www.iplantcollaborative.org enabling cloud and grid powered image phenotyping martha narro iplant...

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Enabling Cloud and Grid PoweredImage Phenotyping

Martha NarroiPlant Collaborative

narro@iplantcollaborative.arizona.eduAdapted from slides by Nirav Merchant

www.iplantcollaborative.org

Motivation

• High throughput imaging is essential for large-scale phenotyping.• Affordable robotics for image

acquisition creating vast amounts of imaging data.

• Many laboratories have automated imaging setups, but lack a comparable analysis platform.

• Super resolution microscopy and multi-channel images are pushing the boundaries of storage and computational capabilities.

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Motivation II• New, improved analysis

algorithms are being published.• Biologists struggle to use

them.• Developers need images to

test algorithms.• Scientists need to compare

algorithms, reproduce results.

• Metadata is key for managing large datasets.• Sharing and collaborating with large image data

sets is challenging.• ONE SIZE FITS ALL APPROACH DOES NOT WORK

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BisqueImage Management, Analysis, Sharing System

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Why Bisque?• Biologists can

• Manage images• Choose from multiple analysis options • Overlay results to validate findings• Annotate images• Share images, results, annotations via secure link • Algorithm developers can

• Publish new analysis methods, easily make them web accessible

• Produce interactive plots, visualizations using built in API• Integrated with iPlant storage and computation

infrastructure for scalability

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How does it work?

Bisque

iPlant Data Store

High B

andw

idth

Trans

fer

iPlant Computational Infrastructure

High Bandwidth

Transfer

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Bisque Features

• Web application• Tiling, zooming, step through image stacks, play as

movie• Display 20K x 20K pixel images in web browser• Handles 100+ image, video formats• Import large image sets (≤ 40 GB Bisque), extremely

large ones (> 40 GB iPlant Data Store)• Scale analyses using distributed computing

(connected to XSEDE) and workflow engines (Pegasus, Condor)

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Pollen Tube Tracker Analysis

Stack of time-lapse images of pollen tubes growing in vitro displaying maximum intensity in each image Tracking by Bisque

Source: Ravi Palanivelu, Kobus Barnard

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MultiRoot Growth Analysis

Time lapse image stack of seeds growing Root tip tracking by Bisque

Source: Edgar Spalding

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Seed Size Analysis

High resolution flat bed scanner image of seeds

Edge detection and analysis by Bisque

Source: Edgar Spalding

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Automated Pollen Identification

Imagine some pollen grains

Source: Matina Donaldson-Matasci, et al.

Imagine the species of the pollen grains has been identified

Coming Attraction!

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Users

Currently iPlant has 5+ groups actively using this infrastructure•3 Graduate courses•2 Summer courses/workshops•NSF ADBC Thematic Collections Network(Yale University led)

www.iplantcollaborative.org

Users

Currently iPlant has 5+ groups actively using this infrastructure•3 Graduate courses•2 Summer courses/workshops•NSF ADBC Thematic Collections Network(Yale University led) •Welcome, 1 Pollen RCN

www.iplantcollaborative.org

Bisque-iPlant Team

• Bisque (U. California, Santa Barbara)• B. S. Manjunath• Kris Kvelikval• Dmitry Fedorov

• Phytomorph (U. Wisconsin, Madison)• Edgar Spalding• Nathan Miller• Logan Johnson

• Nirav Merchant (iPlant; U. Arizona, Tucson)

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• Main application:• bisque.iplantc.org

• Support:• http://ask.iplantcollaborative.org

• Project Website• http://www.iplantcollaborative.org

Useful Links