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.
X Demographics
Mendeley readers
Attention Score in Context
| Title |
A method for near full-length amplification and sequencing for six hepatitis C virus genotypes
|
|---|---|
| Published in |
BMC Genomics, March 2016
|
| DOI | 10.1186/s12864-016-2575-8 |
| Pubmed ID | |
| Authors |
Rowena A. Bull, Auda A. Eltahla, Chaturaka Rodrigo, Sylvie M. Koekkoek, Melanie Walker, Mehdi R. Pirozyan, Brigid Betz-Stablein, Armin Toepfer, Melissa Laird, Steve Oh, Cheryl Heiner, Lisa Maher, Janke Schinkel, Andrew R. Lloyd, Fabio Luciani |
| Abstract |
Hepatitis C virus (HCV) is a rapidly evolving RNA virus that has been classified into seven genotypes. All HCV genotypes cause chronic hepatitis, which ultimately leads to liver diseases such as cirrhosis. The genotypes are unevenly distributed across the globe, with genotypes 1 and 3 being the most prevalent. Until recently, molecular epidemiological studies of HCV evolution within the host and at the population level have been limited to the analyses of partial viral genome segments, as it has been technically challenging to amplify and sequence the full-length of the 9.6 kb HCV genome. Although recent improvements have been made in full genome sequencing methodologies, these protocols are still either limited to a specific genotype or cost-inefficient. In this study we describe a genotype-specific protocol for the amplification and sequencing of the near-full length genome of all six major HCV genotypes. We applied this protocol to 122 HCV positive clinical samples, and had a successful genome amplification rate of 90 %, when the viral load was greater than 15,000 IU/ml. The assay was shown to have a detection limit of 1-3 cDNA copies per reaction. The method was tested with both Illumina and PacBio single molecule, real-time (SMRT) sequencing technologies. Illumina sequencing resulted in deep coverage and allowed detection of rare variants as well as HCV co-infection with multiple genotypes. The application of the method with PacBio RS resulted in sequence reads greater than 9 kb that covered the near full-length HCV amplicon in a single read and enabled analysis of the near full-length quasispecies. The protocol described herein can be utilised for rapid amplification and sequencing of the near-full length HCV genome in a cost efficient manner suitable for a wide range of applications. |
X Demographics
The data shown below were collected from the profiles of 7 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 | 2 | 29% |
| Unknown | 5 | 71% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 4 | 57% |
| Members of the public | 3 | 43% |
Mendeley readers
The data shown below were compiled from readership statistics for 105 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Netherlands | 1 | <1% |
| France | 1 | <1% |
| Switzerland | 1 | <1% |
| Unknown | 102 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 30 | 29% |
| Student > Ph. D. Student | 22 | 21% |
| Student > Bachelor | 10 | 10% |
| Other | 8 | 8% |
| Student > Master | 6 | 6% |
| Other | 18 | 17% |
| Unknown | 11 | 10% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 35 | 33% |
| Biochemistry, Genetics and Molecular Biology | 25 | 24% |
| Medicine and Dentistry | 16 | 15% |
| Immunology and Microbiology | 7 | 7% |
| Environmental Science | 2 | 2% |
| Other | 7 | 7% |
| Unknown | 13 | 12% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 29 March 2016.
All research outputs
#12,755,748
of 22,856,968 outputs
Outputs from BMC Genomics
#4,403
of 10,661 outputs
Outputs of similar age
#144,951
of 326,713 outputs
Outputs of similar age from BMC Genomics
#80
of 217 outputs
Altmetric has tracked 22,856,968 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
So far Altmetric has tracked 10,661 research outputs from this source. They receive a mean Attention Score of 4.7. This one has gotten more attention than average, scoring higher than 57% 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 326,713 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 55% of its contemporaries.
We're also able to compare this research output to 217 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 58% of its contemporaries.