An Interactive Analysis and Exploration Tool for Epigenomic Data

In this design study, we present an analysis and ion of the data and tasks related to the domain of epigenomics, and the design and implementation of an interactive tool to facilitate data analysis and visualization in this domain. Epigenomic data can be grouped into subsets either by k‐means cluste...

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Veröffentlicht in:Computer graphics forum Jg. 32; H. 3pt1; S. 91 - 100
Hauptverfasser: Younesy, H., Nielsen, C.B., Möller, T., Alder, O., Cullum, R., Lorincz, M.C., Karimi, M.M., Jones, S.J.M.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Oxford, UK Blackwell Publishing Ltd 01.06.2013
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ISSN:0167-7055, 1467-8659
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Abstract In this design study, we present an analysis and ion of the data and tasks related to the domain of epigenomics, and the design and implementation of an interactive tool to facilitate data analysis and visualization in this domain. Epigenomic data can be grouped into subsets either by k‐means clustering or by querying for combinations of presence or absence of signal (on/off) in different epigenomic experiments. These steps can easily be interleaved and the comparison of different workflows is explicitly supported. We took special care to contain the exponential expansion of possible on/off combinations by creating a novel querying interface. An interactive heat map facilitates the exploration and comparison of different clusters. We validated our iterative design by working closely with two groups of biologists on different biological problems. Both groups quickly found new insight into their data as well as claimed that our tool would save them several hours or days of work over using existing tools.
AbstractList In this design study, we present an analysis and abstraction of the data and tasks related to the domain of epigenomics, and the design and implementation of an interactive tool to facilitate data analysis and visualization in this domain. Epigenomic data can be grouped into subsets either by k-means clustering or by querying for combinations of presence or absence of signal (on/off) in different epigenomic experiments. These steps can easily be interleaved and the comparison of different workflows is explicitly supported. We took special care to contain the exponential expansion of possible on/off combinations by creating a novel querying interface. An interactive heat map facilitates the exploration and comparison of different clusters. We validated our iterative design by working closely with two groups of biologists on different biological problems. Both groups quickly found new insight into their data as well as claimed that our tool would save them several hours or days of work over using existing tools [PUBLICATION ABSTRACT].
In this design study, we present an analysis and abstraction of the data and tasks related to the domain of epigenomics, and the design and implementation of an interactive tool to facilitate data analysis and visualization in this domain. Epigenomic data can be grouped into subsets either by k-means clustering or by querying for combinations of presence or absence of signal (on/off) in different epigenomic experiments. These steps can easily be interleaved and the comparison of different workflows is explicitly supported. We took special care to contain the exponential expansion of possible on/off combinations by creating a novel querying interface. An interactive heat map facilitates the exploration and comparison of different clusters. We validated our iterative design by working closely with two groups of biologists on different biological problems. Both groups quickly found new insight into their data as well as claimed that our tool would save them several hours or days of work over using existing tools.
In this design study, we present an analysis and ion of the data and tasks related to the domain of epigenomics, and the design and implementation of an interactive tool to facilitate data analysis and visualization in this domain. Epigenomic data can be grouped into subsets either by k‐means clustering or by querying for combinations of presence or absence of signal (on/off) in different epigenomic experiments. These steps can easily be interleaved and the comparison of different workflows is explicitly supported. We took special care to contain the exponential expansion of possible on/off combinations by creating a novel querying interface. An interactive heat map facilitates the exploration and comparison of different clusters. We validated our iterative design by working closely with two groups of biologists on different biological problems. Both groups quickly found new insight into their data as well as claimed that our tool would save them several hours or days of work over using existing tools.
Author Cullum, R.
Jones, S.J.M.
Younesy, H.
Lorincz, M.C.
Möller, T.
Alder, O.
Karimi, M.M.
Nielsen, C.B.
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  organization: School of Computing Science, Simon Fraser University
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  givenname: C.B.
  surname: Nielsen
  fullname: Nielsen, C.B.
  organization: Canada's Michael Smith Genome Sciences Centre, British Columbia Cancer Agency
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  surname: Möller
  fullname: Möller, T.
  organization: School of Computing Science, Simon Fraser University
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  givenname: O.
  surname: Alder
  fullname: Alder, O.
  organization: Terry Fox Laboratory, British Columbia Cancer Agency
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  surname: Cullum
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  organization: Terry Fox Laboratory, British Columbia Cancer Agency
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  surname: Lorincz
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  organization: Department of Medical Genetics, Life Sciences Institute, The University of British Columbia
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  surname: Karimi
  fullname: Karimi, M.M.
  organization: Department of Medical Genetics, Life Sciences Institute, The University of British Columbia
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  surname: Jones
  fullname: Jones, S.J.M.
  organization: Canada's Michael Smith Genome Sciences Centre, British Columbia Cancer Agency
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References_xml – reference: Hoffman M. , Buske O. , Wang J. , Weng Z. , Bilmes J. , Noble W. : Unsupervised pattern discovery in human chromatin structure through genomic segmentation . Nature Methods 9 , 5 ( 2012 ), 473 - 476 . 3 .
– reference: Heintzman N. , Stuart R. , Hon G. , Fu Y. , Ching C. , Hawkins R. , et al. : Distinct and predictive chromatin signatures of transcriptional promoters and enhancers in the human genome . Nature genetics 39 , 3 ( 2007 ), 311 - 318 . 3, 7 .
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– reference: Goecks J. , Nekrutenko A. , Taylor J. , The Galaxy Team : Galaxy: a comprehensive approach for supporting accessible, reproducible, and transparent computational research in the life sciences . Genome Bio. 11 , 8 ( 2010 ), R86 . 3, 7 .
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– volume: 11
  start-page: R86
  issue: 8
  year: 2010
  article-title: Galaxy: a comprehensive approach for supporting accessible, reproducible, and transparent computational research in the life sciences
  publication-title: Genome Bio.
– start-page: 243
  year: 2008
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– volume: 40
  start-page: D912
  issue: D1
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  end-page: D917
  article-title: ENCODE whole‐genome data in the UCSC Genome Browser: update 2012
  publication-title: Nucleic acids research
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  start-page: 108
  issue: 7243
  year: 2009
  end-page: 112
  article-title: Histone modifications at human enhancers reflect global cell‐type‐specific gene expression
  publication-title: Nature
– volume: 16
  start-page: 908
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Snippet In this design study, we present an analysis and ion of the data and tasks related to the domain of epigenomics, and the design and implementation of an...
In this design study, we present an analysis and abstraction of the data and tasks related to the domain of epigenomics, and the design and implementation of...
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SubjectTerms Analysis
Biologists
Clusters
Computer graphics
Data processing
Design engineering
Environmental monitoring
Exploration
H.5.m [Information Systems]: Information Interfaces and Presentation-Miscellaneous
I.3.8 [Computing Methodologies]: Computer Graphics-Applications
Interactive
Studies
Tasks
Visualization
Title An Interactive Analysis and Exploration Tool for Epigenomic Data
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Volume 32
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