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

Overview of attention for article published in BMC Bioinformatics, August 2016
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (90th percentile)
  • High Attention Score compared to outputs of the same age and source (93rd percentile)

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Title
GRASPx: efficient homolog-search of short peptide metagenome database through simultaneous alignment and assembly
Published in
BMC Bioinformatics, August 2016
DOI 10.1186/s12859-016-1119-1
Pubmed ID
Authors

Cuncong Zhong, Youngik Yang, Shibu Yooseph

Abstract

Metagenomics 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. The 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. In 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/ .

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 30 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Brazil 2 7%
Unknown 28 93%

Demographic breakdown

Readers by professional status Count As %
Researcher 10 33%
Student > Master 5 17%
Student > Ph. D. Student 3 10%
Other 2 7%
Student > Doctoral Student 2 7%
Other 4 13%
Unknown 4 13%
Readers by discipline Count As %
Agricultural and Biological Sciences 10 33%
Biochemistry, Genetics and Molecular Biology 7 23%
Computer Science 3 10%
Immunology and Microbiology 2 7%
Environmental Science 1 3%
Other 2 7%
Unknown 5 17%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 19. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 04 April 2023.
All research outputs
#1,747,191
of 23,515,785 outputs
Outputs from BMC Bioinformatics
#385
of 7,404 outputs
Outputs of similar age
#32,330
of 339,538 outputs
Outputs of similar age from BMC Bioinformatics
#9
of 136 outputs
Altmetric has tracked 23,515,785 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,404 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one has done particularly well, scoring higher than 94% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 339,538 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 90% of its contemporaries.
We're also able to compare this research output to 136 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 93% of its contemporaries.