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Article #10heterogeneity (RxC) tests power
From: Ivan Zimogorov
Date: Mon, 04 Nov 1996 00:00
Date: Mon, 04 Nov 1996 00:00
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2051 bytes
Well I came up with a novel way to test heterogeneity of gene frequencies between samples of haploid individuals from several populations (sounds like Karl Pearson, so what? :-)). The question is how to compare other methods (like X^2, Fisher's exact, conditional X^2 etc) with it. I simulated genetic drift by the coalescence process, then sampled from diverged populations, repeated that process many times to get empirical powers for the different degrees of divergence.. Therefore, under the neutral scenario I have an idea how things behave. Now, how do people implement selection? Motoo Kimura's treatment of random intensity selection when there is no dominance, gives U-shaped allele frequency distribution. Is it theoretically valid to generate steady-state distribution of allele frequencies for each population from a Beta(a<1, b<1) density to approximate Kimura's results? What shape should allele frequency profile follow for a non-equilibrium situation? I could not find if there is any theory done for that case. I'd appreciate any references, and hints. Ivan Zimogorov
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X-Google-Language: ENGLISH,ASCII-7-bit X-Google-Thread: f7de2,1d668e08db8d92a0 X-Google-Attributes: gidf7de2,public X-Google-Thread: 10d632,1d668e08db8d92a0 X-Google-Attributes: gid10d632,public X-Google-Thread: 111b91,1d668e08db8d92a0 X-Google-Attributes: gid111b91,public X-Google-Thread: 112c20,1d668e08db8d92a0 X-Google-Attributes: gid112c20,public X-Google-Thread: f732f,a0cd9394a9fd3b9b,start X-Google-Attributes: gidf732f,public X-Google-Thread: 10a7a9,1d668e08db8d92a0 X-Google-Attributes: gid10a7a9,public From: ivan@manifesto.nihonkai.jp (Ivan Zimogorov) Subject: heterogeneity (RxC) tests power Date: 1996/11/04 Message-ID: <6352FR831.6FBV101996@manifesto.Nihonkai.jp> X-Deja-AN: 194170575 supersedes: <554600AXW.0AXX101996@manifesto.Nihonkai.jp> organization: Bacterial Bee Peekers newsgroups: sci.stat.consult,bionet.population-bio,bionet.molbio.evolution,sci.bio.systematics,sci.stat.math,sci.stat.edu