Enabling Cloud and Grid Powered Image Phenotyping Nirav Merchant iPlant Collaborative

Topic Coverage Motivation Key Components Overview of BISQUE Roadmap and future direction

Motivation High throughput imaging is essential for enabling genome scale phenotyping efforts Affordable automation for image acquisition (e.g. robotic high throughput systems) is creating vast amounts of imaging data (rapidly) Many laboratories have custom or commercial setup for high throughput image acquisition (but lack the comparable analysis platform) Super resolution microscopy and multi-channel images are pushing the boundaries of storage and computational capabilities

Image acquisition Robotic image acquisition of root tips (Spalding Lab.)

Image Acquisition Multiple setups recording movies for root growth (Spalding Lab.)

Motivation II New improved algorithms and analysis routines are being constantly published Applying these algorithms to existing data is challenging for biologists Sharing and collaborating with large image data sets is challenging There is no common platform to try multiple methods/algorithms on collection of images Data management is challenging for high throughput methods (metadata is key) Establishing consistent protocol for image analysis is challenging when using multiple applications/platforms ONE SIZE FITS ALL APPROACH DOES NOT WORK

Key iPlant infrastructure iPlant Data Store (iDS) Computational Grid (HPC, HTC) Atmosphere (Cloud Infrastructure)* BISQUE*

iPlant Data Store Connecting people with data and computation: Lifecycle of Data  Transfer  Storage  Analysis  Visualization  Metadata Mark-up  Search and Discover  Share/Collaborate  Publish  Transfer  Storage  Analysis  Visualization  Metadata Mark-up  Search and Discover  Share/Collaborate  Publish

Why cloud ? Standalone interactive GUI-based applications are frequently required for analysis GUI apps not easily to transform into web apps (or run on grid/command line etc.) Need to handle complex software dependencies (e.g specific version on software/library) Users needing full control of their software stack (occasional sudo/super users access) Need to share desktop/applications for collaborative analysis (remote collaborators)

So how does it work ? Configured VM (all required s/w) iPlant Data store High Bandwidth Transfer

How does it look ?

Why Bisque Allows algorithms developers to publish new analysis methods and make it completely web accessible with ease Biologists can choose from multiple analysis options for their images, overlay results to validate findings without altering original image content Produce interactive plots, visualization using built in API Share results, images, annotations with collaborators via secure link. Integrated with iPlant storage and computation infrastructure

Bisque features Rich internet application (completely web based) Draws upon features from popular large scale photo sharing sites and high resolution aerial imagery (google maps) Ability to import and export over 100+ image formats, movies Ability to import extremely large image sets using iPlant storage infrastructure Can display 20Kx20K image using standard web browser Utilizes distributed computing (connected to XSEDE) and workflow engines (Pegasus, Condor) to scale analysis

Whole seedling-size analysis High resolution flat bed scanner image of seeds Edge detection and analysis by PhytoBisque Source: Edgar Spalding

Simple Steps for Using it Concept of Mini-Apps Browse and select image (or video) Run analysis Overlay results and verify Export data

PhytoBisque interface Searching, browsing

PhytoBisque Interface Viewing large (18Kx17k pixel image) and performing analysis on selected section

Participants Bisque (Univ. of California, Santa Barbara) – B. S. Manjunath – Kris Kvelikval – Dmitry Fedorov Phytomorph (Univ. of Wisconsin, Madison) – Edgar Spalding – Nathan Miller – Logan Johnson

Users Currently we have 5+ groups actively using this infrastructure 3 Graduate course 2 Summer courses/workshops 1 Pollen Network RCN NSF ADBC Thematic Collections Network (Yale University led)

Main application: – Support: – Project Website –