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Enabling Phenotypic Image Analysis Using Shared Cyberinfrastructure Nathan Miller Spalding Lab UW-Madison January 23, 2012.

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Presentation on theme: "Enabling Phenotypic Image Analysis Using Shared Cyberinfrastructure Nathan Miller Spalding Lab UW-Madison January 23, 2012."— Presentation transcript:

1 Enabling Phenotypic Image Analysis Using Shared Cyberinfrastructure Nathan Miller Spalding Lab UW-Madison January 23, 2012

2 Small Scale Phenotypic Tool Kit Few phenotyping platforms available Large Scale Genetic Tool Kit High throughput genomic sequencing Reverse Genetic Populations Available Bioinformatics Structured Genetic Populations for Statistical Genomic Work Unbalanced Biological Tool Set Introduction to the phytoMorph Project

3 Small Scale Phenotypic Tool Kit Few phenotyping platforms available Large Scale Genetic Tool Kit High throughput genomic sequencing Reverse Genetic Populations Available Bioinformatics Structured Genetic Populations for Statistical Genomic Work Unbalanced Biological Tool Set Introduction to the phytoMorph Project Common Biological Problem: How Genotype maps to Phenotype

4 Small Scale Phenotypic Tool Kit Few phenotyping platforms available Large Scale Genetic Tool Kit High throughput genomic sequencing Reverse Genetic Populations Available Bioinformatics Structured Genetic Populations for Statistical Genomic Work Unbalanced Biological Tool Set Introduction to the phytoMorph Project Common Biological Problem: How Genotype maps to Phenotype Identify Bottleneck in Solving This Problem

5 Small Scale Phenotypic Tool Kit Few phenotyping platforms available Large Scale Genetic Tool Kit High throughput genomic sequencing Reverse Genetic Populations Available Bioinformatics Structured Genetic Populations for Statistical Genomic Work Unbalanced Biological Tool Set

6 Help Balance via Machine Vision Technologies Machine Vision: Extracting meaningful Information from images Infrared backlight Close-focus zoom lens with visible block/IR-pass filter CCD camera firewire- connected to an automated workflow Petri plate holder

7 In different rooms for different purposes we have approximately 30 of these CCD cameras equipped to image Arabidopsis or maize seedling development. Help Balance via Machine Vision Technologies 70K price for~30 camera sets ~200 movies of plants undergoing a dynamic growth process Only 4GB a day Camera and Data

8 In different rooms for different purposes we have approximately 20 of these CCD cameras equipped to image Arabidopsis or maize seedling development. Help Balance via Machine Vision Technologies High-Throughput Phenotyping of plant growth processes as they unfold. Changes the notion of a static phenotype to a watching a dynamic process unfold. As an example, brief focus on root gravitropism. What can we do with a set of camera banks?

9 What is Gravitropism

10 Why is Gravitropism Important? “Simple” Process of Bending Involves Intra and Intercellular communication Hormone Biology Cell Division and Expansion Water Relations Signal Transduction and Transmission Cell Specialization Control Systems

11 Data set of ~3000 seedling roots responding to gravitropic stimulus. Seedlings are 2,3, or 4 days old. Seedlings come from a variety of seed sizes.

12 Parent A Parent B Time course QTL: [Landsberg Erecta] x [Cape Verde]

13 UW-MadisonStatistical Genetics Applications Reverse Genetic Screens Doane CollegeGenetics of Plasticity Penn StatePlant Cellular and Molecular Biology University of TexasPlant Cellular and Molecular Biology University of FloridaMaize Biology Cold Spring Harbor Class Image Analysis and Phenotyping Phytomorph: Enabling Phenotypic Image Analysis Increase algorithms to include: Seed Size: Measure Arabidopsis Seed Size with flatbed scanner. Tip Tracing: Track a root and shoot apices for Rice, Arabidopsis, and Maize Kinematics: Measure spatiotemporal strain fields during growth. Others……..

14 UW-MadisonStatistical Genetics Applications Reverse Genetic Screens Doane CollegeStatistical Genetics of Plasticity Penn StateCellular and Molecular Biology University of TexasReverse Genetics University of FloridaPhenotypic Dependencies Come full Circle: Same problem but different type Phytomorph: Enabling Phenotypic Image Analysis

15 UW-MadisonStatistical Genetics Applications Reverse Genetic Screens Doane CollegeStatistical Genetics of Plasticity Penn StateCellular and Molecular Biology University of TexasReverse Genetics University of FloridaPhenotypic Dependencies Phytomorph: Enabling Phenotypic Image Analysis Come full Circle: Same problem but different type

16 UW-MadisonStatistical Genetics Applications Reverse Genetic Screens Doane CollegeStatistical Genetics of Plasticity Penn StateCellular and Molecular Biology University of TexasReverse Genetics University of FloridaPhenotypic Dependencies Phytomorph: Enabling Phenotypic Image Analysis &! Come full Circle: Same problem but different type

17 UW-MadisonStatistical Genetics Applications Reverse Genetic Screens Doane CollegeStatistical Genetics of Plasticity Penn StateCellular and Molecular Biology University of TexasReverse Genetics University of FloridaPhenotypic Dependencies Phytomorph: Enabling Phenotypic Image Analysis Using Shared Cyberinfrastructure &! Come full Circle: Same problem but different type

18 Shared Cyberinfrastructure Two of many tools which are being hosted/provided by iPlant 1)AtmoSphere: Cloud Computing 2)iRODS: Cloud Data Storage AtmoSphere Flexible tool for customizing machines for software deployment iPlant Common data repository for Image data

19 Shared Cyberinfrastructure University X Securely Transfer data via iDROP to data store Data can be continously syncronized via iDROP Data can be pushed on- demand iPlant Handles user authentication Large Data storage Receives data in Shared environment Allows iPlant users to transfer data between labs iRODS #1

20 Shared Cyberinfrastructure University X Login to AtmoSphere and Start phytoMorph Machine iPlant Boot-Up Virtual centOS Linux Handle Authentication #2

21 Shared Cyberinfrastructure University X Login to virtual Machine and analyze data iPlant Allow for custom software to be installed #3 First Set of phytoMorph Algorithms

22 Brief List of Some Current Users Won Gyu in Simon Gilroy’s Lab 500 GB of high resolution growth movies taken with Desiree den Os in Gabriele Monshausen’s Lab High Resolution movies of root growth Seed size analysis Used Graduate Level Class: Modern Techniques and Concepts in Plant Cell Biology here at Penn State Greg Clark and a team of students in Stan Roux’s Lab High Resolution movies of root growth Seed size analysis Morphometric Analysis The described way of working is not what we hope for but what is happening with a small set of beta groups. Take a minute to thank them for being VERY patient before iPlant’s infrastructure existed and while I learn how to use iPlant CI.

23 Brief List of Some Current Users Won Gyu in Simon Gilroy’s Lab 500 GB of high resolution growth movies. Desiree den Os in Gabriele Monshausen’s Lab High Resolution movies of root growth Seed size analysis Used Graduate Level Class: Modern Techniques and Concepts in Plant Cell Biology at Penn State Greg Clark and a team of students in Stan Roux’s Lab High Resolution movies of root growth Seed size analysis Morphometric Analysis

24 phytoBisque: Integration of Algorithms with Bisque

25 1)Continue to deploy image processing methods. iPlant CI is an essential tool to leverage. 2)Free up users to work independent. If a single lab can be successful via machine vision technologies, imagine what a community of Biologists can achieve. 3)Free up me to continue my work in modeling complex traits. Conclusions:

26 Staff: Greg Abram Sonali Aditya Roger Barthelson Brad Boyle Todd Bryan Gordon Burleigh John Cazes Mike Conway Karen Cranston Rion Doodey Andy Edmonds Dmitry Fedorov Michael Gatto Utkarsh Gaur Cornel Ghiban Michael Gonzales Hariolf Häfele Matthew Hanlon iPlant’s Building Blocks 74 MetadataDataToolsWorkflowsViz Executive Team: Steve Goff Dan Stanzione Faculty Advisors & Collaborators: Ali Akoglu Greg Andrews Kobus Barnard Sue Brown Thomas Brutnell Michael Donoghue Casey Dunn Brian Enquist Damian Gessler Ruth Grene John Hartman Matthew Hudson Dan Kliebenstein Jim Leebens-Mack David Lowenthal Robert Martienssen Students: Peter Bailey Jeremy Beaulieu Devi Bhattacharya Storme Briscoe Ya-Di Chen John Donoghue Steven Gregory Yekatarina Khartianova Monica Lent Amgad Madkour B.S. Manjunath Nirav Merchant David Neale Brian O’Meara Sudha Ram David Salt Mark Schildhauer Doug Soltis Pam Soltis Edgar Spalding Alexis Stamatakis Ann Stapleton Lincoln Stein Val Tannen Todd Vision Doreen Ware Steve Welch Mark Westneat Andrew Lenards Zhenyuan Lu Eric Lyons Naim Matasci Sheldon McKay Robert McLay Angel Mercer Dave Micklos Nathan Miller Steve Mock Martha Narro Praveen Nuthulapati Shannon Oliver Shiran Pasternak William Peil Titus Purdin J.A. Raygoza Garay Dennis Roberts Jerry Schneider Anthony Heath Barbara Heath Matthew Helmke Natalie Henriques Uwe Hilgert Nicole Hopkins Eun-Sook Jeong Logan Johnson Chris Jordan B.D. Kim Kathleen Kennedy Mohammed Khalfan Seung-jin Kim Lars Koersterk Sangeeta Kuchimanchi Kristian Kvilekval Aruna Lakshmanan Sue Lauter Tina Lee Bruce Schumaker Sriramu Singaram Edwin Skidmore Brandon Smith Mary Margaret Sprinkle Sriram Srinivasan Josh Stein Lisa Stillwell Kris Urie Peter Van Buren Hans Vasquez-Gross Matthew Vaughn Fusheng Wei Jason Williams John Wregglesworth Weijia Xu Jill Yarmchuk Aniruddha Marathe Kurt Michaels Dhanesh Prasad Andrew Predoehl Jose Salcedo Shalini Sasidharan Gregory Striemer Jason Vandeventer Kuan Yang Postdocs: Barbara Banbury Jamie Estill Bindu Joseph Christos Noutsos Brad Ruhfel Stephen A. Smith Chunlao Tang Lin Wang Liya Wang Norman Wickett

27 Settles LabMuday LabSpalding LabFerrier LabDurham Brooks Lab Funding Bisque Project


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