Open AccessPost hoc Analysis for Detecting Individual Rare Variant Risk Associations Using Probit Regression Bayesian Variable Selection Methods in Case-Control Sequencing Studies
Author(s) -
Nicholas B. Larson,
Shan K. McDonnell,
Lisa Can Albright,
Craig C. Teerlink,
Janet L. Stanford,
Elaine A. Ostrander,
William B. Isaacs,
Jianfeng Xu,
Kathleen A. Cooney,
Ethan M. Lange,
Johanna Schleutker,
John D. Carpten,
Isaac J. Powell,
Joan E. Bailey-Wilson,
Olivier Cussenot,
Géraldine CancelTassin,
Graham G. Giles,
Robert J. MacInnis,
Christiane Maier,
Alice S. Whittemore,
ChihLin Hsieh,
Fredrik Wiklund,
William J. Catolona,
William D. Foulkes,
Diptasri Mandal,
Rosalind Eeles,
Zsofia Kóte-Jarai,
Michael J. Ackerman,
Timothy M. Olson,
Christopher J. Klein,
Stephen N. Thibodeau,
Daniel J. Schaid
Publication year - 2016
Publication title -
carolina digital repository (university of north carolina at chapel hill)
Language(s) - English
DOI - 10.17615/azx9-qr47
Subject(s) - probit model , bayesian probability , feature selection , selection (genetic algorithm) , econometrics , computer science , statistics , regression , regression analysis , post hoc , artificial intelligence , machine learning , mathematics , medicine