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Is the whole greater than the sum of its parts? De novo assembly strategies for bacterial genomes based on paired-end sequencing

Overview of attention for article published in BMC Genomics, August 2015
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (75th percentile)
  • Good Attention Score compared to outputs of the same age and source (75th percentile)

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Title
Is the whole greater than the sum of its parts? De novo assembly strategies for bacterial genomes based on paired-end sequencing
Published in
BMC Genomics, August 2015
DOI 10.1186/s12864-015-1859-8
Pubmed ID
Authors

Ting-Wen Chen, Ruei-Chi Gan, Yi-Feng Chang, Wei-Chao Liao, Timothy H. Wu, Chi-Ching Lee, Po-Jung Huang, Cheng-Yang Lee, Yi-Ywan M. Chen, Cheng-Hsun Chiu, Petrus Tang

Abstract

Whole genome sequence construction is becoming increasingly feasible because of advances in next generation sequencing (NGS), including increasing throughput and read length. By simply overlapping paired-end reads, we can obtain longer reads with higher accuracy, which can facilitate the assembly process. However, the influences of different library sizes and assembly methods on paired-end sequencing-based de novo assembly remain poorly understood. We used 250 bp Illumina Miseq paired-end reads of different library sizes generated from genomic DNA from Escherichia coli DH1 and Streptococcus parasanguinis FW213 to compare the assembly results of different library sizes and assembly approaches. Our data indicate that overlapping paired-end reads can increase read accuracy but sometimes cause insertion or deletions. Regarding genome assembly, merged reads only outcompete original paired-end reads when coverage depth is low, and larger libraries tend to yield better assembly results. These results imply that distance information is the most critical factor during assembly. Our results also indicate that when depth is sufficiently high, assembly from subsets can sometimes produce better results. In summary, this study provides systematic evaluations of de novo assembly from paired end sequencing data. Among the assembly strategies, we find that overlapping paired-end reads is not always beneficial for bacteria genome assembly and should be avoided or used with caution especially for genomes containing high fraction of repetitive sequences. Because increasing numbers of projects aim at bacteria genome sequencing, our study provides valuable suggestions for the field of genomic sequence construction.

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The data shown below were collected from the profiles of 12 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 58 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 3%
Germany 1 2%
Brazil 1 2%
Norway 1 2%
Belgium 1 2%
Taiwan 1 2%
Unknown 51 88%

Demographic breakdown

Readers by professional status Count As %
Researcher 17 29%
Student > Ph. D. Student 10 17%
Student > Bachelor 10 17%
Student > Master 6 10%
Student > Doctoral Student 4 7%
Other 8 14%
Unknown 3 5%
Readers by discipline Count As %
Agricultural and Biological Sciences 25 43%
Biochemistry, Genetics and Molecular Biology 14 24%
Computer Science 6 10%
Environmental Science 4 7%
Immunology and Microbiology 2 3%
Other 0 0%
Unknown 7 12%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 24 May 2016.
All research outputs
#5,654,551
of 22,826,360 outputs
Outputs from BMC Genomics
#2,326
of 10,654 outputs
Outputs of similar age
#66,272
of 268,158 outputs
Outputs of similar age from BMC Genomics
#63
of 262 outputs
Altmetric has tracked 22,826,360 research outputs across all sources so far. Compared to these this one has done well and is in the 75th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 10,654 research outputs from this source. They receive a mean Attention Score of 4.7. This one has done well, scoring higher than 77% 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 268,158 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 75% of its contemporaries.
We're also able to compare this research output to 262 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 75% of its contemporaries.