Accounting for Bias from Sequencing Error in Population Genetic Estimates
作者： P. L. F. Johnson , M. Slatkin
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摘要: Sequencing error presents a significant challenge to population genetic analyses using low-coverage sequence in general and single-pass reads particular. Bias parameter estimates becomes severe when the level of polymorphism (signal) is low relative amount (noise). Choosing an arbitrary quality score cutoff yields biased estimates, particularly with newer, non-Sanger sequencing technologies that have different distributions. We propose rule thumb judge given threshold will lead bias suggest alternative approaches reduce bias.
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