@article{Sun01052016,
author = {Sun, Song and Yang, Fan and Tan, Guihong and Costanzo, Michael and Oughtred, Rose and Hirschman, Jodi and Theesfeld, Chandra L. and Bansal, Pritpal and Sahni, Nidhi and Yi, Song and Yu, Analyn and Tyagi, Tanya and Tie, Cathy and Hill, David E. and Vidal, Marc and Andrews, Brenda J. and Boone, Charles and Dolinski, Kara and Roth, Frederick P.}, 
title = {An extended set of yeast-based functional assays accurately identifies human disease mutations},
volume = {26}, 
number = {5}, 
pages = {670-680}, 
year = {2016}, 
doi = {10.1101/gr.192526.115}, 
abstract ={We can now routinely identify coding variants within individual human genomes. A pressing challenge is to determine which variants disrupt the function of disease-associated genes. Both experimental and computational methods exist to predict pathogenicity of human genetic variation. However, a systematic performance comparison between them has been lacking. Therefore, we developed and exploited a panel of 26 yeast-based functional complementation assays to measure the impact of 179 variants (101 disease- and 78 non-disease-associated variants) from 22 human disease genes. Using the resulting reference standard, we show that experimental functional assays in a 1-billion-year diverged model organism can identify pathogenic alleles with significantly higher precision and specificity than current computational methods.}, 
URL = {http://genome.cshlp.org/content/26/5/670.abstract}, 
eprint = {http://genome.cshlp.org/content/26/5/670.full.pdf+html}, 
journal = {Genome Research} 
}