Evidence map›Paper›PMID 27585568›Full record

ArticleBMC bioinformatics2016

GRASPx: efficient homolog-search of short peptide metagenome database through simultaneous alignment and assembly.

Cuncong Zhong, Youngik Yang, Shibu Yooseph

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Article in BMC bioinformatics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

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3citing papers in PubMed
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3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Cuncong ZhongInformatics Department, J. Craig Venter Institute, La Jolla, CA, 92037, USA.
Youngik YangInformatics Department, J. Craig Venter Institute, La Jolla, CA, 92037, USA.
Shibu YoosephInformatics Department, J. Craig Venter Institute, La Jolla, CA, 92037, USA. syooseph@jcvi.org.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMetagenomics is a cultivation-independent approach that enables the study of the genomic composition of microbes present in an environment. Metagenomic samples are routinely sequenced using next-generation sequencing technologies that generate short nucleotide reads. Proteins identified from these reads are mostly of partial length. On the other hand, de novo assembly of a large metagenomic dataset is computationally demanding and the assembled contigs are often fragmented, resulting in the identification of protein sequences that are also of partial length and incomplete. Annotation of an incomplete protein sequence often proceeds by identifying its homologs in a database of reference sequences. Identifying the homologs of incomplete sequences is a challenge and can result in substandard annotation of proteins from metagenomic datasets. To address this problem, we recently developed a homology detection algorithm named GRASP (Guided Reference-based Assembly of Short Peptides) that identifies the homologs of a given reference protein sequence in a database of short peptide metagenomic sequences. GRASP was developed to implement a simultaneous alignment and assembly algorithm for annotation of short peptides identified on metagenomic reads. The program achieves significantly improved recall rate at the cost of computational efficiency. In this article, we adopted three techniques to speed up the original version of GRASP, including the pre-construction of extension links, local assembly of individual seeds, and the implementation of query-level parallelism.

resultsThe resulting new program, GRASPx, achieves >30X speedup compared to its predecessor GRASP. At the same time, we show that the performance of GRASPx is consistent with that of GRASP, and that both of them significantly outperform other popular homology-search tools including the BLAST and FASTA suites. GRASPx was also applied to a human saliva metagenome dataset and shows superior performance for both recall and precision rates.

conclusionsIn this article we present GRASPx, a fast and accurate homology-search program implementing a simultaneous alignment and assembly framework. GRASPx can be used for more comprehensive and accurate annotation of short peptides. GRASPx is freely available at http://graspx.sourceforge.net/ .

Indexed as

AlgorithmsDatabases, ProteinMetagenomeSequence Homology, Amino AcidAmino Acid SequenceComputer SimulationHumansMetagenomicsPeptidesSequence AlignmentPeptides

Identifiers

PMID27585568
PMCPMC5009819

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.