Introduction

Functional annotation of the gigantic metagenomic data is one of the major time-consuming and computationally demanding tasks, which is currently a bottleneck for the efficient analysis. The commonly used homology-based methods to functionally annotate and classify proteins are extremely slow. Therefore, to achieve faster and accurate functional annotation, we have developed an orthology-based functional classifier 'Woods' by using a combination of machine learning and similarity-based approaches. Woods displayed a precision of 98.79% on independent genomic dataset, 96.66% on simulated metagenomic dataset and >97% on two real metagenomic datasets. In addition, it performed >87 times faster than BLAST on the two real metagenomic datasets. Woods can be used as a highly efficient and accurate classifier with high-throughput capability which facilitates its usability on large metagenomic datasets.

Publications

  1. Woods: A fast and accurate functional annotator and classifier of genomic and metagenomic sequences.
    Cite this
    Sharma AK, Gupta A, Kumar S, Dhakan DB, Sharma VK, 2015-07-01 - Genomics

Credits

  1. Ashok K Sharma
    Developer

    MetaInformatics Laboratory, Metagenomics and Systems Biology Group, India

  2. Ankit Gupta
    Developer

    MetaInformatics Laboratory, Metagenomics and Systems Biology Group, India

  3. Sanjiv Kumar
    Developer

    MetaInformatics Laboratory, Metagenomics and Systems Biology Group, India

  4. Darshan B Dhakan
    Developer

    MetaInformatics Laboratory, Metagenomics and Systems Biology Group, India

  5. Vineet K Sharma
    Investigator

    MetaInformatics Laboratory, Metagenomics and Systems Biology Group, India

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Summary
AccessionBT000117
Tool TypeApplication
Category
PlatformsLinux/Unix
TechnologiesPerl, R
User InterfaceTerminal Command Line
Download Count0
Submitted ByVineet K Sharma