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.
X Demographics
Mendeley readers
Attention Score in Context
| Chapter title |
Detecting Pedigree Relationship Errors
|
|---|---|
| Chapter number | 3 |
| Book title |
Statistical Human Genetics
|
| Published in |
Methods in molecular biology, January 2017
|
| DOI | 10.1007/978-1-4939-7274-6_3 |
| Pubmed ID | |
| Book ISBNs |
978-1-4939-7273-9, 978-1-4939-7274-6
|
| Authors |
Lei Sun |
| Abstract |
Pedigree relationship errors often occur in family data collected for genetic studies, and unidentified errors can lead to either increased false positives or decreased power in both linkage and association analyses. Here, we review several allele sharing as well as likelihood-based statistics that were proposed to efficiently extract genealogical information from available genome-wide marker data, and the software package PREST that implements these methods. We provide the detailed analytical steps involved using two application examples, and we discuss various practical issues, including result interpretation. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 5 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 5 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 1 | 20% |
| Student > Bachelor | 1 | 20% |
| Student > Doctoral Student | 1 | 20% |
| Unknown | 2 | 40% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 2 | 40% |
| Agricultural and Biological Sciences | 1 | 20% |
| Unknown | 2 | 40% |
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 06 October 2017.
All research outputs
#20,449,496
of 23,005,189 outputs
Outputs from Methods in molecular biology
#9,941
of 13,159 outputs
Outputs of similar age
#356,165
of 421,224 outputs
Outputs of similar age from Methods in molecular biology
#842
of 1,074 outputs
Altmetric has tracked 23,005,189 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,159 research outputs from this source. They receive a mean Attention Score of 3.4. This one is in the 1st percentile – i.e., 1% 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 421,224 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1,074 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.