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Fast Algorithms for Inferring Gene-Species Associations

  • Arkadiusz BetkierEmail author
  • Paweł Szczęsny
  • Paweł Górecki
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9096)

Abstract

Assessment of microbial biodiversity is typically made by sequencing either PCR-amplified marker genes or all genomic DNA from environmental samples. Both approaches rely on the similarity of the sequenced material to known entries in sequence databases. However, amplicons of non-marker genes are often used, when the research question aims at assessing both functional capabilities of a microbial community and its biodiversity. In such cases, a phylogenetic tree is constructed with known and metagenomic sequences, and expert assessment defines the taxonomic groups the amplicons belong to. Here, instead of relying on sequences, often missing, of non-marker genes, we use tree reconciliation to obtain a distribution of mappings between genes and species. We describe efficient algorithms for the reconstruction of gene-species mappings and a Monte-Carlo method for the inference of distributions for the cases when the number of optimal reconstructions is large. We provide a comparative study of different cost functions showing that the duplication-loss cost induces mappings of the highest quality. Further, we demonstrate the correctness of our approach using several datasets.

Keywords

Species Tree Gene Tree Horizontal Gene Transfer Input Tree mcrA Gene 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Arkadiusz Betkier
    • 1
    Email author
  • Paweł Szczęsny
    • 2
  • Paweł Górecki
    • 1
  1. 1.Faculty of Mathematics, Informatics and MechanicsUniversity of WarsawWarsawPoland
  2. 2.Institute of Biochemistry and BiophysicsPolish Academy of SciencesWarsawPoland

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