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MPD: multiplex primer design for next-generation targeted sequencing

Overview of attention for article published in BMC Bioinformatics, January 2017
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2 tweeters

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Title
MPD: multiplex primer design for next-generation targeted sequencing
Published in
BMC Bioinformatics, January 2017
DOI 10.1186/s12859-016-1453-3
Pubmed ID
Authors

Thomas S. Wingo, Alex Kotlar, David J. Cutler

Abstract

Targeted resequencing offers a cost-effective alternative to whole-genome and whole-exome sequencing when investigating regions known to be associated with a trait or disease. There are a number of approaches to targeted resequencing, including microfluidic PCR amplification, which may be enhanced by multiplex PCR. Currently, there is no open-source software that can design next-generation multiplex PCR experiments that ensures primers are unique at a genome-level and efficiently pools compatible primers. We present MPD, a software package that automates the design of multiplex PCR primers for next-generation sequencing. The core of MPD is implemented in C for speed and uses a hashed genome to ensure primer uniqueness, avoids placing primers over sites of known variation, and efficiently pools compatible primers. A JavaScript web application ( http://multiplexprimer.io ) utilizing the MPD Perl package provides a convenient platform for users to make designs. Using a realistic set of genes identified by genome-wide association studies (GWAS), we achieve 90% coverage of all exonic regions using stringent design criteria. Using the first 47 primer pools for wet-lab validation, we sequenced ~25Kb at 99.7% completeness with a mean coverage of 300X among 313 samples simultaneously and identified 224 variants. The number and nature of variants we observe are consistent with high quality sequencing. MPD can successfully design multiplex PCR experiments suitable for next-generation sequencing, and simplifies retooling targeted resequencing pipelines to focus on new targets as new genetic evidence emerges.

Twitter Demographics

The data shown below were collected from the profiles of 2 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 112 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 <1%
China 1 <1%
France 1 <1%
Unknown 109 97%

Demographic breakdown

Readers by professional status Count As %
Researcher 34 30%
Student > Ph. D. Student 17 15%
Student > Master 17 15%
Student > Bachelor 10 9%
Other 7 6%
Other 10 9%
Unknown 17 15%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 37 33%
Agricultural and Biological Sciences 34 30%
Computer Science 6 5%
Immunology and Microbiology 5 4%
Nursing and Health Professions 2 2%
Other 9 8%
Unknown 19 17%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 10 January 2017.
All research outputs
#15,416,191
of 22,925,760 outputs
Outputs from BMC Bioinformatics
#5,390
of 7,306 outputs
Outputs of similar age
#256,610
of 420,807 outputs
Outputs of similar age from BMC Bioinformatics
#84
of 138 outputs
Altmetric has tracked 22,925,760 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,306 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 18th percentile – i.e., 18% 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 420,807 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 30th percentile – i.e., 30% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 138 others from the same source and published within six weeks on either side of this one. This one is in the 29th percentile – i.e., 29% of its contemporaries scored the same or lower than it.