Utility of gene-specific algorithms for predicting pathogenicity of uncertain gene variants

Update item information
Publication Type Manuscript
School or College School of Medicine
Department Ophthalmology
Creator Crockett, David K.
Other Author Lyon, Elaine; Williams, Marc S.; Narus, Scott P.; Facelli, Julio C.; Mitchell, Joyce A.
Title Utility of gene-specific algorithms for predicting pathogenicity of uncertain gene variants
Date 2012
Description The rapid advance of gene sequencing technologies has produced an unprecedented rate of discovery for genome variation in humans. A growing numbered of authoritative clinical repositories archive gene variants and disease phenotype, yet there are currently many more gene variants that lack clear annotation or disease association. To date, there has been very limited coverage of gene-specific predictors in the literature. Here we present the evaluation of ?gene-specific? predictor models based on a Na?ve Bayesian classifier for 20 gene-disease data sets, containing 3,986 variants with clinically characterized patient conditions. Utility of gene-specific prediction is then compared ?all-gene? generalized prediction and also to existing popular predictors. Gene-specific computational prediction models derived from clinically curated gene variant disease data sets often outperform established generalized algorithms for novel and uncertain gene variants.
Type Text
Publisher Elsevier
DOI 10.1136/amiajnl-2011-000309
Language eng
Bibliographic Citation Crockett, D. K., Lyon, E., Williams, M. S., Narus, S. P., Facelli, J. C., & Mitchell, J. A. (2012). Utility of gene-specific algorithms for predicting pathogenicity of uncertain gene variants. Journal of the American Medical Informatics Association, 19(2), 207-11.
Rights Management © Elsevier, Crockett, D. K., Lyon, E., Williams, M. S., Narus, S. P., Facelli, J. C., & Mitchell, J. A. (2012). Utility of gene-specific algorithms for predic0ting pathogenicity of uncertain gene variants. Journal of the American Medical Informatics Association, 19(2), 207-11. http://dx.doi.org/doi:10.1136/amiajnl-2011-000309.
Format Medium application/pdf
Format Extent 1,741,231 bytes
Identifier ir-main,17121
ARK ark:/87278/s6dr3cn1
Setname ir_uspace
Date Created 2012-06-13
Date Modified 2012-06-13
ID 703098
Reference URL https://collections.lib.utah.edu/ark:/87278/s6dr3cn1
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