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STRScan: targeted profiling of short tandem repeats in whole-genome sequencing data

Overview of attention for article published in BMC Bioinformatics, October 2017
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Title
STRScan: targeted profiling of short tandem repeats in whole-genome sequencing data
Published in
BMC Bioinformatics, October 2017
DOI 10.1186/s12859-017-1800-z
Pubmed ID
Authors

Haixu Tang, Etienne Nzabarushimana

Abstract

Short tandem repeats (STRs) are found in many prokaryotic and eukaryotic genomes, and are commonly used as genetic markers, in particular for identity and parental testing in DNA forensics. The unstable expansion of some STRs was associated with various genetic disorders (e.g., the Huntington disease), and thus was used in genetic testing for screening individuals at high risk. Traditional STR analyses were based on the PCR amplification of STR loci followed by gel electrophoresis. With the availability of massive whole genome sequencing data, it becomes practical to mine STR profiles in silico from genome sequences. Software tools such as lobSTR and STR-FM have been developed to address these demands, which are, however, built upon whole genome reads mapping tools, and thus may not be sensitive enough. In this paper, we present a standalone software tool STRScan that uses a greedy algorithm for targeted STR profiling in next-generation sequencing (NGS) data. STRScan was tested on the whole genome sequencing data from Venter genome sequencing and 1000 Genomes Project. The results showed that STRScan can profile 20% more STRs in the target set that are missed by lobSTR. STRScan is particularly useful for the NGS-based targeted STR profiling, e.g., in genetic and human identity testing. STRScan is available as open-source software at http://darwin.informatics.indiana.edu/str/ .

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 73 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 73 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 12 16%
Student > Ph. D. Student 12 16%
Researcher 9 12%
Student > Doctoral Student 6 8%
Student > Bachelor 5 7%
Other 14 19%
Unknown 15 21%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 24 33%
Agricultural and Biological Sciences 10 14%
Computer Science 4 5%
Psychology 3 4%
Medicine and Dentistry 3 4%
Other 10 14%
Unknown 19 26%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 07 October 2017.
All research outputs
#14,082,324
of 23,005,189 outputs
Outputs from BMC Bioinformatics
#4,496
of 7,312 outputs
Outputs of similar age
#172,261
of 323,064 outputs
Outputs of similar age from BMC Bioinformatics
#50
of 105 outputs
Altmetric has tracked 23,005,189 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,312 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 35th percentile – i.e., 35% of its peers scored the same or lower than it.
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 323,064 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 45th percentile – i.e., 45% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 105 others from the same source and published within six weeks on either side of this one. This one is in the 49th percentile – i.e., 49% of its contemporaries scored the same or lower than it.