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X Demographics
Mendeley readers
Attention Score in Context
| Title |
CoreDetector: a flexible and efficient program for core-genome alignment of evolutionary diverse genomes
|
|---|---|
| Published in |
Bioinformatics, October 2023
|
| DOI | 10.1093/bioinformatics/btad628 |
| Pubmed ID | |
| Authors |
Mario Fruzangohar, Paula Moolhuijzen, Nicolette Bakaj, Julian Taylor |
| Abstract |
Whole genome alignment of eukaryote species remains an important method for the determination of sequence and structural variations and can also be used to ascertain the representative non-redundant core genome sequence of a population. Many whole genome alignment tools were first developed for the more mature analysis of prokaryote species with few current tools containing the functionality to process larger genomes of eukaryotes as well as genomes of more divergent species. In addition, the functionality of these tools becomes computationally prohibitive due to the significant compute resources needed to handle larger genomes. In this research we present CoreDetector, an easy-to-use general-purpose program that can align the core-genome sequences for a range of genome sizes and divergence levels. To illustrate the flexibility of CoreDetector we conducted alignments of a large set of closely related fungal pathogen and hexaploid wheat cultivar genomes as well as more divergent fly and rodent species genomes. In all cases, compared to existing multiple genome alignment tools, CoreDetector exhibited improved flexibility, efficiency, and competitive accuracy in tested cases. CoreDetector was developed in the cross platform, and easily deployable, Java language. A packaged pipeline is readily executable in a bash terminal without any external need for Perl or Python environments. Installation, example data and usage instructions for CoreDetector, are freely available from https://github.com/mfruzan/CoreDetector. Supplementary data are available at Bioinformatics online. |
X Demographics
The data shown below were collected from the profiles of 58 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 | 3% |
| Switzerland | 2 | 3% |
| Australia | 1 | 2% |
| Mexico | 1 | 2% |
| United Kingdom | 1 | 2% |
| Uruguay | 1 | 2% |
| Ecuador | 1 | 2% |
| Colombia | 1 | 2% |
| Italy | 1 | 2% |
| Other | 4 | 7% |
| Unknown | 43 | 74% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 30 | 52% |
| Members of the public | 26 | 45% |
| Science communicators (journalists, bloggers, editors) | 2 | 3% |
Mendeley readers
The data shown below were compiled from readership statistics for 5 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 5 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Professor > Associate Professor | 2 | 40% |
| Researcher | 2 | 40% |
| Unknown | 1 | 20% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 2 | 40% |
| Biochemistry, Genetics and Molecular Biology | 1 | 20% |
| Unknown | 2 | 40% |
Attention Score in Context
This research output has an Altmetric Attention Score of 92. 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 11 December 2023.
All research outputs
#481,485
of 26,194,269 outputs
Outputs from Bioinformatics
#61
of 13,020 outputs
Outputs of similar age
#8,705
of 369,969 outputs
Outputs of similar age from Bioinformatics
#3
of 151 outputs
Altmetric has tracked 26,194,269 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 98th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 13,020 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.2. This one has done particularly well, scoring higher than 99% 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 369,969 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 97% of its contemporaries.
We're also able to compare this research output to 151 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 98% of its contemporaries.