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X Demographics
Mendeley readers
Attention Score in Context
| Title |
nPoRe: n-polymer realigner for improved pileup-based variant calling
|
|---|---|
| Published in |
BMC Bioinformatics, March 2023
|
| DOI | 10.1186/s12859-023-05193-4 |
| Pubmed ID | |
| Authors |
Tim Dunn, David Blaauw, Reetuparna Das, Satish Narayanasamy |
| Abstract |
Despite recent improvements in nanopore basecalling accuracy, germline variant calling of small insertions and deletions (INDELs) remains poor. Although precision and recall for single nucleotide polymorphisms (SNPs) now exceeds 99.5%, INDEL recall remains below 80% for standard R9.4.1 flow cells. We show that read phasing and realignment can recover a significant portion of false negative INDELs. In particular, we extend Needleman-Wunsch affine gap alignment by introducing new gap penalties for more accurately aligning repeated n-polymer sequences such as homopolymers ([Formula: see text]) and tandem repeats ([Formula: see text]). At the same precision, haplotype phasing improves INDEL recall from 63.76 to [Formula: see text] and nPoRe realignment improves it further to [Formula: see text]. |
X Demographics
The data shown below were collected from the profiles of 15 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 Kingdom | 2 | 13% |
| United States | 2 | 13% |
| Poland | 1 | 7% |
| India | 1 | 7% |
| Canada | 1 | 7% |
| Unknown | 8 | 53% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 8 | 53% |
| Members of the public | 7 | 47% |
Mendeley readers
The data shown below were compiled from readership statistics for 4 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 4 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Unspecified | 1 | 25% |
| Student > Ph. D. Student | 1 | 25% |
| Researcher | 1 | 25% |
| Student > Postgraduate | 1 | 25% |
| Readers by discipline | Count | As % |
|---|---|---|
| Unspecified | 1 | 25% |
| Agricultural and Biological Sciences | 1 | 25% |
| Chemistry | 1 | 25% |
| Unknown | 1 | 25% |
Attention Score in Context
This research output has an Altmetric Attention Score of 7. 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 19 March 2023.
All research outputs
#5,327,565
of 25,163,238 outputs
Outputs from BMC Bioinformatics
#1,916
of 7,657 outputs
Outputs of similar age
#101,677
of 416,703 outputs
Outputs of similar age from BMC Bioinformatics
#24
of 145 outputs
Altmetric has tracked 25,163,238 research outputs across all sources so far. Compared to these this one has done well and is in the 78th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,657 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 gotten more attention than average, scoring higher than 74% 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 416,703 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 75% 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 well, scoring higher than 82% of its contemporaries.