| Title |
SuRankCo: supervised ranking of contigs in de novo assemblies
|
|---|---|
| Published in |
BMC Bioinformatics, July 2015
|
| DOI | 10.1186/s12859-015-0644-7 |
| Pubmed ID | |
| Authors |
Mathias Kuhring, Piotr Wojtek Dabrowski, Vitor C. Piro, Andreas Nitsche, Bernhard Y. Renard |
| Abstract |
Evaluating the quality and reliability of a de novo assembly and of single contigs in particular is challenging since commonly a ground truth is not readily available and numerous factors may influence results. Currently available procedures provide assembly scores but lack a comparative quality ranking of contigs within an assembly. We present SuRankCo, which relies on a machine learning approach to predict quality scores for contigs and to enable the ranking of contigs within an assembly. The result is a sorted contig set which allows selective contig usage in downstream analysis. Benchmarking on datasets with known ground truth shows promising sensitivity and specificity and favorable comparison to existing methodology. SuRankCo analyzes the reliability of de novo assemblies on the contig level and thereby allows quality control and ranking prior to further downstream and validation experiments. |
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% |
| United Kingdom | 2 | 12% |
| Canada | 2 | 12% |
| China | 1 | 6% |
| Sweden | 1 | 6% |
| Italy | 1 | 6% |
| Unknown | 7 | 41% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 9 | 53% |
| Members of the public | 8 | 47% |
Mendeley readers
The data shown below were compiled from readership statistics for 49 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Netherlands | 1 | 2% |
| France | 1 | 2% |
| Norway | 1 | 2% |
| Korea, Republic of | 1 | 2% |
| Sweden | 1 | 2% |
| United States | 1 | 2% |
| Unknown | 43 | 88% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 17 | 35% |
| Student > Bachelor | 7 | 14% |
| Student > Ph. D. Student | 7 | 14% |
| Professor > Associate Professor | 3 | 6% |
| Student > Master | 3 | 6% |
| Other | 6 | 12% |
| Unknown | 6 | 12% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 20 | 41% |
| Computer Science | 10 | 20% |
| Biochemistry, Genetics and Molecular Biology | 7 | 14% |
| Engineering | 3 | 6% |
| Social Sciences | 1 | 2% |
| Other | 1 | 2% |
| Unknown | 7 | 14% |
Attention Score in Context
This research output has an Altmetric Attention Score of 19. 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 October 2015.
All research outputs
#2,013,186
of 25,706,302 outputs
Outputs from BMC Bioinformatics
#423
of 7,735 outputs
Outputs of similar age
#24,855
of 275,676 outputs
Outputs of similar age from BMC Bioinformatics
#7
of 108 outputs
Altmetric has tracked 25,706,302 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,735 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.6. This one has done particularly well, scoring higher than 94% of its peers.
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We're also able to compare this research output to 108 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 93% of its contemporaries.