Estimating genotype error rates from high-coverage next-generation sequence data.

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Published in Genome Res on October 10, 2014

Authors

Jeffrey D Wall1, Ling Fung Tang2, Brandon Zerbe3, Mark N Kvale3, Pui-Yan Kwok4, Catherine Schaefer5, Neil Risch6

Author Affiliations

1: Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, California 94143, USA; Institute for Human Genetics, University of California San Francisco, San Francisco, California 94143, USA; wallj@humgen.ucsf.edu.
2: Cardiovascular Research Institute, University of California San Francisco, San Francisco, California 94143, USA;
3: Institute for Human Genetics, University of California San Francisco, San Francisco, California 94143, USA;
4: Institute for Human Genetics, University of California San Francisco, San Francisco, California 94143, USA; Cardiovascular Research Institute, University of California San Francisco, San Francisco, California 94143, USA;
5: Kaiser Permanente Northern California Division of Research, Oakland, California 94612, USA.
6: Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, California 94143, USA; Institute for Human Genetics, University of California San Francisco, San Francisco, California 94143, USA; Kaiser Permanente Northern California Division of Research, Oakland, California 94612, USA.

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