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GRASP: guided reference-based assembly of short peptides.

Cuncong Zhong1, Youngik Yang1, Shibu Yooseph2

  • 1Informatics Department, J. Craig Venter Institute, La Jolla, CA 92037, USA.

Nucleic Acids Research
|November 22, 2014
PubMed
Summary

GRASP is a new algorithm that accurately finds protein homologs in fragmented metagenomic data. This tool improves the detection and quantification of taxonomic and protein family abundances in metagenomic datasets.

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Area of Science:

  • Metagenomics
  • Bioinformatics
  • Computational Biology

Background:

  • Metagenomic protein annotation relies on homology detection.
  • Partial-length protein sequences from fragmented metagenomic data hinder accurate homology detection.
  • This limitation impacts the quality of metagenomic dataset annotations.

Purpose of the Study:

  • To present a novel algorithm, GRASP, for accurate homology detection of reference proteins within partial-length metagenomic protein databases.
  • To improve the annotation quality of metagenomic datasets.

Main Methods:

  • GRASP employs a reference-guided strategy for homology detection.
  • It simultaneously searches and assembles overlapping sequences in the database.
  • The algorithm was compared against BLASTP, PSI-BLAST, and FASTM using simulated and real datasets.

Main Results:

  • GRASP demonstrates significantly higher sensitivity compared to BLASTP, PSI-BLAST, and FASTM.
  • The algorithm maintains a very high specificity.
  • Evaluations confirmed GRASP's effectiveness on both simulated and real metagenomic data.

Conclusions:

  • GRASP accurately identifies homologs of reference proteins from partial-length metagenomic sequences.
  • The algorithm enhances the detection and quantification of taxonomic and protein family abundances.
  • GRASP offers a valuable tool for metagenomic data analysis and annotation.