OBJECTIVE: The use of haplotypes to impute the genotypes of unmeasured single nucleotide variants continues to rise in popularity. Simulation results suggest that the use of the dosage as a one-dimensional summary statistic of imputation posterior probabilities may be optimal both in terms of statistical power and computational efficiency; however, little theoretical understanding is available to explain and unify these simulation results. In our analysis, we provide a theoretical foundation for the use of the dosage as a one-dimensional summary statistic of genotype posterior probabilities from any technology. METHODS: We analytically evaluate the dosage, mode and the more general set of all one-dimensional summary statistics of two-dimensional (three posterior probabilities that must sum to 1) genotype posterior probability vectors. RESULTS: We prove that the dosage is an optimal one-dimensional summary statistic under a typical linear disease model and is robust to violations of this model. Simulation results confirm our theoretical findings. CONCLUSIONS: Our analysis provides a strong theoretical basis for the use of the dosage as a one-dimensional summary statistic of genotype posterior probability vectors in related tests of genetic association across a wide variety of genetic disease models.
OBJECTIVE: The use of haplotypes to impute the genotypes of unmeasured single nucleotide variants continues to rise in popularity. Simulation results suggest that the use of the dosage as a one-dimensional summary statistic of imputation posterior probabilities may be optimal both in terms of statistical power and computational efficiency; however, little theoretical understanding is available to explain and unify these simulation results. In our analysis, we provide a theoretical foundation for the use of the dosage as a one-dimensional summary statistic of genotype posterior probabilities from any technology. METHODS: We analytically evaluate the dosage, mode and the more general set of all one-dimensional summary statistics of two-dimensional (three posterior probabilities that must sum to 1) genotype posterior probability vectors. RESULTS: We prove that the dosage is an optimal one-dimensional summary statistic under a typical linear disease model and is robust to violations of this model. Simulation results confirm our theoretical findings. CONCLUSIONS: Our analysis provides a strong theoretical basis for the use of the dosage as a one-dimensional summary statistic of genotype posterior probability vectors in related tests of genetic association across a wide variety of genetic disease models.
Authors: Jeffrey C Barrett; Sarah Hansoul; Dan L Nicolae; Judy H Cho; Richard H Duerr; John D Rioux; Steven R Brant; Mark S Silverberg; Kent D Taylor; M Michael Barmada; Alain Bitton; Themistocles Dassopoulos; Lisa Wu Datta; Todd Green; Anne M Griffiths; Emily O Kistner; Michael T Murtha; Miguel D Regueiro; Jerome I Rotter; L Philip Schumm; A Hillary Steinhart; Stephan R Targan; Ramnik J Xavier; Cécile Libioulle; Cynthia Sandor; Mark Lathrop; Jacques Belaiche; Olivier Dewit; Ivo Gut; Simon Heath; Debby Laukens; Myriam Mni; Paul Rutgeerts; André Van Gossum; Diana Zelenika; Denis Franchimont; Jean-Pierre Hugot; Martine de Vos; Severine Vermeire; Edouard Louis; Lon R Cardon; Carl A Anderson; Hazel Drummond; Elaine Nimmo; Tariq Ahmad; Natalie J Prescott; Clive M Onnie; Sheila A Fisher; Jonathan Marchini; Jilur Ghori; Suzannah Bumpstead; Rhian Gwilliam; Mark Tremelling; Panos Deloukas; John Mansfield; Derek Jewell; Jack Satsangi; Christopher G Mathew; Miles Parkes; Michel Georges; Mark J Daly Journal: Nat Genet Date: 2008-06-29 Impact factor: 38.330
Authors: David M Altshuler; Richard A Gibbs; Leena Peltonen; David M Altshuler; Richard A Gibbs; Leena Peltonen; Emmanouil Dermitzakis; Stephen F Schaffner; Fuli Yu; Leena Peltonen; Emmanouil Dermitzakis; Penelope E Bonnen; David M Altshuler; Richard A Gibbs; Paul I W de Bakker; Panos Deloukas; Stacey B Gabriel; Rhian Gwilliam; Sarah Hunt; Michael Inouye; Xiaoming Jia; Aarno Palotie; Melissa Parkin; Pamela Whittaker; Fuli Yu; Kyle Chang; Alicia Hawes; Lora R Lewis; Yanru Ren; David Wheeler; Richard A Gibbs; Donna Marie Muzny; Chris Barnes; Katayoon Darvishi; Matthew Hurles; Joshua M Korn; Kati Kristiansson; Charles Lee; Steven A McCarrol; James Nemesh; Emmanouil Dermitzakis; Alon Keinan; Stephen B Montgomery; Samuela Pollack; Alkes L Price; Nicole Soranzo; Penelope E Bonnen; Richard A Gibbs; Claudia Gonzaga-Jauregui; Alon Keinan; Alkes L Price; Fuli Yu; Verneri Anttila; Wendy Brodeur; Mark J Daly; Stephen Leslie; Gil McVean; Loukas Moutsianas; Huy Nguyen; Stephen F Schaffner; Qingrun Zhang; Mohammed J R Ghori; Ralph McGinnis; William McLaren; Samuela Pollack; Alkes L Price; Stephen F Schaffner; Fumihiko Takeuchi; Sharon R Grossman; Ilya Shlyakhter; Elizabeth B Hostetter; Pardis C Sabeti; Clement A Adebamowo; Morris W Foster; Deborah R Gordon; Julio Licinio; Maria Cristina Manca; Patricia A Marshall; Ichiro Matsuda; Duncan Ngare; Vivian Ota Wang; Deepa Reddy; Charles N Rotimi; Charmaine D Royal; Richard R Sharp; Changqing Zeng; Lisa D Brooks; Jean E McEwen Journal: Nature Date: 2010-09-02 Impact factor: 49.962
Authors: Gonçalo R Abecasis; David Altshuler; Adam Auton; Lisa D Brooks; Richard M Durbin; Richard A Gibbs; Matt E Hurles; Gil A McVean Journal: Nature Date: 2010-10-28 Impact factor: 49.962
Authors: P F Sullivan; E J C de Geus; G Willemsen; M R James; J H Smit; T Zandbelt; V Arolt; B T Baune; D Blackwood; S Cichon; W L Coventry; K Domschke; A Farmer; M Fava; S D Gordon; Q He; A C Heath; P Heutink; F Holsboer; W J Hoogendijk; J J Hottenga; Y Hu; M Kohli; D Lin; S Lucae; D J Macintyre; W Maier; K A McGhee; P McGuffin; G W Montgomery; W J Muir; W A Nolen; M M Nöthen; R H Perlis; K Pirlo; D Posthuma; M Rietschel; P Rizzu; A Schosser; A B Smit; J W Smoller; J-Y Tzeng; R van Dyck; M Verhage; F G Zitman; N G Martin; N R Wray; D I Boomsma; B W J H Penninx Journal: Mol Psychiatry Date: 2008-12-09 Impact factor: 15.992
Authors: Dana B Hancock; Nathan C Gaddis; Joshua L Levy; Laura J Bierut; Alex H Kral; Eric O Johnson Journal: AIDS Date: 2015-04-24 Impact factor: 4.177