Visualization and analysis of large data collections: a case study applied to confocal microscopy data

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Visualization and analysis of large data
collections a case study applied to confocal
microscopy data

• Wim de Leeuw, Swammerdam Institute for Life
  Sciences, Amsterdam
• Pernette Verschure, Swammerdam Institute for Life
  Sciences, Amsterdam
• Robert van Liere, Center for Mathematics and
  Computer Science, Amsterdam

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Motivation (1)

• Context cell biology experiments
• Phenomenon captured using digital microscopy
• Experiment characteristics
• Biological diversity
• Not all biological parameters can be controlled
• Many measurements needed

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Motivation (2)

• Visualization and analysis of collections of data
  sets
• High variability
• Non-trivial information extraction (eg
  segmentation)
• Noise
• Visualization Modes Interactive vs Batch
• Interactive controlfeedback vs static settings
  of parameters
• Time consuming vs multiple data sets processed
  simultaneously
• Aim combine advantages of Interactive and Batch
  Visualization

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Agenda

• Biological Problem
• Chromatin structure and gene control
• Visualization Problem
• Data collection description
• Analysis with visual summaries

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Chromatin Structure and Gene Control

• Chromatin Structure
• Low level DNA, nucleosomes, 30 nm fiber
• High level fiber folding
• Gene control
• Regulation of gene activity
• Biological research question
• Relation chromatin structure and gene control
• Is there, what is, when, etc....

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Experiment

• Question influence of Hetrochromatin protein 1
  on chromatin structure?
• Approach
• Prepare collection of cells with a specific
  region
• Control group target GFP to the region
• HP1 group target GFP/HP1 to the region
• Observe regions with confocal microscope
• Data analysis question
• Identify and quantify the differences between
  control and HP1 group

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Collection of data sets

• 60 data sets (30 control group, 30 HP1 group)
• Each data set 512 x 512 x 32
• Sample images
• Control group (left)
• HP1 group (right)
• Data analysis questions
• Accurately detect region of interest
• Quantify region attributes (size, roughness,
  roundness, etc)
• What are the attribute differences in the control
  and HP1 groups ?

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Diversity of the collection
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Interactive Visualization of Collection

• Advantages
• Control over visualization tools and parameters
• Segmentation
• Attribute computations
• Direct feedback
• Disadvantages
• Laborious
• Error prone

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Batch processing of collection

• Advantage
• All sets are processed automatically
• A-priori parameter settings
• Disadvantage
• No feedback on the process

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Visual Summaries

• Definition a user defined compact visual
  representation of the data during (batch)
  processing
• Governing idea the visual summary is used to
  visualize the steps in batch process
• Examples
• General strategy
• Interactive setup (determine parameters,
  attributes, etc)
• Batch processing using setup
• Information visualization with visual summaries

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User Interface using Visual Summaries
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Discriminating groups

• Red HP1 sets, Green control
• Region granularity vs number of spots in region
• Granularity attribute
• Average intensity gradient of region
• Plot tells us
• Large variation, some outliers
• HP1 and control seem different

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Large variation, some outliers

• Brush / link outliers
• Investigate visual summary
• Problems with data set
• Corrupt data

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HP1 and control seem different

• Further analysis
• Histograms
• Box plots
• Statistical tests
• Wilcoxon
• Wilcoxon tells us that there is indeed a
  significant difference

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Lessons learned

• Showing a significant difference in granularity
  vs number of spots tells us that the HP1 effects
  the structure of chromatin. The effect is that
  chromatin is condensed in a number of compact
  regions.
• Biological significant result. Two papers
  published
• Strategy for analysis of collections of confocal
  data sets
• Interactive visualization and batch processing
  are both needed
• Information visualization is used for the
  analysis of batch output
• Visual summaries are used to link back to
  original data set or previous steps in batch
  process
• Strategy has been implemented as the Argos system

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Generality

• Argos has been used for the analysis of an
  experiment consisting of 2500 confocal data sets
• Argos has been used for the analysis of micro
  array data