Paper Info
Title
NeoPredPipe: high-throughput neoantigen prediction and recognition potential pipeline.
Abstract
Next generation sequencing has yielded an unparalleled means of quickly determining the molecular make-up of patient tumors. In conjunction with emerging, effective immunotherapeutics for a number of cancers, this rapid data generation necessitates a paired high-throughput means of predicting and assessing neoantigens from tumor variants that may stimulate immune response. Here we offer NeoPredPipe (Neoantigen Prediction Pipeline) as a contiguous means of predicting putative neoantigens and their corresponding recognition potentials for both single and multi-region tumor samples. NeoPredPipe is able to quickly provide summary information for researchers, and clinicians alike, on predicted neoantigen burdens while providing high-level insights into tumor heterogeneity given somatic mutation calls and, optionally, patient HLA haplotypes. Given an example dataset we show how NeoPredPipe is able to rapidly provide insights into neoantigen heterogeneity, burden, and immune stimulation potential. Through the integration of widely adopted tools for neoantigen discovery NeoPredPipe offers a contiguous means of processing single and multi-region sequence data. NeoPredPipe is user-friendly and adaptable for high-throughput performance. NeoPredPipe is freely available at https://github.com/MathOnco/NeoPredPipe .
Year
DOI
Venue
2019
10.1186/s12859-019-2876-4
BMC Bioinformatics
Keywords
Field
DocType
Neoantigens, Cancer, Evolution, Heterogeneity, Next-generation sequencing
Biology,Haplotype,DNA sequencing,Human leukocyte antigen,Throughput,Germline mutation,Genetics
Journal
Volume
Issue
ISSN
20
1
1471-2105
Citations 
PageRank 
References 
0
0.34
0
Authors
5
Name
Order
Citations
PageRank
Ryan O Schenck110.70
Eszter Lakatos210.68
Chandler Gatenbee300.34
Trevor A Graham410.69
Alexander R. A. Anderson53610.26