Integrated analysis of genomic and transcriptomic data for the discovery of splice-associated variants in cancer

Authors

• Kelsy C Cotto, Washington University School of Medicine in St. Louis
• Yang-Yang Feng, Washington University School of Medicine in St. Louis
• Avinash Ramu, Washington University School of Medicine in St. Louis
• Megan Richters, Washington University School of Medicine in St. Louis
• Sharon L Freshour, Washington University School of Medicine in St. Louis
• Zachary L Skidmore, Washington University School of Medicine in St. Louis
• Huiming Xia, Washington University School of Medicine in St. Louis
• Joshua F McMichael, Washington University School of Medicine in St. Louis
• Jason Kunisaki, Washington University School of Medicine in St. Louis
• Katie M Campbell, Washington University School of Medicine in St. Louis
• Timothy Hung-Po Chen, Washington University School of Medicine in St. Louis
• Emily B Rozycki, Washington University School of Medicine in St. Louis
• Douglas Adkins, Washington University School of Medicine in St. Louis
• Siddhartha Devarakonda, Washington University School of Medicine in St. Louis
• Sumithra Sankararaman, Washington University School of Medicine in St. Louis
• Yiing Lin, Washington University School of Medicine in St. Louis
• William C Chapman, Washington University School of Medicine in St. Louis
• Christopher A Maher, Washington University School of Medicine in St. Louis
• Vivek Arora, Washington University School of Medicine in St. Louis
• Ramaswamy Govindan, Washington University School of Medicine in St. Louis
• Obi L Griffith, Washington University School of Medicine in St. Louis
• Malachi Griffith, Washington University School of Medicine in St. Louis
• et al.

Journal

Nature Communications

Publication Date

3-22-2023

Volume

14

Issue

1

First Page

1589

Document Type

Open Access Publication

DOI

10.1038/s41467-023-37266-6

Rights and Permissions

Cotto, K.C., Feng, YY., Ramu, A. et al. Integrated analysis of genomic and transcriptomic data for the discovery of splice-associated variants in cancer. Nat Commun 14, 1589 (2023). https://doi.org/10.1038/s41467-023-37266-6 This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

Recommended Citation

Cotto, Kelsy C; Feng, Yang-Yang; Ramu, Avinash; Richters, Megan; Freshour, Sharon L; Skidmore, Zachary L; Xia, Huiming; McMichael, Joshua F; Kunisaki, Jason; Campbell, Katie M; Chen, Timothy Hung-Po; Rozycki, Emily B; Adkins, Douglas; Devarakonda, Siddhartha; Sankararaman, Sumithra; Lin, Yiing; Chapman, William C; Maher, Christopher A; Arora, Vivek; Govindan, Ramaswamy; Griffith, Obi L; Griffith, Malachi; and et al., "Integrated analysis of genomic and transcriptomic data for the discovery of splice-associated variants in cancer." Nature Communications. 14, 1. 1589 (2023).
https://digitalcommons.wustl.edu/oa_4/1478

Department

ICTS (Institute of Clinical and Translational Sciences)

Additional Links

Supplemental material is available for this article at publisher site.