↓ Skip to main content

InteMAP: Integrated metagenomic assembly pipeline for NGS short reads

Overview of attention for article published in BMC Bioinformatics, August 2015
Altmetric Badge

About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (84th percentile)
  • High Attention Score compared to outputs of the same age and source (82nd percentile)

Mentioned by

twitter
20 X users

Citations

dimensions_citation
23 Dimensions

Readers on

mendeley
122 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
InteMAP: Integrated metagenomic assembly pipeline for NGS short reads
Published in
BMC Bioinformatics, August 2015
DOI 10.1186/s12859-015-0686-x
Pubmed ID
Authors

Binbin Lai, Fumeng Wang, Xiaoqi Wang, Liping Duan, Huaiqiu Zhu

Abstract

Next-generation sequencing (NGS) has greatly facilitated metagenomic analysis but also raised new challenges for metagenomic DNA sequence assembly, owing to its high-throughput nature and extremely short reads generated by sequencers such as Illumina. To date, how to generate a high-quality draft assembly for metagenomic sequencing projects has not been fully addressed. We conducted a comprehensive assessment on state-of-the-art de novo assemblers and revealed that the performance of each assembler depends critically on the sequencing depth. To address this problem, we developed a pipeline named InteMAP to integrate three assemblers, ABySS, IDBA-UD and CABOG, which were found to complement each other in assembling metagenomic sequences. Making a decision of which assembling approaches to use according to the sequencing coverage estimation algorithm for each short read, the pipeline presents an automatic platform suitable to assemble real metagenomic NGS data with uneven coverage distribution of sequencing depth. By comparing the performance of InteMAP with current assemblers on both synthetic and real NGS metagenomic data, we demonstrated that InteMAP achieves better performance with a longer total contig length and higher contiguity, and contains more genes than others. We developed a de novo pipeline, named InteMAP, that integrates existing tools for metagenomics assembly. The pipeline outperforms previous assembly methods on metagenomic assembly by providing a longer total contig length, a higher contiguity and covering more genes. InteMAP, therefore, could potentially be a useful tool for the research community of metagenomics.

X Demographics

X Demographics

The data shown below were collected from the profiles of 20 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 122 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 5 4%
Brazil 3 2%
United States 3 2%
Uruguay 1 <1%
Sweden 1 <1%
Australia 1 <1%
Spain 1 <1%
Russia 1 <1%
Unknown 106 87%

Demographic breakdown

Readers by professional status Count As %
Researcher 33 27%
Student > Ph. D. Student 30 25%
Student > Master 17 14%
Student > Bachelor 10 8%
Professor 7 6%
Other 17 14%
Unknown 8 7%
Readers by discipline Count As %
Agricultural and Biological Sciences 58 48%
Biochemistry, Genetics and Molecular Biology 31 25%
Computer Science 8 7%
Immunology and Microbiology 8 7%
Environmental Science 3 2%
Other 3 2%
Unknown 11 9%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 11. 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 03 February 2016.
All research outputs
#3,247,313
of 24,885,505 outputs
Outputs from BMC Bioinformatics
#1,062
of 7,601 outputs
Outputs of similar age
#40,206
of 269,698 outputs
Outputs of similar age from BMC Bioinformatics
#21
of 117 outputs
Altmetric has tracked 24,885,505 research outputs across all sources so far. Compared to these this one has done well and is in the 86th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,601 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one has done well, scoring higher than 85% 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 269,698 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 84% of its contemporaries.
We're also able to compare this research output to 117 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 82% of its contemporaries.