Insertion and deletion (indels) have been recognized as an important source generating tumor-specific mutant peptides (neoantigens). The focus of indel-derived neoantigen identification has been on leveraging DNA sequencing such as whole exome sequencing, with the effort of using RNA-seq less well explored. Here we present ScanNeo, a fast-streamlined computational pipeline for analyzing RNA-seq to predict neoepitopes derived from small to large-sized indels. We applied ScanNeo in a prostate cancer cell line and validated our predictions with matched mass spectrometry data. Finally, we demonstrated that indel neoantigens predicted from RNA-seq were associated with checkpoint inhibitor response in a cohort of melanoma patients. Availability and implementation: ScanNeo is implemented in Python. It is freely accessible at the GitHub repository (https://github.com/ylab-hi/ScanNeo). Supplementary information: Supplementary data are available at Bioinformatics online.
Bibliographical noteFunding Information:
This work was supported by Young Investigator Award from the Prostate Cancer Foundation and Research Starter Grant from PhRMA foundation.
PubMed: MeSH publication types
- Journal Article
- Research Support, Non-U.S. Gov't