Neutrality Tests for Sequences with Missing Data
Author(s) -
Luca Ferretti,
Emanuele Raineri,
Sebastián E. RamosOnsins
Publication year - 2012
Publication title -
genetics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.792
H-Index - 246
eISSN - 1943-2631
pISSN - 0016-6731
DOI - 10.1534/genetics.112.139949
Subject(s) - estimator , missing data , biology , neutrality , variance (accounting) , statistics , dna microarray , protocol (science) , computational biology , genetics , computer science , mathematics , gene , philosophy , gene expression , accounting , epistemology , business , medicine , alternative medicine , pathology
Missing data are common in DNA sequences obtained through high-throughput sequencing. Furthermore, samples of low quality or problems in the experimental protocol often cause a loss of data even with traditional sequencing technologies. Here we propose modified estimators of variability and neutrality tests that can be naturally applied to sequences with missing data, without the need to remove bases or individuals from the analysis. Modified statistics include the Watterson estimator θW, Tajima's D, Fay and Wu's H, and HKA. We develop a general framework to take missing data into account in frequency spectrum-based neutrality tests and we derive the exact expression for the variance of these statistics under the neutral model. The neutrality tests proposed here can also be used as summary statistics to describe the information contained in other classes of data like DNA microarrays.
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