Download presentation
Presentation is loading. Please wait.
Published byCecil Higgins Modified over 9 years ago
1
The iPlant Collaborative Community Cyberinfrastructure for Life Science Roger Barthelson/Uwe Hilgert iPlant / University of Arizona
2
The iPlant Collaborative Vision www.iPlantCollaborative.org Enable life science researchers and educators to use and extend cyberinfrastructure
3
Community-driven organization builds cyberinfrastructure for biological sciences The iPlant Collaborative Vision
4
UA TACC CSHL iPlant Collaborative A virtual organization
5
Biological Cyberinfrastructure Big Data in Biology
6
Human Genome: $2.7 Billion, 13 Years Human Genome: $900, 6 Hours 2014 Oxford Nanopore MiniION 2003: ABI 3730 Sequencer The Egalitarian Genome Next Generation Sequencing 2014
7
“BGI, based in China, is the world’s largest genomics research institute, with 167 DNA sequencers producing the equivalent of 2,000 human genomes a day. BGI churns out so much data that it often cannot transmit its results to clients or collaborators over the Internet or other communications lines because that would take weeks. Instead, it sends computer disks containing the data, via FedEx.” The Big Data Problem Storage and Analysis
8
Biological Cyberinfrastructure The Problem of Big Data in Biology
9
Biology’s Other Big Data Phenomics Visualization
10
How iPlant CI Enables Discovery Challenge: Create an easy-to-use platform powerful enough to handle data-intensive biology Many bioinformatics tools “off limits” to those without specialized computational backgrounds (“command line”). Data Store Discovery Environment – 100s of tools/apps Atmosphere – Cloud Computing Bisque – Image Analysis Environment APIs
11
iPlant APIs Resources The Biology App Store
12
The iPlant Collaborative What is cyberinfrastructure? Manage Data Share Data Analyze Data Scalable, accessible computation: data storage, cloud services, and software tools Utilize Big Data Tech Facilitate Collaborations Connect Resources Manage Access Enable science (verifiable, reproducible, tractable)
13
The iPlant Collaborative What iPlant offers Data Management & Storage Resources Access to High Performance Computing Resources Tool Integration System Application Programming Interfaces (APIs) Cloud Computing Genotype To Phenotype Science Enablement Tree of Life Science Enablement Image Analysis Platform Support for Molecular Breeding Platform (IBP) Support for AgMIP Others to come...
14
The iPlant Collaborative What iPlant offers
15
The iPlant Collaborative What iPlant offers
16
The iPlant Collaborative What iPlant offers
17
How iPlant CI Enables Discovery Challenge: Navigate biology’s “data deluge” HT Image data – GB’s per day HT sequence data – TB’s per run
18
iPlant Data Store Texas Replication Arizona Grid Computing Cloud Computing HPC Community Super Computing iDrop WebDAV FoundationAPI DE i-commands iPlant Data Store Scalable Reliable Redundant High-Performance Connected iPlant Data Store Scalable Reliable Redundant High-Performance Connected
19
How iPlant CI Enables Discovery Solution: iPlant Data Store All data in within the same platform speed and accessibility Access your data from multiple iPlant services Automatic data backup redundant between University of Arizona and University of Texas Multiple ways to share data with collaborators Multi-threaded high speed transfers Default 100 GB allocation. >1 TB allocations available with justification SourceTime (s) CD320 Berkeley Server150 External Drive36* USB2.0 Flash30 iPlant Data Store 18* My Computer15 Getting 1 GB onto my computer takes...
20
How iPlant CI Enables Discovery What iPlant data solutions mean for a bovine breeder “It's kind of like being in that COPD commercial where the weight is lifted off your chest, only with iPlant, we have access to more computational power, so we can get to projects much faster and we can do big projects that our machines may not have allowed us to do previously! The ability to transport 2TB of data overnight using the iRODS system was particularly helpful because previously, we had been mailing hard drives which is not an optimal solution to sharing big data.” James Koltes, Iowa State
21
How iPlant CI Enables Discovery Solution: Discovery Environment An extensible platform for science High-powered computing Data sharing/collaboration Easy to use interface Virtually limitless apps Analysis history (provenance)
22
iPlant’s Discovery Environment Web Interface for Hundreds of Applications
23
(Some) Apps in Discovery Environment Sequence Quality Control – FastQC – Fastx Toolkit – Sabre, Scythe, Sickle (paired end trimming) – SGA cleanup (paired end quality trimming) – Coming soon… Sequence induction, assessment, and trimming pipeline Mira contaminant detection and removal (for sequencing studies)
24
(Some) Apps in Discovery Environment Genome Assembly – ABySS – Soapdenovo2 – Velvet – Newbler – Contig analysis tools With or without reference sequence for comparison – Coming soon… Minimus2 Mira PacBioToCA Or PBJelly? (for sequencing studies)
25
(Some) Apps in Discovery Environment Transcript assembly/RNASeq – Tophat, Cufflinks, Cuffmerge, CuffDiff – Oases – Trinity – Newbler – Scarf – Coming soon… Open pipeline for transcript expression analysis (quantitative RNASeq) Mira transcriptome assembly (for sequencing studies)
26
The iPlant Collaborative What iPlant offers
27
The iPlant Collaborative What iPlant offers
28
How iPlant CI Enables Discovery What the Discovery Environment means to bench biologists “In one week I was able to align my RNA-Seq samples using a method that previously took me a month on my bioinformatics computers… Being able to access my data any time and from anywhere – price less. The DE interface is intuitive and easy to use...[and] will allow greater continuity and comparability between different experiments from different laboratories.” Richard Barker – Univ. Wisconsin, Madison
29
How iPlant CI Enables Discovery Challenge: Collaborate and access software on demand Frustrated bioinformaticians serving the needs of several users + works well / powerful - expensive / complex Cartoon: http://phdhumor.blogspot.com/2008/12/on-lazy-day-for-bioinformatician.html
30
How iPlant CI Enables Discovery iPlant Solution: Atmosphere On-demand computing resource built on a cloud infrastructure Virtual Machine pre-configured with: Software Memory requirements Processing power Plant authentication and storage and HPC capabilities Build custom images/appliances and share with community Cross-platform desktop access to GUI applications in the cloud (using VNC)
31
Atmosphere: Your Cloud, Your Way Google Cloud Atmosphere
32
Atmosphere Select a Machine Image, Launch
33
How iPlant CI Enables Discovery What Atmosphere means to bioinformaticians “What my users used to call me for, they now do on their own through Atmosphere. Now I can scale up my user community” Nathan Miller, Univ. Wisconsin, Madison BLAST 400k transcripts against NCBI nr in 36 h vs. 2 months Use iPlant Data Store to move 1500 high-res images per day for analysis “iPlant is a great equalizer.” Mike Covington, UC Davis
34
The iPlant Collaborative Your colleagues Staff: Greg Abram Sonali Aditya Ritu Arora Roger Barthelson Rob Bovill Brad Boyle Gordon Burleigh John Cazes Mike Conway Victor Cordero Rion Dooley Aaron Dubrow Andy Edmonds Dmitry Fedorov John Fonner Melyssa Fratkin Michael Gatto Leadership Team Steve Goff - UA Dan Stanzione – TACC Matt Vaughn - TACC Nirav Merchant – UA Eric Lyons - UA Doreen Ware – CSHL Faculty Advisors & Collaborators: Ali Akoglu Kobus Barnard Volker Brendel Timothy Clausner Sally Elgin Brian Enquist Damian Gessler Ruth Grene John Hartman Matthew Hudson David Lowenthal B.S. Manjunath David Neale Students: Peter Bailey Jeremy Beaulieu Devi Bhattacharya Storme Briscoe YaDi Chen David Choi Barbara Dobrin Brian O’Meara Sudha Ram David Salt Mark Schildhauer Neelima Sinha Doug Soltis Pam Soltis Edgar Spalding Alexis Stamatakis Rick Stevens James Taylor Brett Tyler Steve Welch Zhenyuan Lu Eric Lyons Aaron MarcuseKubitz Naim Matasci Robert McLay Nathan Miller Steve Mock Martha Narro Shannon Oliver Benoit Parmentier Jmatt Peterson Dennis Roberts Paul Sarando Jerry Schneider Edwin Skidmore Brandon Smith Utkarsh Gaur Cornel Ghiban Steve Gregory Mathew Helmke Natalie Henriques Uwe Hilgert Nicole Hopkins Logan Johnson Chris Jordan Kathleen Kennedy Mohammed Khalfan David Knapp Lars Koersterk Sangeeta Kuchimanchi Kristian Kvilekval Sue Lauter Tina Lee Mary Margaret Sprinkle Sriram Srinivasan Josh Stein Lisa Stillwell Jonathan Strootman Peter Van Buren Hans VasquezGross Rebeka Villarreal Ramona Wallls Liya Wang Anton Westveld Jason Williams John Wregglesworth Weijia Xu Andrew Predoehl Sathee Ravindranath Kyle Simek Gregory Striemer Jason Vandeventer Nicholas Woodward Kuan Yang Postdocs: Barbara Banbury Christos Noutsos Solon Pissis Brad Ruhfel John Donoghue Yekatarina Khartianova Chris La Rose Amgad Madkour Aniruddha Marathe Andre Mercer Kurt Michaels Zack Pierce Michael Schatz – CSHL David Micklos – CSHL Ann Stapleton – UNCW Ron Vetter – UNCW
35
Connect with iPlant! Twitter: @iPlantCollab #iPlant Facebook: facebook.com/iPlantCollab LinkedIn: iplant.co/iPlantCollabLinkedIn Google+: iplant.com/iPlantGooglePlus
Similar presentations
© 2025 SlidePlayer.com. Inc.
All rights reserved.