↓ Skip to main content

Identity-by-descent refines mapping of candidate regions for preaxial polydactyly II /III in a large Chinese pedigree

Overview of attention for article published in Hereditas, July 2017
Altmetric Badge

Mentioned by

twitter
2 X users

Readers on

mendeley
9 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Identity-by-descent refines mapping of candidate regions for preaxial polydactyly II /III in a large Chinese pedigree
Published in
Hereditas, July 2017
DOI 10.1186/s41065-017-0040-6
Pubmed ID
Authors

Xingyan Yang, Quankuan Shen, Xierzhatijiang Sulaiman, Hequn Liu, Minsheng Peng, Yaping Zhang

Abstract

Preaxial polydactyly (PPD) is congenital hand malformation characterized by the duplication of digit. Herein, we scan the genome-wide SNPs for a large Chinese family with PPD-II/III. We employ the refined IBD algorithm to identify the identity-by-decent (IBD) segments and compare the frequency among the patients and normal relatives. A total of 72 markers of 0.01 percentile of the permutation are identified as the peak signals. Among of them, 57markers locate on chromosome 7q36 which is associated with PPD. Further analyses refine the mapping of candidate region in chromosome 7q36 into two 380 Kb fragments within LMBR1 and SHH respectively. IBD approach is a suitable method for mapping causal gene of human disease. Target-enrichment sequencing as well as functional experiments are required to illustrate the pathogenic mechanisms for PPD in the future.

X Demographics

X Demographics

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 9 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 9 100%

Demographic breakdown

Readers by professional status Count As %
Librarian 1 11%
Lecturer 1 11%
Professor 1 11%
Student > Ph. D. Student 1 11%
Student > Master 1 11%
Other 2 22%
Unknown 2 22%
Readers by discipline Count As %
Medicine and Dentistry 6 67%
Physics and Astronomy 1 11%
Immunology and Microbiology 1 11%
Unknown 1 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 21 July 2017.
All research outputs
#20,660,571
of 25,382,440 outputs
Outputs from Hereditas
#398
of 513 outputs
Outputs of similar age
#251,741
of 326,157 outputs
Outputs of similar age from Hereditas
#4
of 6 outputs
Altmetric has tracked 25,382,440 research outputs across all sources so far. This one is in the 10th percentile – i.e., 10% of other outputs scored the same or lower than it.
So far Altmetric has tracked 513 research outputs from this source. They receive a mean Attention Score of 4.0. This one is in the 13th percentile – i.e., 13% 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 326,157 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 12th percentile – i.e., 12% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 6 others from the same source and published within six weeks on either side of this one. This one has scored higher than 2 of them.