Integrated protocol for exitron and exitron-derived neoantigen identification using human RNA-seq data with ScanExitron and ScanNeo

Ting-You Wang; Rendong Yang

doi:10.1016/j.xpro.2021.100788

Integrated protocol for exitron and exitron-derived neoantigen identification using human RNA-seq data with ScanExitron and ScanNeo

STAR Protoc. 2021 Sep 3;2(3):100788. doi: 10.1016/j.xpro.2021.100788. eCollection 2021 Sep 17.

Authors

Ting-You Wang¹, Rendong Yang^{1

2}

Affiliations

¹ The Hormel Institute, University of Minnesota, Austin, MN 55912, USA.
² Masonic Cancer Center, University of Minnesota, Minneapolis, MN 55455, USA.

Abstract

Exitron splicing (EIS) events in cancers can disrupt functional protein domains to cause cancer driver effects. EIS has been recognized as a new source of tumor neoantigens. Here, we describe an integrated protocol for EIS and EIS-derived neoantigen identification using RNA-seq data. The protocol constitutes a step-by-step guide from data collection to neoantigen prediction. For complete details on the use and execution of this protocol, please refer to Wang et al. (2021).

Keywords: Bioinformatics; Cancer; Genetics; Genomics; Immunology; RNAseq.

Publication types

Research Support, Non-U.S. Gov't
Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

Antigens, Neoplasm / genetics*
Databases, Genetic
Genomics / methods*
Humans
Neoplasms / genetics
RNA Splicing / genetics*
RNA-Seq / methods*
Software

Substances

Antigens, Neoplasm