The paper introduces a new statistical test, Φw, for detecting recombination in genetic sequences. The authors develop this test to address the challenge of identifying recombination, which is a significant evolutionary force that can complicate phylogenetic analyses. They demonstrate through simulations that Φw effectively distinguishes between the presence and absence of recombination, even under diverse conditions such as exponential growth and patterns of substitution rate correlation. Other tests, such as Max χ2, NSS, and coalescent-based likelihood permutation tests, often underestimate recombination under strong population growth and falsely infer recombination under simple models of mutation rate correlation. Empirical data analysis shows that Φw can detect recombination between closely and distantly related samples, regardless of the suspected recombination rate. The results suggest that Φw is one of the best approaches to distinguish recurrent mutation from recombination in various circumstances. The test is also compared with other methods in terms of power, false positives, and computational efficiency, highlighting its advantages in detecting recombination under different conditions.The paper introduces a new statistical test, Φw, for detecting recombination in genetic sequences. The authors develop this test to address the challenge of identifying recombination, which is a significant evolutionary force that can complicate phylogenetic analyses. They demonstrate through simulations that Φw effectively distinguishes between the presence and absence of recombination, even under diverse conditions such as exponential growth and patterns of substitution rate correlation. Other tests, such as Max χ2, NSS, and coalescent-based likelihood permutation tests, often underestimate recombination under strong population growth and falsely infer recombination under simple models of mutation rate correlation. Empirical data analysis shows that Φw can detect recombination between closely and distantly related samples, regardless of the suspected recombination rate. The results suggest that Φw is one of the best approaches to distinguish recurrent mutation from recombination in various circumstances. The test is also compared with other methods in terms of power, false positives, and computational efficiency, highlighting its advantages in detecting recombination under different conditions.