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Pooled Genomic Indexing (PGI): Mathematical Analysis and Experiment Design

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Algorithms in Bioinformatics (WABI 2002)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2452))

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Abstract

Pooled Genomic Indexing (PGI) is a novel method for physical mapping of clones onto known macromolecular sequences. PGI is carried out by pooling arrayed clones, generating shotgun sequence reads from pools and by comparing the reads against a reference sequence. If two reads from two different pools match the reference sequence at a close distance, they are both assigned (deconvoluted) to the clone at the intersection of the two pools and the clone is mapped onto the region of the reference sequence between the two matches. A probabilistic model for PGI is developed, and several pooling schemes are designed and analyzed. The probabilistic model and the pooling schemes are validated in simulated experiments where 625 rat BAC clones and 207 mouse BAC clones are mapped onto homologous human sequence.

Bacterial Artificial Chromosome

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Author information

Authors and Affiliations

  1. Département d’informatique et de recherche opérationnelle, Université de Montréal, CP 6128 succ. Centre-Ville, H3C 3J7, Montréal, Québec, Canada

    Miklós Csűrös

  2. Human Genome Sequencing Center, Department of Molecular and Human Genetics, Baylor College of Medicine, Canada

    Miklós Csűrös & Aleksandar Milosavljevic

  3. Bioinformatics Research Laboratory Department of Molecular and Human Genetics, Baylor College of Medicine, 77030, Houston, Texas, USA

    Miklós Csűrös & Aleksandar Milosavljevic

Authors
  1. Miklós Csűrös
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  2. Aleksandar Milosavljevic
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Editor information

Editors and Affiliations

  1. IMIM-UPF-CRG, Dr. Aiguader 80, 08003, Barcelona, Spain

    Roderic Guigó

  2. Department of Computer Science, University of California, 95616, Davis, CA, USA

    Dan Gusfield

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© 2002 Springer-Verlag Berlin Heidelberg

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Csűrös, M., Milosavljevic, A. (2002). Pooled Genomic Indexing (PGI): Mathematical Analysis and Experiment Design. In: Guigó, R., Gusfield, D. (eds) Algorithms in Bioinformatics. WABI 2002. Lecture Notes in Computer Science, vol 2452. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45784-4_2

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  • DOI: https://doi.org/10.1007/3-540-45784-4_2

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-44211-0

  • Online ISBN: 978-3-540-45784-8

  • eBook Packages: Springer Book Archive

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