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Cladograms with Path to Event (ClaPTE): a novel algorithm to detect associations between genotypes or phenotypes

Samuel K Handelman¹, Jacob M Aaronson², Michal Seweryn³

¹Department of Pharmacology, Ohio State University College of Medicine, 5072 Graves Hall, 333 West 10th Avenue, Columbus, OH 43210, United States; Mathematical Biosciences Institute, The Ohio State University, Jennings Hall 3rd Floor, 1735 Neil Avenue, Columbus, OH 43210, United States.

Computers in Biology and Medicine

|January 12, 2015

Summary

A new method, Cladograms with Path to Event (ClaPTE), identifies associations between genetic traits and phenotypes while accounting for evolutionary history. ClaPTE offers improved accuracy and error control compared to existing methods for pathogen evolution studies.

Keywords:

Correlated evolution Drug resistance Genetic simulation Genotype-phenotype association HIV evolution Influenza evolution Phylogenetics Protein evolution

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Area of Science:

Evolutionary biology
Genetics
Bioinformatics

Background:

Genotype-phenotype associations reveal pathogen evolution, drug resistance, and transmission dynamics.
Common ancestry can create spurious associations between unrelated traits.
Phylogenetic tree analysis is crucial for understanding these evolutionary relationships.

Purpose of the Study:

To introduce Cladograms with Path to Event (ClaPTE), a novel method for detecting character-pair associations.
To adjust for common ancestry when identifying genotype-phenotype relationships.
To compare ClaPTE's performance against existing phylogenetic association methods.

Main Methods:

ClaPTE identifies character-pairs exhibiting co-evolutionary patterns on phylogenetic trees.
The method was evaluated using simulations on gene trees (HIV Env, HIV promoter, bacterial DnaJ, GuaB) and case studies (Influenza/Oseltamavir resistance, DnaJ, GuaB).
Performance was assessed by comparing ClaPTE to independent contrasts, mixed models, and likelihood ratio tests, focusing on type I and type II error rates.

Main Results:

ClaPTE demonstrates competitive sensitivity and superior type I error control compared to existing methods.
In the Influenza case study, ClaPTE identified associations between adjacent amino acid positions missed by other methods.
For DnaJ and GuaB, ClaPTE found more associations within protein families than between them, aligning with biological expectations.

Conclusions:

ClaPTE is a robust method for detecting biologically plausible genotype-phenotype associations.
The method effectively corrects for common ancestry, providing more reliable insights into pathogen evolution.
ClaPTE offers an advancement in analyzing complex evolutionary relationships in molecular data.