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Introduction to next generation sequencing
Introduction to next generation sequencing
Introduction to next generation sequencing
Introduction to next generation sequencing
Introduction to next generation sequencing
Introduction to next generation sequencing
Introduction to next generation sequencing
Introduction to next generation sequencing
Introduction to next generation sequencing
Introduction to next generation sequencing
Introduction to next generation sequencing
Introduction to next generation sequencing
Introduction to next generation sequencing
Introduction to next generation sequencing
Introduction to next generation sequencing
Introduction to next generation sequencing
Introduction to next generation sequencing
Introduction to next generation sequencing
Introduction to next generation sequencing
Introduction to next generation sequencing
Introduction to next generation sequencing
Introduction to next generation sequencing
Introduction to next generation sequencing
Introduction to next generation sequencing
Introduction to next generation sequencing
Introduction to next generation sequencing
Introduction to next generation sequencing
Introduction to next generation sequencing
Introduction to next generation sequencing
Introduction to next generation sequencing
Introduction to next generation sequencing
Introduction to next generation sequencing
Introduction to next generation sequencing
Introduction to next generation sequencing
Introduction to next generation sequencing
Introduction to next generation sequencing
Introduction to next generation sequencing
Introduction to next generation sequencing
Introduction to next generation sequencing
Introduction to next generation sequencing
Introduction to next generation sequencing
Introduction to next generation sequencing
Introduction to next generation sequencing
Introduction to next generation sequencing
Introduction to next generation sequencing
Introduction to next generation sequencing
Introduction to next generation sequencing
Introduction to next generation sequencing
Introduction to next generation sequencing
Introduction to next generation sequencing
Introduction to next generation sequencing
Introduction to next generation sequencing
Introduction to next generation sequencing
Introduction to next generation sequencing
Introduction to next generation sequencing
Introduction to next generation sequencing
Introduction to next generation sequencing
Introduction to next generation sequencing
Introduction to next generation sequencing
Introduction to next generation sequencing
Introduction to next generation sequencing
Introduction to next generation sequencing
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Introduction to next generation sequencing

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  • 1. Introduction toNext Generation Sequencing Alex Sánchez Statistics and Bioinformatics Research Group Statistics department, Universitat de Barelona Statistics and Bioinformatics Unit Vall d’Hebron Institut de Recerca Introduction to NGS http://ueb.ir.vhebron.net/NGS
  • 2. OutlineIntroduction, Presentation, Goals.Next generation sequencing technologies. Evolution, Description, Comparison.Bioinformatics challenges.Some aspects of NGS data analysis. NGS data, and data preprocessing (QC) Types of analyses, workflows, toolsConclusions and perspectives Introduction to NGS http://ueb.ir.vhebron.net/NGS
  • 3. Who, where, what? Introduction to NGS http://ueb.ir.vhebron.net/NGS
  • 4. Introduction Introduction to NGS http://ueb.ir.vhebron.net/NGS
  • 5. Why is NGS revolutionary?• NGS has brought high speed not only to genome sequencing and personal medicine,• it has also changed the way we do genome research Got a question on genome organization? SEQUENCE IT !!! Ana Conesa, bioinformatics researcher at Principe Felipe Research Center Introduction to NGS http://ueb.ir.vhebron.net/NGS
  • 6. Sequencing: the Sanger Method (1977) Click here to see an animation Introduction to NGS http://ueb.ir.vhebron.net/NGS
  • 7. History of DNA sequencing is related to the combination of new technologies. Introduction to NGS http://ueb.ir.vhebron.net/NGS
  • 8. The human genome project Introduction to NGS http://ueb.ir.vhebron.net/NGS
  • 9. Next generation sequencing The future is here, now Introduction to NGS http://ueb.ir.vhebron.net/NGS
  • 10. Next generation Sequencing• Improvements in enzymes, chemistry and image analysis, mature by the middle of last decade dramatically increased sequencing capabilities.• The newest type of technology, called “next-generation sequencing“, appeared with the potential to dramatically accelerate biological and biomedical research – by enabling the comprehensive analysis of genomes, transcriptomes and interactomes, – by tending to become inexpensive, routine and widespread, rather than requiring very costly production-scale efforts. Introduction to NGS http://ueb.ir.vhebron.net/NGS
  • 11. NGS technologies Introduction to NGS http://ueb.ir.vhebron.net/NGS
  • 12. Next-generation DNA sequencingSanger sequencing Cyclic-array sequencing Introduction to NGS http://ueb.ir.vhebron.net/NGS
  • 13. Next-generation DNA sequencingSanger sequencing Next-generation sequencing Advantages of NGS - Construction of a sequencing library clonal amplification to generate sequencing features Introduction to NGS http://ueb.ir.vhebron.net/NGS
  • 14. Next-generation DNA sequencingSanger sequencing Next-generation sequencing Advantages: - Construction of a sequencing library clonal amplification to generate sequencing features No in vivo cloning, transformation, colony picking... Introduction to NGS http://ueb.ir.vhebron.net/NGS
  • 15. Next-generation DNA sequencingSanger sequencing Next-generation sequencing Advantages: - Construction of a sequencing library clonal amplification to generate sequencing features No in vivo cloning, transformation, colony picking... - Array-based sequencing Introduction to NGS http://ueb.ir.vhebron.net/NGS
  • 16. Next-generation DNA sequencingSanger sequencing Next-generation sequencing Advantages: - Construction of a sequencing library clonal amplification to generate sequencing features No in vivo cloning, transformation, colony picking... - Array-based sequencing Higher degree of parallelism than capillary-based sequencing Introduction to NGS http://ueb.ir.vhebron.net/NGS
  • 17. NGS means high sequencing capacity GS FLX 454 HiSeq 2000 5500xl SOLiD (ROCHE) (ILLUMINA) (ABI) GS Junior Ion TORRENT Introduction to NGS http://ueb.ir.vhebron.net/NGS
  • 18. NGS Platforms Performance 454 GS Junior 35MB Introduction to NGS http://ueb.ir.vhebron.net/NGS
  • 19. 454 Sequencing Introduction to NGS http://ueb.ir.vhebron.net/NGS
  • 20. ABI SOLID Sequencing Introduction to NGS http://ueb.ir.vhebron.net/NGS
  • 21. Solexa sequencing Introduction to NGS http://ueb.ir.vhebron.net/NGS
  • 22. Comparison of 2nd NGS Introduction to NGS http://ueb.ir.vhebron.net/NGS
  • 23. Some numbers Introduction to NGS http://ueb.ir.vhebron.net/NGS
  • 24. The sequencing process, in detail1 Library preparation 1 DNA fragmentation and in vitro adaptor ligation Introduction to NGS http://ueb.ir.vhebron.net/NGS
  • 25. Next-generation DNA sequencing1 Library preparation 1 DNA2 Clonal amplification fragmentation and in vitro adaptor ligation emulsion PCR2 Introduction to NGS http://ueb.ir.vhebron.net/NGS
  • 26. Next-generation DNA sequencing1 Library preparation 1 DNA2 Clonal amplification fragmentation and in vitro adaptor ligation emulsion PCR bridge PCR2 Introduction to NGS http://ueb.ir.vhebron.net/NGS
  • 27. Next-generation DNA sequencing1 Library preparation 1 DNA2 Clonal amplification fragmentation and in vitro3 Cyclic array sequencing adaptor ligation emulsion PCR bridge PCR23 Pyrosequencing 454 sequencingIntroduction to NGS http://ueb.ir.vhebron.net/NGS
  • 28. Next-generation DNA sequencing1 Library preparation 1 DNA2 Clonal amplification fragmentation and in vitro3 Cyclic array sequencing adaptor ligation emulsion PCR bridge PCR23 Pyrosequencing Sequencing-by-ligation 454 sequencingIntroduction to NGSplatform SOLiD http://ueb.ir.vhebron.net/NGS
  • 29. Next-generation DNA sequencing1 Library preparation 1 DNA2 Clonal amplification fragmentation and in vitro3 Cyclic array sequencing adaptor ligation emulsion PCR bridge PCR23 Pyrosequencing Sequencing-by-ligation Sequencing-by-synthesis 454 sequencingIntroduction to NGSplatform SOLiD Solexa technology http://ueb.ir.vhebron.net/NGS
  • 30. Next next generation sequencing• Pacific Biosystems – Real time DNA synthesis – Up to 12000nt (?) – 50 bases/second (?)• Promises delivery of human genome in minutes? – Company on track for 2013 Introduction to NGS http://ueb.ir.vhebron.net/NGS
  • 31. Bioinformatics challenges of NGS Introduction to NGS http://ueb.ir.vhebron.net/NGS
  • 32. I have my sequences/images. Now what? Introduction to NGS http://ueb.ir.vhebron.net/NGS
  • 33. NGS pushes (bio)informatics needs up• Need for large amount of CPU power – Informatics groups must manage compute clusters – Challenges in parallelizing existing software or redesign of algorithms to work in a parallel environment – Another level of software complexity and challenges to interoperability• VERY large text files (~10 million lines long) – Can’t do ‘business as usual’ with familiar tools such as Perl/Python. – Impossible memory usage and execution time – Impossible to browse for problems• Need sequence Quality filtering Introduction to NGS http://ueb.ir.vhebron.net/NGS
  • 34. Data management issues• Raw data are large. How long should be kept?• Processed data are manageable for most people – 20 million reads (50bp) ~1Gb• More of an issue for a facility: HiSeq recommends 32 CPU cores, each with 4GB RAM• Certain studies much more data intensive than other – Whole genome sequencing • A 30X coverage genome pair (tumor/normal) ~500 GB • 50 genome pairs ~ 25 TB Introduction to NGS http://ueb.ir.vhebron.net/NGS
  • 35. So what?• In NGS we have to process really big amounts of data, which is not trivial in computing terms.• Big NGS projects require supercomputing infrastructures• Or put another way: its not the case that anyone can do everything. – Small facilities must carefully choose their projects to be scaled with their computing capabilities. Introduction to NGS http://ueb.ir.vhebron.net/NGS
  • 36. Computational infrastructure for NGS• There is great variety but a good point to start with: – Computing cluster • Multiple nodes (servers) with multiple cores • High performance storage (TB, PB level) • Fast networks (10Gb ethernet, infiniband) – Enough space and conditions for the equipment ("servers room") – Skilled people (sysadmin, developers) • CNAG, in Barcelona: 36 people, more than 50% of them informaticians Introduction to NGS http://ueb.ir.vhebron.net/NGS
  • 37. Big computing infrastructure• Distributed memory cluster – Starting at 20 computing nodes – 160 to 240 cores – amd64 (x86_64) is the most used cpu architecture – At least 48GB ram per node• Fast networks – 10Gbit – Infiniband• Batch queue system (sge, condor, pbs, slurm)• Optional MPI and GPUs environment depending on project requirements. Introduction to NGS http://ueb.ir.vhebron.net/NGS
  • 38. Big infrastructure is expensive• Starting at 200.000€ – 200.000€ is just the hardware – Plus data center (computers room) – Plus informaticians salary• Not every partner knows about supercomputing. – SGI – Bull – IBMHP Introduction to NGS http://ueb.ir.vhebron.net/NGS
  • 39. Middle size infrastructure• "Small” distributed filesystem ( around 50TB).• "Small” cluster (around 10 nodes, 80 to 120 cores).• At least gigabit ethernet network.• Price range: 50.000 – 100.000 € (just hardware) – plus data center and informaticians salary Introduction to NGS http://ueb.ir.vhebron.net/NGS
  • 40. Small infrastructure• Recommended at least 2 machines – 8 or 12 cores each machine. – 48Gb ram minimum each machine. – BIG local disk. At least 4TB each machine • As much local disks as we can afford• Price range: starting at 8.000€ - 10.000€ (2 machines) Introduction to NGS http://ueb.ir.vhebron.net/NGS
  • 41. Alternatives (1): Cloud Computing• Pros – Flexibility. – You pay what you use. – Don´t need to maintain a data center.• Cons – Transfer big datasets over internet is slow. – You pay for consumed bandwidth. That is a problem with big datasets. – Lower performance, specially in disk read/write. – Privacy/security concerns. – More expensive for big and long term projects. Introduction to NGS http://ueb.ir.vhebron.net/NGS
  • 42. Alternatives (2): Grid Computing• Pros – Cheaper. – More resources available.• Cons – Heterogeneous environment. – Slow connectivity (specially in Spain). – Much time required to find good resources in the grid. Introduction to NGS http://ueb.ir.vhebron.net/NGS
  • 43. So what?• Think before you NGS• Decide what you … – want to do, – can afford – know how to do• Consider all alternatives• Look for expert advice … Introduction to NGS http://ueb.ir.vhebron.net/NGS
  • 44. NGS data analysis Introduction to NGS http://ueb.ir.vhebron.net/NGS
  • 45. NGS data analysis stages Introduction to NGS http://ueb.ir.vhebron.net/NGS
  • 46. Applications of Next-Generation Sequencing
  • 47. Metagenomics and other community-based “omics”Zoetendal E G et al.Gut 2008;57:1605-1615 Introduction to NGS http://ueb.ir.vhebron.net/NGS
  • 48. De novo sequencing Introduction to NGS http://ueb.ir.vhebron.net/NGS
  • 49. Transcriptomics by NGS: RNASeq• Analog Signal • Digital Signal• Easy to convey the signal’s • Harder to achieve & interpret information• Continuous strength • Reads counts: discrete values• Signal loss and distortion • Weak background or no noise Introduction to NGS http://ueb.ir.vhebron.net/NGS
  • 50. Which software for NGS (data) analysis?• Answer is not straightforward. http://seqanswers.com/wiki/Software/list• Many possible classifications – Biological domains • SNP discovery, Genomics, ChIP-Seq, De-novo assembly, … – Bioinformatics methods • Mapping, Assembly, Alignment, Seq-QC,… – Technology • Illumina, 454, ABI SOLID, Helicos, … – Operating system • Linux, Mac OS X, Windows, … – License type • GPLv3, GPL, Commercial, Free for academic use,… – Language • C++, Perl, Java, C, Phyton – Interface • Web Based, Integrated solutions, command line tools, pipelines,… Introduction to NGS http://ueb.ir.vhebron.net/NGS
  • 51. Combining tools in a typical workflow Introduction to NGS http://ueb.ir.vhebron.net/NGS
  • 52. Other popular tools Introduction to NGS http://ueb.ir.vhebron.net/NGS
  • 53. Quality control and preprocessing of NGS data Introduction to NGS http://ueb.ir.vhebron.net/NGS
  • 54. Data types Introduction to NGS http://ueb.ir.vhebron.net/NGS
  • 55. Why QC and preprocessing• Sequencer output: – Reads + quality• Natural questions – Is the quality of my sequenced data OK? – If something is wrong can I fix it?• Problem: HUGE files... How do they look?• Files are flat files and big... tens of Gbs (even hard to browse them) Introduction to NGS http://ueb.ir.vhebron.net/NGS
  • 56. Preprocessing sequences improves results Introduction to NGS http://ueb.ir.vhebron.net/NGS
  • 57. How is quality measured?• Sequencing systems use to assign quality scores to each peak• Phred scores provide log(10)-transformed error probability values: If p is probability that the base call is wrong the Phred score is Q = .10·log10p – score = 20 corresponds to a 1% error rate – score = 30 corresponds to a 0.1% error rate – score = 40 corresponds to a 0.01% error rate• The base calling (A, T, G or C) is performed based on Phred scores.• Ambiguous positions with Phred scores <= 20 are labeled with N. Introduction to NGS http://ueb.ir.vhebron.net/NGS
  • 58. Data formats• FastA format (everybody knows about it) – Header line starts with “>” followed by a sequence ID – Sequence (string of nt).• FastQ format (http://maq.sourceforge.net/fastq.shtml) – First is the sequence (like Fasta but starting with “@”) – Then “+” and sequence ID (optional) and in the following line are QVs encoded as single byte ASCII codes • Different quality encode variants• Nearly all downstream analysis take FastQ as input sequence Introduction to NGS http://ueb.ir.vhebron.net/NGS
  • 59. The fastq format• A FASTQ file normally uses four lines per sequence. – Line 1 begins with a @ character and is followed by a sequence identifier and an optional description (like a FASTA title line). – Line 2 is the raw sequence letters. – Line 3 begins with a + character and isoptionally followed by the same sequence identifier (and any description) again. – Line 4 encodes the quality values for the sequence in Line 2, and must contain the same number of symbols as letters in the sequence. • Different encodings are in use • Sanger format can encode a Phred quality score from 0 to 93 using ASCII 33 to 126@Seq descriptionGATTTGGGGTTCAAAGCAGTATCGATCAAATAGTAAATCCATTTGTTCAACTCACAGTTT+!*((((***+))%%%++)(%%%%).1***-+*))**55CCF>>>>>>CCCCCCC65 Introduction to NGS http://ueb.ir.vhebron.net/NGS
  • 60. Some tools to deal with QC• Use FastQC to see your starting state.• Use Fastx-toolkit to optimize different datasets and then visualize the result with FastQC to prove your success!• Hints: – Trimming, clipping and filtering may improve quality – But beware of removing too many sequences…Go to the tutorial and try the exercises... Introduction to NGS http://ueb.ir.vhebron.net/NGS
  • 61. AcknowledgementsGrupo de investigación en Estadística y Bioinformática deldepartamento de Estadística de la Universidad deBarcelona.Xavier de Pedro and Ferran Briansó (but also Jose LuisMosquera and Israel Ortega) de la Unitat d’Estadística iBioinformàtica del VHIR (Vall d’Hebron Institut deRecerca)Unitat de Serveis Científico Tècnics (UCTS) del VHIR(Vall d’Hebron Institut de Recerca)People whose materials have been borrowed Manel Comabella, Rosa Prieto, Paqui Gallego, Javier Santoyo, Ana Conesa, Pablo Escobar, Thomas Girke … Introduction to NGS http://ueb.ir.vhebron.net/NGS
  • 62. Gracias por la atención y la paciencia Introduction to NGS http://ueb.ir.vhebron.net/NGS

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