Human whole-exome genotype data for Alzheimer’s disease

Yuk Yee Leung, Adam C. Naj, Yi Fan Chou, Otto Valladares, Michael Schmidt, Kara Hamilton-Nelson, Nicholas Wheeler, Honghuang Lin, Prabhakaran Gangadharan, Liming Qu, Kaylyn Clark, Amanda B. Kuzma, Wan Ping Lee, Laura Cantwell, Heather Nicaretta, Sven van der Lee, Adam English, Divya Kalra, Donna Muzny, Evette SkinnerHarsha Doddapeneni, Huyen Dinh, Jianhong Hu, Jireh Santibanez, Joy Jayaseelan, Kim Worley, Richard A. Gibbs, Sandra Lee, Shannon Dugan-Perez, Viktoriya Korchina, Waleed Nasser, Xiuping Liu, Yi Han, Yiming Zhu, Yue Liu, Ziad Khan, Congcong Zhu, Fangui Jenny Sun, Gyungah R. Jun, Jaeyoon Chung, John Farrell, Xiaoling Zhang, Eric Banks, Namrata Gupta, Stacey Gabriel, Mariusz Butkiewicz, Penelope Benchek, Sandra Smieszek, Yeunjoo Song, Badri Vardarajan, Christiane Reitz, Dolly Reyes-Dumeyer, Giuseppe Tosto, Phillip L. De Jager, Sandra Barral, Yiyi Ma, Alexa Beiser, Ching Ti Liu, Josee Dupuis, Kathy Lunetta, L. Adrienne Cupples, Seung Hoan Choi, Yuning Chen, Jesse Mez, Ashley Vanderspek, M. Arfan Ikram, Shahzad Ahmad, Kelley Faber, Tatiana Foroud, Elisabeth Mlynarski, Helena Schmidt, Reinhold Schmidt, Brian Kunkle, Farid Rajabli, Gary Beecham, Jeffrey M. Vance, Larry D. Adams, Michael Cuccaro, Pedro Mena, Briana M. Booth, Alan Renton, Alison Goate, Edoardo Marcora, Adam Stine, Michael Feolo, Lenore J. Launer, Daniel C. Koboldt, Richard K. Wilson, Cornelia van Duijn, Najaf Amin, Manav Kapoor, William Salerno, David A. Bennett, Li Charlie Xia, John Malamon, Thomas H. Mosley, Claudia Satizabal, Bressler Jan Bressler, Xueqiu Jian, Alejandro Q. Nato, Andrea R. Horimoto, Bowen Wang, Bruce Psaty, Daniela Witten, Debby Tsuang, Elizabeth Blue, Ellen Wijsman, Harkirat Sohi, Hiep Nguyen, Joshua C. Bis, Kenneth Rice, Lisa Brown, Michael Dorschner, Mohamad Saad, Pat Navas, Rafael Nafikov, Timothy Thornton, Tyler Day, Jacob Haut, Jin Sha, Nancy Zhang, Taha Iqbal, Yi Zhao, Jennifer E. Below, David E. Larson, Elizabeth Appelbaum, Jason Waligorski, Lucinda Antonacci-Fulton, Robert S. Fulton, Jonathan Haines, Lindsay Farrer, Sudha Seshadri, Zoran Brkanac, Carlos Cruchaga, Margaret Pericak-Vance, Richard P. Mayeux, William S. Bush, Anita Destefano, Eden Martin, Gerard D. Schellenberg, Li San Wang

Research output: Contribution to journalArticlepeer-review

Abstract

The heterogeneity of the whole-exome sequencing (WES) data generation methods present a challenge to a joint analysis. Here we present a bioinformatics strategy for joint-calling 20,504 WES samples collected across nine studies and sequenced using ten capture kits in fourteen sequencing centers in the Alzheimer’s Disease Sequencing Project. The joint-genotype called variant-called format (VCF) file contains only positions within the union of capture kits. The VCF was then processed specifically to account for the batch effects arising from the use of different capture kits from different studies. We identified 8.2 million autosomal variants. 96.82% of the variants are high-quality, and are located in 28,579 Ensembl transcripts. 41% of the variants are intronic and 1.8% of the variants are with CADD > 30, indicating they are of high predicted pathogenicity. Here we show our new strategy can generate high-quality data from processing these diversely generated WES samples. The improved ability to combine data sequenced in different batches benefits the whole genomics research community.

Original languageEnglish
Article number684
JournalNature Communications
Volume15
Issue number1
DOIs
StatePublished - Dec 2024

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