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ParentChecker: a computer program for automated inference of missing parental genotype calls and linkage phase correction

Overview of attention for article published in BMC Genomic Data, February 2012
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Title
ParentChecker: a computer program for automated inference of missing parental genotype calls and linkage phase correction
Published in
BMC Genomic Data, February 2012
DOI 10.1186/1471-2156-13-9
Pubmed ID
Authors

Zhiqiu Hu, Jeffrey D Ehlers, Philip A Roberts, Timothy J Close, Mitchell R Lucas, Steve Wanamaker, Shizhong Xu

Abstract

Accurate genetic maps are the cornerstones of genetic discovery, but their construction can be hampered by missing parental genotype information. Inference of parental haplotypes and correction of phase errors can be done manually on a one by one basis with the aide of current software tools, but this is tedious and time consuming for the high marker density datasets currently being generated for many crop species. Tools that help automate the process of inferring parental genotypes can greatly speed the process of map building. We developed a software tool that infers and outputs missing parental genotype information based on observed patterns of segregation in mapping populations. When phases are correctly inferred, they can be fed back to the mapping software to quickly improve marker order and placement on genetic maps.

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

Mendeley readers

The data shown below were compiled from readership statistics for 37 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 1 3%
United States 1 3%
Unknown 35 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 14 38%
Researcher 14 38%
Professor 2 5%
Lecturer > Senior Lecturer 1 3%
Other 1 3%
Other 1 3%
Unknown 4 11%
Readers by discipline Count As %
Agricultural and Biological Sciences 31 84%
Biochemistry, Genetics and Molecular Biology 1 3%
Mathematics 1 3%
Unknown 4 11%
Attention Score in Context

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 12 March 2012.
All research outputs
#19,945,185
of 25,374,917 outputs
Outputs from BMC Genomic Data
#786
of 1,204 outputs
Outputs of similar age
#129,002
of 169,012 outputs
Outputs of similar age from BMC Genomic Data
#11
of 21 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. This one is in the 18th percentile – i.e., 18% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,204 research outputs from this source. They receive a mean Attention Score of 4.3. This one is in the 28th percentile – i.e., 28% 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 169,012 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 21st percentile – i.e., 21% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 21 others from the same source and published within six weeks on either side of this one. This one is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.