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    • Keywords


      Alignment-free; feature vector space; metagenomics; micro-eukaryotes; oligonucleotide composition

    • Abstract


      Physical partitioning techniques are routinely employed (during sample preparation stage) for segregating the prokaryotic and eukaryotic fractions of metagenomic samples. In spite of these efforts, several metagenomic studies focusing on bacterial and archaeal populations have reported the presence of contaminating eukaryotic sequences inmetagenomic data sets. Contaminating sequences originate not only from genomes of micro-eukaryotic species but also from genomes of (higher) eukaryotic host cells. The latter scenario usually occurs in the case of host-associatedmetagenomes. Identification and removal of contaminating sequences is important, since these sequences not only impact estimates of microbial diversity but also affect the accuracy of several downstream analyses. Currently, the computational techniques used for identifying contaminating eukaryotic sequences, being alignment based, are slow, inefficient, and require huge computing resources. In this article, we present Eu-Detect, an alignment-free algorithm that can rapidly identify eukaryotic sequences contaminating metagenomic data sets. Validation results indicate that on a desktop with modest hardware specifications, the Eu-Detect algorithm is able to rapidly segregate DNA sequence fragments of prokaryotic and eukaryotic origin, with high sensitivity. A Web server for the Eu-Detect algorithm is available at http://metagenomics.atc.tcs.com/Eu-Detect/.

    • Author Affiliations


      Monzoorul Haque Mohammed1 Sudha Chadaram Dinakar1 Dinakar Komanduri1 Tarini Shankar Ghosh1 Sharmila S Mande1

      1. Bio-Sciences R & D Division, TCS Innovation Labs, Tata Consultancy Services Limited, Hyderabad 500 081, India
    • Dates

    • Supplementary Material

  • Journal of Biosciences | News

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      Posted on July 25, 2019

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