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

Ting You Wang^*, Rendong Yang

^*Corresponding author for this work

Urology

Research output: Contribution to journal › Article › peer-review

7 Scopus citations

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).

Original language	English (US)
Article number	100788
Journal	STAR Protocols
Volume	2
Issue number	3
DOIs	https://doi.org/10.1016/j.xpro.2021.100788
State	Published - Sep 17 2021

Funding

We acknowledge the following sources of funding: DoD ( W81XWH-19-1-0161 ) to R.Y. and Eagles Telethon Postdoctoral Fellowship to T.-Y.W. We thank Dr. Jeffrey McDonald at The Hormel Institute for his technical support for computing facilities. Support from the Minnesota Supercomputer Institute (MSI) is also gratefully acknowledged. We acknowledge the following sources of funding: DoD (W81XWH-19-1-0161) to R.Y. and Eagles Telethon Postdoctoral Fellowship to T.-Y.W. We thank Dr. Jeffrey McDonald at The Hormel Institute for his technical support for computing facilities. Support from the Minnesota Supercomputer Institute (MSI) is also gratefully acknowledged. Writing, T.-Y.W. and R.Y.; development and processing, T.-Y.W.; funding acquisition, R.Y. The authors declare no competing interests.

Keywords

Bioinformatics
Cancer
Genetics
Genomics
Immunology
RNAseq

ASJC Scopus subject areas

General Biochemistry, Genetics and Molecular Biology
General Neuroscience
General Immunology and Microbiology
General Medicine

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1016/j.xpro.2021.100788

Cite this

@article{3be1b22259bc4b1a86cf2b498166b736,

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

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",

author = "Wang, {Ting You} and Rendong Yang",

note = "Funding Information: We acknowledge the following sources of funding: DoD ( W81XWH-19-1-0161 ) to R.Y. and Eagles Telethon Postdoctoral Fellowship to T.-Y.W. We thank Dr. Jeffrey McDonald at The Hormel Institute for his technical support for computing facilities. Support from the Minnesota Supercomputer Institute (MSI) is also gratefully acknowledged. Funding Information: We acknowledge the following sources of funding: DoD (W81XWH-19-1-0161) to R.Y. and Eagles Telethon Postdoctoral Fellowship to T.-Y.W. We thank Dr. Jeffrey McDonald at The Hormel Institute for his technical support for computing facilities. Support from the Minnesota Supercomputer Institute (MSI) is also gratefully acknowledged. Writing, T.-Y.W. and R.Y.; development and processing, T.-Y.W.; funding acquisition, R.Y. The authors declare no competing interests. Publisher Copyright: {\textcopyright} 2021 The Author(s)",

year = "2021",

month = sep,

day = "17",

doi = "10.1016/j.xpro.2021.100788",

language = "English (US)",

volume = "2",

journal = "STAR Protocols",

issn = "2666-1667",

publisher = "Cell Press",

number = "3",

}

TY - JOUR

T1 - Integrated protocol for exitron and exitron-derived neoantigen identification using human RNA-seq data with ScanExitron and ScanNeo

AU - Wang, Ting You

AU - Yang, Rendong

N1 - Funding Information: We acknowledge the following sources of funding: DoD ( W81XWH-19-1-0161 ) to R.Y. and Eagles Telethon Postdoctoral Fellowship to T.-Y.W. We thank Dr. Jeffrey McDonald at The Hormel Institute for his technical support for computing facilities. Support from the Minnesota Supercomputer Institute (MSI) is also gratefully acknowledged. Funding Information: We acknowledge the following sources of funding: DoD (W81XWH-19-1-0161) to R.Y. and Eagles Telethon Postdoctoral Fellowship to T.-Y.W. We thank Dr. Jeffrey McDonald at The Hormel Institute for his technical support for computing facilities. Support from the Minnesota Supercomputer Institute (MSI) is also gratefully acknowledged. Writing, T.-Y.W. and R.Y.; development and processing, T.-Y.W.; funding acquisition, R.Y. The authors declare no competing interests. Publisher Copyright: © 2021 The Author(s)

PY - 2021/9/17

Y1 - 2021/9/17

N2 - 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).

AB - 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).

KW - Bioinformatics

KW - Cancer

KW - Genetics

KW - Genomics

KW - Immunology

KW - RNAseq

UR - http://www.scopus.com/inward/record.url?scp=85122822083&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85122822083&partnerID=8YFLogxK

U2 - 10.1016/j.xpro.2021.100788

DO - 10.1016/j.xpro.2021.100788

M3 - Article

C2 - 34522901

AN - SCOPUS:85122822083

SN - 2666-1667

VL - 2

JO - STAR Protocols

JF - STAR Protocols

IS - 3

M1 - 100788

ER -

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

Abstract

Funding

Keywords

ASJC Scopus subject areas

UN SDGs

Access to Document

Other files and links

Fingerprint

Cite this