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X Demographics
Mendeley readers
Attention Score in Context
| Chapter title |
Genome-Wide Association Analysis Using R
|
|---|---|
| Chapter number | 14 |
| Book title |
Oat
|
| Published in |
Methods in molecular biology, January 2017
|
| DOI | 10.1007/978-1-4939-6682-0_14 |
| Pubmed ID | |
| Book ISBNs |
978-1-4939-6680-6, 978-1-4939-6682-0
|
| Authors |
Julio Isidro-Sánchez, Deniz Akdemir, Gracia Montilla-Bascón |
| Editors |
Sebastian Gasparis |
| Abstract |
This chapter provides a practical overview of the statistical analysis using R [1] and genotype by sequencing (GBS) markers for genome-wide association studies (GWAS) in oats. Statistical analysis is performed by R package rrBLUP [2] and issues associated with the analysis are addressed along with the R code. The ultimate aim of this chapter is to provide a practical guideline to do GWAS analysis using R, rather than describe the theory in depth. For more details about the subject, readers are referred to the excellent resource book in GWAS [3]. A basic programming experience in R is assumed. |
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 % |
|---|---|---|
| United Kingdom | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 108 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | <1% |
| United States | 1 | <1% |
| Unknown | 106 | 98% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 22 | 20% |
| Student > Master | 14 | 13% |
| Researcher | 13 | 12% |
| Student > Bachelor | 10 | 9% |
| Student > Postgraduate | 6 | 6% |
| Other | 12 | 11% |
| Unknown | 31 | 29% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 40 | 37% |
| Biochemistry, Genetics and Molecular Biology | 23 | 21% |
| Mathematics | 4 | 4% |
| Medicine and Dentistry | 2 | 2% |
| Pharmacology, Toxicology and Pharmaceutical Science | 1 | <1% |
| Other | 7 | 6% |
| Unknown | 31 | 29% |
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 17 November 2020.
All research outputs
#18,530,362
of 22,952,268 outputs
Outputs from Methods in molecular biology
#7,935
of 13,137 outputs
Outputs of similar age
#311,015
of 420,594 outputs
Outputs of similar age from Methods in molecular biology
#733
of 1,155 outputs
Altmetric has tracked 22,952,268 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,137 research outputs from this source. They receive a mean Attention Score of 3.4. This one is in the 24th percentile – i.e., 24% of its peers scored the same or lower than it.
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We're also able to compare this research output to 1,155 others from the same source and published within six weeks on either side of this one. This one is in the 21st percentile – i.e., 21% of its contemporaries scored the same or lower than it.