Network-based pathogenicity prediction for variants of uncertain significance
Mayumi Kamada, Atsuko Takagi, Ryosuke Kojima, Yoshihisa Tanaka, Masahiko Nakatsui, Noriko Tanabe, Makoto Hirata, Teruhiko Yoshida, Yasushi Okuno
This paper introduces PathoGN, a network-based method for predicting variant pathogenicity, which outperforms existing methods and identifies pathogenicity for 3,994 variants of uncertain significance.
bioRxiv · Jul 15, 2021 · PreprintGenomics