Haplotype-resolved diverse human genomes and integrated analysis of structural variation.
P Ebert, PA Audano, Q Zhu, B Rodriguez-Martin, D Porubsky, MJ Bonder, A Sulovari, J Ebler, W Zhou, R Serra Mari, F Yilmaz, X Zhao, P Hsieh, J Lee, S Kumar, J Lin, T Rausch, Y Chen, J Ren, M Santamarina, W Hops, H Ashraf, NT Chuang, X Yang, KM Munson, AP Lewis, S Fairley, LJ Tallon, WE Clarke, AO Basile, M Byrska-Bishop, A Corvelo, US Evani, TY Lu, MJP Chaisson, J Chen, C Li, H Brand, AM Wenger, M Ghareghani, WT Harvey, B Raeder, P Hasenfeld, AA Regier, HJ Abel, IM Hall, P Flicek, O Stegle, MB Gerstein, JMC Tubio, Z Mu, YI Li, X Shi, AR Hastie, K Ye, Z Chong, AD Sanders, MC Zody, ME Talkowski, RE Mills, SE Devine, C Lee, JO Korbel, T Marschall, EE Eichler (2021). Science 372.

Expectations and blind spots for structural variation detection from long-read assemblies and short-read genome sequencing technologies.
X Zhao, RL Collins, WP Lee, AM Weber, Y Jun, Q Zhu, B Weisburd, Y Huang, PA Audano, H Wang, M Walker, C Lowther, J Fu, Human Genome Structural Variation Consortium, MB Gerstein, SE Devine, T Marschall, JO Korbel, EE Eichler, MJP Chaisson, C Lee, RE Mills, H Brand, ME Talkowski (2021). Am J Hum Genet 108: 919-928.

SVFX: a machine learning framework to quantify the pathogenicity of structural variants.
S Kumar, A Harmanci, J Vytheeswaran, MB Gerstein (2020). Genome Biol 21: 274.


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