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High type I error and misrepresentations in search for transgenerational epigenetic inheritance: response to Guerrero-Bosagna

Overview of attention for article published in Genome Biology, July 2016
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Title
High type I error and misrepresentations in search for transgenerational epigenetic inheritance: response to Guerrero-Bosagna
Published in
Genome Biology, July 2016
DOI 10.1186/s13059-016-0981-5
Pubmed ID
Authors

Khursheed Iqbal, Diana A. Tran, Arthur X. Li, Charles Warden, Angela Y. Bai, Purnima Singh, Zach B. Madaj, Mary E. Winn, Xiwei Wu, Gerd P. Pfeifer, Piroska E. Szabó

Abstract

In a recent paper, we described our efforts in search for evidence supporting epigenetic transgenerational inheritance caused by endocrine disrupter chemicals. One aspect of our study was to compare genome-wide DNA methylation changes in the vinclozolin-exposed fetal male germ cells (n = 3) to control samples (n = 3), their counterparts in the next, unexposed, generation (n = 3 + 3) and also in adult spermatozoa (n = 2 + 2) in both generations. We reported finding zero common hits in the intersection of these four comparisons. In our interpretation, this result did not support the notion that DNA methylation provides a mechanism for a vinclozolin-induced transgenerational male infertility phenotype. In response to criticism by Guerrero-Bosagna regarding our statistical power in the above study, here we provide power calculations to clarify the statistical power of our study and to show the validity of our conclusions. We also explain here how our data is misinterpreted in the commentary by Guerrero-Bosagna by leaving out important data points from consideration.Please see related Correspondence article: xxx (13059_2016_982) and related Research article: http://genomebiology.biomedcentral.com/articles/10.1186/s13059-015-0619-z.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 25 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 4%
United States 1 4%
Unknown 23 92%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 6 24%
Researcher 5 20%
Other 2 8%
Student > Master 2 8%
Student > Doctoral Student 1 4%
Other 5 20%
Unknown 4 16%
Readers by discipline Count As %
Agricultural and Biological Sciences 7 28%
Biochemistry, Genetics and Molecular Biology 5 20%
Computer Science 2 8%
Medicine and Dentistry 2 8%
Nursing and Health Professions 2 8%
Other 3 12%
Unknown 4 16%
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 16 July 2016.
All research outputs
#19,942,887
of 25,371,288 outputs
Outputs from Genome Biology
#4,233
of 4,467 outputs
Outputs of similar age
#272,323
of 370,095 outputs
Outputs of similar age from Genome Biology
#56
of 63 outputs
Altmetric has tracked 25,371,288 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 4,467 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.6. This one is in the 4th percentile – i.e., 4% of its peers scored the same or lower than it.
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We're also able to compare this research output to 63 others from the same source and published within six weeks on either side of this one. This one is in the 9th percentile – i.e., 9% of its contemporaries scored the same or lower than it.