Adjusted likelihood-ratio test for variants with unknown genotypes

2018 ◽  
Vol 16 (05) ◽  
pp. 1840020 ◽  
Author(s):  
Ronald J. Nowling ◽  
Scott J. Emrich
Keyword(s):  
Likelihood Ratio ◽  
Likelihood Ratio Test ◽  
Malaria Vectors ◽  
Similar Species ◽  
Ratio Test ◽  
Anopheles Coluzzii ◽  
Nucleotide Polymorphisms ◽  
Single Nucleotide ◽  
Novel Approach ◽  
Lr Test

Association tests performed with the Likelihood-Ratio Test (LR Test) can be an alternative to [Formula: see text], which is often used in population genetics to find variants of interest. Because the LR Test has several properties that could make it preferable to [Formula: see text], we propose a novel approach for modeling unknown genotypes in highly-similar species. To show the effectiveness of this LR Test approach, we apply it to single-nucleotide polymorphisms (SNPs) associated with the recent speciation of the malaria vectors Anopheles gambiae and Anopheles coluzzii and compare to [Formula: see text].

scholarly journals Detecting Inversions with PCA in the Presence of Population Structure

2019 ◽  
Author(s):  
Ronald J. Nowling ◽  
Krystal R. Manke ◽  
Scott J. Emrich
Keyword(s):  
Simulated Data ◽  
Principal Component ◽  
Real Data ◽  
Malaria Vectors ◽  
Anopheles Coluzzii ◽  
Nucleotide Polymorphisms ◽  
Data Set ◽  
Single Nucleotide ◽  
Closely Related Species ◽  
Proper Analysis

ABSTRACTChromosomal inversions are associated with reproductive isolation and adaptation in insects such as Drosophila melanogaster and the malaria vectors Anopheles gambiae and Anopheles coluzzii. While methods based on read alignment have been useful in humans for detecting inversions, these methods are less successful in insects due to long repeated sequences at the breakpoints. Alternatively, inversions can be detected using principal component analysis (PCA) of single nucleotide polymorphisms (SNPs). We apply PCA-based inversion detection to a simulated data set and real data from multiple insect species, which vary in complexity from a single inversion in samples drawn from a single population to analyzing multiple overlapping inversions occurring in closely-related species, samples of which that were generated from multiple geographic locations. We show empirically that proper analysis of these data can be challenging when multiple inversions or populations are present, and that our alternative framework is more robust in these more difficult scenarios.

A likelihood ratio test for detecting patterns of disease-marker association

1997 ◽  
Vol 61 (4) ◽  
pp. 335-350 ◽  
Author(s):  
A. P. MORRIS ◽  
J. C. WHITTAKER ◽  
R. N. CURNOW
Keyword(s):  
Likelihood Ratio ◽  
Likelihood Ratio Test ◽  
Ratio Test ◽  
Disease Marker

A Likelihood Ratio Test of the Equality of Paired Survival Data with Censoring

1986 ◽  
Vol 28 (6) ◽  
pp. 665-672 ◽  
Author(s):  
R. G. Knapp ◽  
A. J. Gross ◽  
A. B. Cantor
Keyword(s):  
Likelihood Ratio ◽  
Likelihood Ratio Test ◽  
Survival Data ◽  
Ratio Test
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