1. Canadian Bioinformatics Workshops www.bioinformatics.ca

2. Cold Spring Harbor Laboratory & New York Genome Center In collaboration with

3. 3Module #: Title of Module

4. Module 1 bioinformatics.ca

5. Module 1 bioinformatics.ca You are free to: Copy, share, adapt, or re-mix; Photograph, film, or broadcast; Blog, live-blog, or post video of; This presentation. Provided that: You attribute the work to its author and respect the rights and licenses associated with its components. Slide Concept by Cameron Neylon, who has waived all copyright and related or neighbouring rights. This slide only ccZero.ccZero Social Media Icons adapted with permission from originals by Christopher Ross. Original images are available under GPL at; http://www.thisismyurl.com/free-downloads/15-free-speech-bubble-icons-for-popular-websites

6. Module 1 bioinformatics.ca @bffo francis@oicr.on.ca E-mail #CBW15

7. Module 1 bioinformatics.ca I do not (and will not) profit in any way, shape or form, from any of the brands, products or companies I may mention. Disclaimer

8. Module 1.1 Overview of Workshop

9. Module 1 bioinformatics.ca Bioinformatics History of bioinformatics.ca Cloud computing Getting on Amazon Web Services Outline

10. Module 1 bioinformatics.ca What biologist do: Make observations Make hypothesis Test them Challenge them Conclude things Write papers http://goo.gl/7sCUI

11. Module 1 bioinformatics.ca RNA-Seq Protein MS http://goo.gl/Lye8R

12. Module 1 bioinformatics.ca Interaction and Pathway Space

13. Module 1 bioinformatics.ca Central Dogma RNA protein DNA

14. Module 1 bioinformatics.ca Central Dogma RNA protein DNA Then you write a paper about it

15. Some of the things we do when we try and understand the cell … We do experiments Some of these are bioinformatics experiments We all want these to be reproducible We want people to find our data We want people to find our methods … and we want them to be able to rerun our experiments, validate our work, move the science forward.

16. Module 2 bioinformatics.ca Bioinformatics experiments: 16 BLAST searchSequence Alignment Reagents: Sequence Databases Method: P-PBLASTP N-PBLASTX P-NTBLASTN N-NBLASTN N (P) – N (P)TBLASTX Interpretation: Similarity Hypothesis testing Know your reagents Know your methods Do your controls

17. Module 1 bioinformatics.ca Think – Pair – Share! What is Bioinformatics? 17Introduction 1.0

18. Module 1 bioinformatics.ca Bioinformatics is about integrating biological themes together with the help of computer tools and biological databases, and gaining new knowledge about the system in study.

19. Module 1 bioinformatics.ca 1998

20. Module 1 bioinformatics.ca 1999 –2007 Bioinformatics Developing the Tools Genomics Proteomics

21. Module 1 bioinformatics.ca 2008– present

22. Module 1 bioinformatics.ca Analysis of Metagenomic Data - 3 Bioinformatics of Cancer Genomics - 5 Exploratory Analysis of Biological Data using R - 2 High-throughput Biology: From Sequence to Networks - 7 Informatics and Statistics for Metabolomics - 2 Informatics for RNA-seq Analysis- 2 Informatics on High-Throughput Sequencing Data– 2 Introduction to R – 1 Microarray Expression Analysis - 2 Pathway and Network Analysis of -omic Data – 3

23. Module 1 bioinformatics.ca

24. http://bioinformatics.ca/workshops/2014

25. E-mail: course_info@bioinformatics.ca Web: http://bioinformatics.ca Workshop announcement mailing list: http://bioinformatics.ca/mailman/listinfo/announce

26. Soap-Box time! Open Access, Open Data and Open Source are essential for Science. Openness is a responsibility, an obligation, and something that comes with the privilege of doing publicly funded work. Open Access Open Source Open Data Opencourseware

27. Module 1 bioinformatics.ca If databases get it wrong, the onus is on on the user to let the databases know that it is wrong! http://goo.gl/bGjMH

28. Module 1 bioinformatics.ca If databases get it wrong, the onus is on on the user to let the databases know that it is wrong! any db ……………………………………………..….. http://goo.gl/bGjMH

29. Module 1 bioinformatics.ca Q: Why do we have Bioinformatics? A: Open Data from Genomic and Proteomics Technologies

30. Module 1.2 Overview of Cloud Computing

31. Cloud computing … and new software paradigm Data sets are reaching the Petabyte scale. Data (and the security rules that come with it) will be somewhere, and you will move your software to it. Software development paradigm will change: no more reading of files into RAM, processing, and then writing output: you need to think about processing streaming data coming from a sequencing machine somewhere on the net.

32. Module 1 bioinformatics.ca 19901992 1994 199619982000200320042006200820102012 0 1 10 100 1,000 10,000 100,000 1,000,000 1 10 100 1,000 10,000 100,000 1,000,000 10,000,000 100,000,000 1,000,000,000 Disk Capacity vs Sequencing Capacity, 1990-2009 Disk Storage (Mbytes/$) DNA Sequencing (bp/$) Hard disk storage (MB/$) Doubling time=14 mo Hard disk storage (MB/$) Doubling time=14 mo Pre-nextgen sequencing (bp/$) Doubling time=19 mo Pre-nextgen sequencing (bp/$) Doubling time=19 mo Nextgen sequencing (bp/$) Doubling time=4 mo0 Nextgen sequencing (bp/$) Doubling time=4 mo0

33. Module 1 bioinformatics.ca We now have ~ $1000 genome, but now need to think more about the cost of the analysis. The doubling time of the reduction of sequencing in cost is in the “many months” range. The doubling time of storage and network bandwidth is “very small number of years” range. The doubling time of CPU speed is 18 months. The cost of sequencing a base pair will equal the cost of storing a base pair by in the next “very small number” of years. About DNA and computers

34. Module 1 bioinformatics.ca Too much data and not enough computer infrastructure in most labs –Where do they go? –Write more grants? –Get more hardware? –Look to the sky? What is the general biomedical scientists to do?

35. Module 1 bioinformatics.ca Typical sequencing company pipeline: Genomic companies already there! ACGTACGTAA GTTCGGATGG CGTAGTCCCT TTTTGGGGTG TAGTGAGGC GCTGATTCGG AGAG All of the hard work done here! All of the hard work done here!

36. Module 1 bioinformatics.ca Google docs Dropbox Netflix Twitter Most people already there!

37. Module 1 bioinformatics.ca Amazon Web Services (AWS) Infinite storage (scalable): S3 (simple storage service) Compute per hour: EC2 (elastic cloud computing) Ready when you are High Performance Computing Multiple football fields of HPC throughout the world HPC are expanded at one contained at a time: http://goo.gl/7PVAl

38. Module 1 bioinformatics.ca Not cheap! Getting files to and from there Not the best solution for everybody Standardization PHI: personal health information & security concerns In the USA: Patriot act Some of the challenges with cloud computing:

39. Module 1 bioinformatics.ca At the CBW: we received a grant from Amazon, so supported by ‘AWS in Education grant award. There are better ways of transferring large files, and now AWS makes it free to upload files. A number of datasets exist on AWS (e.g. 1000 genome data). Many useful bioinformatics AMI’s (Amazon Machine Images) exist on AWS: e.g. cloudbiolinux & CloudMan (Galaxy) Many flavors of cloud available, not just AWS Some of the advantages with cloud computing:

40. Module 1 bioinformatics.ca Some tools (data) are on your computer on the web on the cloud. You will become efficient at traversing these various spaces, and finding resources you need, and using what is best for you. There are different ways of using the cloud: 1.Command line (like your own very powerful Unix box) 2.With a web-browser (e.g. Galaxy): not in this workshop In this workshop:

41. Module 1 bioinformatics.ca This is what a 5MB hard drive looked like in 1956! What will it be in 2056? “Big Data” is a relative term! http://goo.gl/f1PkV

42. MinION from Oxford Nanopore http://www.nanoporetech.com/technology/minion-a-miniaturised-sensing-instrument

43. Module 1 bioinformatics.ca Loaded data files to an AWS We brought up an Ubuntu (Linux) instance, and loaded a whole bunch of software for NGS analysis. We then cloned this, and made separate instances for everybody in the class. We’ve simplified the security: you basically all have the same login and and file access, and opened ports. In your own world you would be more secure. Things we have set up:

44. Module 1 bioinformatics.ca For this workshop: all on Wiki! http://bioinformatics.ca/workshop_wiki/ Login: FirstnameLastname Password: guest

45. Module 1 bioinformatics.ca

46. Module 1 bioinformatics.ca

47. Module 1 bioinformatics.ca

48. Module 1 bioinformatics.ca CBWNY.pem On Mac: Control+

49. Module 1 bioinformatics.ca CBWNY.pem

50. Module 1 bioinformatics.ca ls -l (long listing) drwx------+ 67 francis staff 2278 22 May 21:25../ -rw-r--r--@ 1 francis staff 1696 22 May 21:31 CBWNY.pem rwx : owner rwx : group rwx: world r read (4) w write (2) x execute (1) Which ever way you add these 3 numbers, you know which integers were used (6 is always 4+2, 5 is 4+1, 4 is by itself, 0 is none of them etc …) So, when you have: chmod 600 It is “rw” for the the file owner only

51. Module 1 bioinformatics.ca Logging in to AWS

52. Module 1 bioinformatics.ca Windows

53. Module 1 bioinformatics.ca 1

54. Module 1 bioinformatics.ca 2 3

55. Module 1 bioinformatics.ca 4 5

56. Module 1 bioinformatics.ca

57. Module 1 bioinformatics.ca Your laptop is ready for the workshop If it is not, you know where to get the information you need You know how to use the wiki for this workshop You know where all of the lectures are You have read all of the pre-lecture material If not, you know where the papers are, and you are a speed reader You know how to login to AWS So, at this point:

58. Module 1 bioinformatics.ca We are on a Coffee Break & Networking Session