Assessing the performance of in silico methods for predicting the pathogenicity of variants in the gene CHEK2, among Hispanic females with breast cancer

The availability of disease‐specific genomic data is critical for developing new computational methods that predict the pathogenicity of human variants and advance the field of precision medicine. However, the lack of gold standards to properly train and benchmark such methods is one of the greatest...

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Veröffentlicht in:	Human mutation 2019-09, Vol.40 (9), p.1612-1622
Hauptverfasser:	Voskanian, Alin, Katsonis, Panagiotis, Lichtarge, Olivier, Pejaver, Vikas, Radivojac, Predrag, Mooney, Sean D., Capriotti, Emidio, Bromberg, Yana, Wang, Yanran, Miller, Max, Martelli, Pier Luigi, Savojardo, Castrense, Babbi, Giulia, Casadio, Rita, Cao, Yue, Sun, Yuanfei, Shen, Yang, Garg, Aditi, Pal, Debnath, Yu, Yao, Huff, Chad D., Tavtigian, Sean V., Young, Erin, Neuhausen, Susan L., Ziv, Elad, Pal, Lipika R., Andreoletti, Gaia, Brenner, Steven E., Kann, Maricel G.
Format:	Artikel
Sprache:	eng
Schlagworte:	Adult Aged Breast cancer Breast Neoplasms - ethnology Breast Neoplasms - genetics CAGI Case-Control Studies Checkpoint Kinase 2 - genetics CHEK2 CHK2 protein Computational Biology - methods Computer applications Computer Simulation Female Generalized linear models Genetic Predisposition to Disease Genomes Hispanic Americans - genetics Hispanic women Humans Kinases Linear Models Middle Aged Pathogenicity Polymorphism, Single Nucleotide Precision medicine SNV United States - ethnology Whole Exome Sequencing
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