Abstract Details
Activity Number:
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596
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Type:
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Topic Contributed
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Date/Time:
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Thursday, August 7, 2014 : 8:30 AM to 10:20 AM
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Sponsor:
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Biometrics Section
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Abstract #311429
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View Presentation
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Title:
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Image Rna-Seq Data Analysis in Clouds
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Author(s):
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Junhai Jiang*+ and Nan Lin and Momiao Xiong
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Companies:
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UTSPH and UTSPH and University of Texas Health Science Center at Houston
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Keywords:
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Image Genetics ;
RNA-seq ;
Cloud Computing
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Abstract:
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Large-scale integrated genetic and imaging data analysis is a new approach used to uncover the individual variability and mechanism of disease development. This approach, which has not been well developed, has the potential to open a new avenue for dissecting genetic structure of complex disease and personal medicine. Joint analysis of imaging and RNA-seq data will identify genes significantly associated with tumors and provide useful information on target therapy. However, an image may contain 100k-1M voxels and RNA-seq data may include number of reads in 100 M genomic position. As both imaging- and RNA-seq-domain observations include a huge number of variables, joint image and RNA-seq analysis on such Big Data represents a computational challenge that cannot be addressed with conventional computational techniques. To address this challenge, we use cloud computing techniques to develop sophisticated algorithms for joint analysis of imaging and RNA-seq data running on Amazon cloud computer. The developed method has been applied to image and RNA-seq data of ovarian cancer downloaded from TCGA datasets. We identify 124 significantly associated genes.
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Authors who are presenting talks have a * after their name.
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