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X Demographics
Mendeley readers
Attention Score in Context
| Title |
AGC: compact representation of assembled genomes with fast queries and updates
|
|---|---|
| Published in |
Bioinformatics, March 2023
|
| DOI | 10.1093/bioinformatics/btad097 |
| Pubmed ID | |
| Authors |
Sebastian Deorowicz, Agnieszka Danek, Heng Li |
| Abstract |
High-quality sequence assembly is the ultimate representation of complete genetic information of an individual. Several ongoing pangenome projects are producing collections of high-quality assemblies of various species. Each project has already generated assemblies of hundreds of gigabytes on disk, greatly impeding the distribution of and access to such rich datasets. Here we show how to reduce the size of the sequenced genomes by 2 to 3 orders of magnitude. Our tool compresses the genomes significantly better than the existing programs and is much faster. Moreover, its unique feature is the ability to access any contig (or its part) in a fraction of a second and easily append new samples to the compressed collections. Thanks to this, AGC could be useful not only for backup or transfer purposes, but also for routine analysis of pangenome sequences in common pipelines. With the rapidly reduced cost and improved accuracy of sequencing technologies, we anticipate more comprehensive pangenome projects with much larger sample sizes. AGC is likely to become a foundation tool to store, distribute and access pangenome data. The source code of AGC is available at https://github.com/refresh-bio/agc. The package can be installed via Bioconda at https://anaconda.org/bioconda/agc. Supplementary data are available at Bioinformatics online. |
X Demographics
The data shown below were collected from the profiles of 170 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 | 33 | 19% |
| Germany | 11 | 6% |
| France | 9 | 5% |
| United Kingdom | 8 | 5% |
| Sweden | 5 | 3% |
| Spain | 4 | 2% |
| Netherlands | 3 | 2% |
| Australia | 3 | 2% |
| Canada | 3 | 2% |
| Other | 23 | 14% |
| Unknown | 68 | 40% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 105 | 62% |
| Members of the public | 63 | 37% |
| Practitioners (doctors, other healthcare professionals) | 1 | <1% |
| Science communicators (journalists, bloggers, editors) | 1 | <1% |
Mendeley readers
The data shown below were compiled from readership statistics for 11 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 11 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Unspecified | 2 | 18% |
| Researcher | 2 | 18% |
| Student > Ph. D. Student | 1 | 9% |
| Student > Bachelor | 1 | 9% |
| Student > Master | 1 | 9% |
| Other | 1 | 9% |
| Unknown | 3 | 27% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 3 | 27% |
| Unspecified | 2 | 18% |
| Agricultural and Biological Sciences | 2 | 18% |
| Computer Science | 1 | 9% |
| Unknown | 3 | 27% |
Attention Score in Context
This research output has an Altmetric Attention Score of 90. 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 31 July 2023.
All research outputs
#475,497
of 25,576,275 outputs
Outputs from Bioinformatics
#59
of 12,857 outputs
Outputs of similar age
#10,968
of 423,582 outputs
Outputs of similar age from Bioinformatics
#3
of 145 outputs
Altmetric has tracked 25,576,275 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 12,857 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.0. 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 423,582 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 145 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.