Open AccessAssessing Genome-Wide Statistical Significance for Large p Small n Problems
Author(s) -
Guoqing Diao,
Anand N. Vidyashankar
Publication year - 2013
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.113.150896
Subject(s) - resampling , genome , biology , statistical significance , genetics , type i and type ii errors , statistical hypothesis testing , computational biology , statistics , gene , mathematics
Assessing genome-wide statistical significance is an important issue in genetic studies. We describe a new resampling approach for determining the appropriate thresholds for statistical significance. Our simulation results demonstrate that the proposed approach accurately controls the genome-wide type I error rate even under the large p small n situations.
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