Inflated type I error rates when using aggregation methods to analyze rare variants in the 1000 Genomes Project exon sequencing data in unrelated individuals: summary results from Group 7 at Genetic Analysis Workshop 17.

@article{Tintle2011InflatedTI,
  title={Inflated type I error rates when using aggregation methods to analyze rare variants in the 1000 Genomes Project exon sequencing data in unrelated individuals: summary results from Group 7 at Genetic Analysis Workshop 17.},
  author={Nathan L. Tintle and Hugues Aschard and Inchi Hu and Nora L Nock and Haitian Wang and Elizabeth W. Pugh},
  journal={Genetic epidemiology},
  year={2011},
  volume={35 Suppl 1},
  pages={S56-60}
}
As part of Genetic Analysis Workshop 17 (GAW17), our group considered the application of novel and standard approaches to the analysis of genotype-phenotype association in next-generation sequencing data. Our group identified a major issue in the analysis of the GAW17 next-generation sequencing data: type I error and false-positive report probability rates higher than those expected based on empirical type I error levels (as high as 90%). Two main causes emerged: population stratification and… CONTINUE READING

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