipelines Single commercial pipelines Proprietary internal algorithms. A mixture?

72. EdgeBioExome Coverage Statistics

73. EdgeBio Exon Coverage StatisticsHow well is the exome covered?* * Data from Fragment Runs – Since moving to PE, seeing 15% improvement

74. Venter Genome - Algorithms PLOS genetics 2008 vol 4 issue 8 e10000160 ~21K SNP in exons (29MB Targeted) 36,206 expected SNPs for 50MB Kit

75. 3 Tools and Associated SNP Counts Software A 45,551 Software B 29,814 Software C 40,964

76. Software B v. Software A A 45,511 B 29,814 21,250 24,261 8,564 Union: 54,075 Intersection: 21,250 Not to Scale

77. Software B v. Software C C 40,964 B 29,814 23,456 17,508 6,358 Union: 47,322 Intersection 23,456

78. Software A v. Software C C 40,964 A 45,511 30,773 10,191 14,738 Union: 55,702 Intersection: 30,773

79. A 45,511 B 29,814 13,130 4,750 1,608 19,642 3,814 11,131 6,377 Union: 60,452 Intersection: 19,642 Voting Scheme (2/3): 36,195 C 40,964

82. Join discordance

83. Scripting

84. Visualization

85. Better algorithms for variant calling

86. Cancer specific

87. Standardization of algorithms for variant calling

90. Ion Torrent PGM Longer, Accurate Reads in 2.5 Hours Microbial & Viral Resequencing Microbial & Viral De novo Applications Eukaryotic Amplicon Sequencing Metagenomics WGS 16S Surveys

91. Ion Torrent PGM

92. Ion Torrent PGM

93. Ion Torrent PGM

94. Real World Examples – Speed Rapid sequenced the genome of the Escherichia coli strain from European outbreak “…[University of Münster & Life Tech] ]received the samples on Monday, began sequencing that evening, and began analyzing the data on Wednesday…” “…Justin Johnson, director of bioinformatics at EdgeBio, assembled and analyzed the raw reads made publicly available by BGI using CLC Bio's software…Johnson said his analysis took just a couple of hours…

95. Acknowledgements CPDR (Center for Prostate Disease Research) Collaboration Shyh-Han Tan, Ph.D. DNA Farber Cancer Institute Collaboration Andrew Lane M.D.,Ph.D.; David Weinstock M.D.; Oliver Weigert M.D.,Ph.D Scripps Translational Health Samuel Levy Sequencing Team led by Joy Adigun EdgeBio Research IFX led by John Seed, Ph.D. and Quang Nguyen MD, Ph.D.

96. QuestionsTwitter: @Bioinfojjohnson@edgebio.com