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Several variations of the Watterson estimator of variability for Next Generation Sequencing (NGS) data have been proposed in the literature. We present a unified framework for generalized Watterson estimators based on Maximum Composite Likelihood, which encompasses most of the existing estimators. We propose this class of unbiased estimators as generalized Watterson estimators for a large class of NGS data, including pools and trios. We also discuss the relation with the estimators proposed in the literature and show that they admit two equivalent but seemingly different forms, deriving a set of combinatorial identities as a byproduct. Finally, we give a detailed treatment of Watterson estimators for single or multiple autopolyploid individuals.

Original publication

DOI

10.1016/j.tpb.2015.01.001

Type

Journal

Theoretical population biology

Publication Date

03/2015

Volume

100C

Pages

79 - 87

Addresses

Systématique, Adaptation et Evolution (UMR 7138), UPMC Univ Paris 06, CNRS, MNHN, IRD, Paris, France; CIRB, Collège de France, Paris, France. Electronic address: luca.ferretti@gmail.com.