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Multivariate Segmentation in the Analysis of Transcription Tiling Array Data

  • Conference paper
Research in Computational Molecular Biology (RECOMB 2007)

Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 4453))

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Abstract

Tiling DNA microarrays extend current microarray technology by probing the non-repeat portion of a genome at regular intervals in an unbiased fashion. A fundamental problem in the analysis of these data is the detection of genomic regions that are differentially transcribed across multiple conditions. We propose a linear time algorithm based on segmentation techniques and linear modeling that can work at a user-selected false discovery rate. It also attains a four-fold sensitivity gain over the only competing algorithm when applied to a whole genome transcription data set spanning the embryonic development of Drosophila melanogaster.

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Authors and Affiliations

  1. Affymetrix, Inc., 6650 Vallejo St. Suite 100, Emeryville, CA 94608,  

    Antonio Piccolboni

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  1. Antonio Piccolboni
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Terry Speed Haiyan Huang

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© 2007 Springer Berlin Heidelberg

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Piccolboni, A. (2007). Multivariate Segmentation in the Analysis of Transcription Tiling Array Data. In: Speed, T., Huang, H. (eds) Research in Computational Molecular Biology. RECOMB 2007. Lecture Notes in Computer Science(), vol 4453. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-71681-5_22

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  • DOI: https://doi.org/10.1007/978-3-540-71681-5_22

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-71680-8

  • Online ISBN: 978-3-540-71681-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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