| Title |
Comparison of Genome Sequencing Technology and Assembly Methods for the Analysis of a GC-Rich Bacterial Genome
|
|---|---|
| Published in |
Current Microbiology, November 2014
|
| DOI | 10.1007/s00284-014-0721-6 |
| Pubmed ID | |
| Authors |
Derrick Scott, Bert Ely |
| Abstract |
Improvements in technology and decreases in price have made de novo bacterial genomic sequencing a reality for many researchers, but it has created a need to evaluate the methods for generating a complete and accurate genome assembly. We sequenced the GC-rich Caulobacter henricii genome using the Illumina MiSeq, Roche 454, and Pacific Biosciences RS II sequencing systems. To generate a complete genome sequence, we performed assemblies using eight readily available programs and found that builds using the Illumina MiSeq and the Roche 454 data produced accurate yet numerous contigs. SPAdes performed the best followed by PANDAseq. In contrast, the Celera assembler produced a single genomic contig using the Pacific Biosciences data after error correction with the Illumina MiSeq data. In addition, we duplicated this build using the Pacific Biosciences data with HGAP2.0. The accuracy of these builds was verified by pulsed-field gel electrophoresis of genomic DNA cut with restriction enzymes. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 76 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 3 | 4% |
| France | 1 | 1% |
| Colombia | 1 | 1% |
| Belgium | 1 | 1% |
| Sweden | 1 | 1% |
| Unknown | 69 | 91% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 20 | 26% |
| Student > Ph. D. Student | 19 | 25% |
| Researcher | 14 | 18% |
| Professor | 3 | 4% |
| Other | 2 | 3% |
| Other | 5 | 7% |
| Unknown | 13 | 17% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 26 | 34% |
| Biochemistry, Genetics and Molecular Biology | 23 | 30% |
| Immunology and Microbiology | 4 | 5% |
| Computer Science | 3 | 4% |
| Medicine and Dentistry | 2 | 3% |
| Other | 4 | 5% |
| Unknown | 14 | 18% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 13 February 2017.
All research outputs
#17,731,162
of 22,769,322 outputs
Outputs from Current Microbiology
#1,567
of 2,406 outputs
Outputs of similar age
#177,336
of 262,838 outputs
Outputs of similar age from Current Microbiology
#14
of 29 outputs
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