Nature Communications (Mar 2023)
Integrated analysis of genomic and transcriptomic data for the discovery of splice-associated variants in cancer
- Kelsy C. Cotto,
- Yang-Yang Feng,
- Avinash Ramu,
- Megan Richters,
- Sharon L. Freshour,
- Zachary L. Skidmore,
- Huiming Xia,
- Joshua F. McMichael,
- Jason Kunisaki,
- Katie M. Campbell,
- Timothy Hung-Po Chen,
- Emily B. Rozycki,
- Douglas Adkins,
- Siddhartha Devarakonda,
- Sumithra Sankararaman,
- Yiing Lin,
- William C. Chapman,
- Christopher A. Maher,
- Vivek Arora,
- Gavin P. Dunn,
- Ravindra Uppaluri,
- Ramaswamy Govindan,
- Obi L. Griffith,
- Malachi Griffith
Affiliations
- Kelsy C. Cotto
- Division of Oncology, Department of Medicine, Washington University School of Medicine
- Yang-Yang Feng
- McDonnell Genome Institute, Washington University School of Medicine
- Avinash Ramu
- Department of Genetics, Washington University School of Medicine
- Megan Richters
- Division of Oncology, Department of Medicine, Washington University School of Medicine
- Sharon L. Freshour
- Division of Oncology, Department of Medicine, Washington University School of Medicine
- Zachary L. Skidmore
- Division of Oncology, Department of Medicine, Washington University School of Medicine
- Huiming Xia
- Division of Oncology, Department of Medicine, Washington University School of Medicine
- Joshua F. McMichael
- McDonnell Genome Institute, Washington University School of Medicine
- Jason Kunisaki
- McDonnell Genome Institute, Washington University School of Medicine
- Katie M. Campbell
- Division of Oncology, Department of Medicine, Washington University School of Medicine
- Timothy Hung-Po Chen
- Division of Oncology, Department of Medicine, Washington University School of Medicine
- Emily B. Rozycki
- Division of Oncology, Department of Medicine, Washington University School of Medicine
- Douglas Adkins
- Division of Oncology, Department of Medicine, Washington University School of Medicine
- Siddhartha Devarakonda
- Division of Oncology, Department of Medicine, Washington University School of Medicine
- Sumithra Sankararaman
- Division of Oncology, Department of Medicine, Washington University School of Medicine
- Yiing Lin
- Department of Surgery, Washington University School of Medicine
- William C. Chapman
- Department of Surgery, Washington University School of Medicine
- Christopher A. Maher
- Division of Oncology, Department of Medicine, Washington University School of Medicine
- Vivek Arora
- Division of Oncology, Department of Medicine, Washington University School of Medicine
- Gavin P. Dunn
- Department of Neurosurgery, Mass General Hospital
- Ravindra Uppaluri
- Department of Surgery, Brigham and Women’s Hospital
- Ramaswamy Govindan
- Division of Oncology, Department of Medicine, Washington University School of Medicine
- Obi L. Griffith
- Division of Oncology, Department of Medicine, Washington University School of Medicine
- Malachi Griffith
- Division of Oncology, Department of Medicine, Washington University School of Medicine
- DOI
- https://doi.org/10.1038/s41467-023-37266-6
- Journal volume & issue
-
Vol. 14,
no. 1
pp. 1 – 18
Abstract
Analysing the regulatory consequences of mutations and splice variants at large scale in cancer requires efficient computational tools. Here, the authors develop RegTools, a software package that can identify splice-associated variants from large-scale genomics and transcriptomics data with efficiency and flexibility.
