bioRxiv preprint doi: https://doi.org/10.1101/2021.02.04.429640; this version posted February 6, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license. NeuroSCORE: A Genome-wide Omics-Based Model to Identify Candidate Disease Genes of the Central Nervous System Kyle W. Davis, ScM1, Colleen G. Bilancia, PhD1, Megan Martin, MS1, Rena Vanzo, MS1, Megan Rimmasch1, Yolanda Hom, MS1, Mohammed Uddin, PhD2, Moises Serrano, PhD1 1Bionano Genomics, Lineagen Division, Inc., San Diego, CA, USA 2Mohammed Bin Rashid University of Medicine and Health Sciences, College of Medicine, Dubai, UAE Corresponding Author: Kyle W. Davis, ScM, CGC 9540 Towne Center, Dr. #100 San Diego, CA, 92121
[email protected] 801.931.6189 Co-author email addresses:
[email protected] [email protected] [email protected] [email protected] [email protected] [email protected] [email protected] Key words: bioinformatics, candidate genes, clinical interpretation, gene-disease association, gene scoring model, genomics, neurodevelopment, neurogenetics, omics, variant classification bioRxiv preprint doi: https://doi.org/10.1101/2021.02.04.429640; this version posted February 6, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license. Abstract: To identify and prioritize candidate disease genes of the central nervous system (CNS) we created the Neurogenetic Systematic Correlation of Omics-Related Evidence (NeuroSCORE).