EconPapers    
Economics at your fingertips  
 

Accounting for Dependence in Similarity Data from DNA Fingerprinting

Hepworth Graham, Gordon Ian R and McCullough Michael J
Additional contact information
Hepworth Graham: The University of Melbourne
Gordon Ian R: The University of Melbourne
McCullough Michael J: The University of Melbourne

Statistical Applications in Genetics and Molecular Biology, 2007, vol. 6, issue 1, 1-15

Abstract: Differentiating strains of a pathogen is often central to investigating its epidemiological aspects. The genetic similarity of a group of strains can be assessed by calculating a matrix of dissimilarities from their DNA fingerprinting profiles. The mean dissimilarity for each strain across other strains within the group is then used as an observation in a statistical analysis. These observations are not independent of each other, and so standard analysis techniques such as the t-test are inappropriate, because they underestimate the variance of the group means, and hence overstate the statistical significance of any differences. By examining the correlation between elements of the dissimilarity matrix, it is shown that the variance is underestimated by a factor of between about 2 and 4. Permutation tests are proposed as a way of addressing the problem of dependence, and are applied to a study of fluconazole resistance in Candida albicans.

Date: 2007
References: Add references at CitEc
Citations: Track citations by RSS feed

Downloads: (external link)
https://doi.org/10.2202/1544-6115.1212 (text/html)
For access to full text, subscription to the journal or payment for the individual article is required.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bpj:sagmbi:v:6:y:2007:i:1:n:1

Ordering information: This journal article can be ordered from
https://www.degruyter.com/view/j/sagmb

DOI: 10.2202/1544-6115.1212

Access Statistics for this article

Statistical Applications in Genetics and Molecular Biology is currently edited by Michael P. H. Stumpf

More articles in Statistical Applications in Genetics and Molecular Biology from De Gruyter
Bibliographic data for series maintained by Peter Golla ().

 
Page updated 2021-05-07
Handle: RePEc:bpj:sagmbi:v:6:y:2007:i:1:n:1