| Title |
HTQC: a fast quality control toolkit for Illumina sequencing data
|
|---|---|
| Published in |
BMC Bioinformatics, January 2013
|
| DOI | 10.1186/1471-2105-14-33 |
| Pubmed ID | |
| Authors |
Xi Yang, Di Liu, Fei Liu, Jun Wu, Jing Zou, Xue Xiao, Fangqing Zhao, Baoli Zhu |
| Abstract |
Illumina sequencing platform is widely used in genome research. Sequence reads quality assessment and control are needed for downstream analysis. However, software that provides efficient quality assessment and versatile filtration methods is still lacking. |
X Demographics
The data shown below were collected from the profiles of 17 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 | 3 | 18% |
| France | 2 | 12% |
| Tunisia | 1 | 6% |
| Montenegro | 1 | 6% |
| Belgium | 1 | 6% |
| Cameroon | 1 | 6% |
| Canada | 1 | 6% |
| Norway | 1 | 6% |
| Spain | 1 | 6% |
| Other | 2 | 12% |
| Unknown | 3 | 18% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 9 | 53% |
| Members of the public | 7 | 41% |
| Practitioners (doctors, other healthcare professionals) | 1 | 6% |
Mendeley readers
The data shown below were compiled from readership statistics for 213 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 6 | 3% |
| France | 3 | 1% |
| Sweden | 3 | 1% |
| Germany | 1 | <1% |
| Switzerland | 1 | <1% |
| Brazil | 1 | <1% |
| Colombia | 1 | <1% |
| Chile | 1 | <1% |
| Czechia | 1 | <1% |
| Other | 3 | 1% |
| Unknown | 192 | 90% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 55 | 26% |
| Researcher | 51 | 24% |
| Student > Master | 22 | 10% |
| Student > Bachelor | 21 | 10% |
| Student > Doctoral Student | 11 | 5% |
| Other | 32 | 15% |
| Unknown | 21 | 10% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 107 | 50% |
| Biochemistry, Genetics and Molecular Biology | 41 | 19% |
| Computer Science | 13 | 6% |
| Engineering | 6 | 3% |
| Immunology and Microbiology | 4 | 2% |
| Other | 12 | 6% |
| Unknown | 30 | 14% |
Attention Score in Context
This research output has an Altmetric Attention Score of 10. 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 05 April 2016.
All research outputs
#3,373,825
of 23,881,329 outputs
Outputs from BMC Bioinformatics
#1,188
of 7,454 outputs
Outputs of similar age
#35,776
of 287,843 outputs
Outputs of similar age from BMC Bioinformatics
#18
of 136 outputs
Altmetric has tracked 23,881,329 research outputs across all sources so far. Compared to these this one has done well and is in the 85th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,454 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 84% 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 287,843 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 87% 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 well, scoring higher than 87% of its contemporaries.