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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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Pernette Verschure, Swammerdam Institute for Life Sciences, Amsterdam
Robert van Liere, Center for Mathematics and Computer Science, AmsterdamVisualization and analysis of large data collections: a case study applied to confocal microscopy data
Context: cell biology experiments
Phenomenon captured using digital microscopy
Not all biological parameters can be controlled
Many measurements needed
Visualization and analysis of collections of data sets
Non-trivial information extraction (eg segmentation)
Visualization Modes: Interactive vs Batch
Interactive control+feedback vs static settings of parameters
Time consuming vs multiple data sets processed simultaneously
Aim: combine advantages of Interactive and Batch Visualization
Chromatin structure and gene control
Data collection description
Analysis with visual summaries
Low level : DNA, nucleosomes, 30 nm fiber
High level: fiber folding
Regulation of gene activity
Biological research question:
Relation chromatin structure and gene control
Is there, what is, when, etc....
Question: influence of Hetrochromatin protein 1 on chromatin structure?
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
60 data sets (30 control group, 30 HP1 group)
Each data set: 512 x 512 x 32
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 ?
Control over visualization tools and parameters
All sets are processed automatically
A-priori parameter settings
No feedback on the process
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
Interactive setup (determine parameters, attributes, etc)
Batch processing using setup
Information visualization with visual summaries
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
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