Skip to content

Calculate and explore property indices of peptides for cancer immunotherapy study

License

Unknown, MIT licenses found

Licenses found

Unknown
LICENSE
MIT
LICENSE.md
Notifications You must be signed in to change notification settings

ShixiangWang/neopeptides

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

33 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

neopeptides

Lifecycle: stable

The goal of neopeptides is to calculate and explore property indices of peptides for cancer immunotherapy study.

Installation

You can install the development version from GitHub with:

# install.packages("devtools")
devtools::install_github("ShixiangWang/neopeptides")

Configuration

To use neopeptide, blast is required.

After installation of blast, you can set the path with

set_blast_path()
# e.g. 
# set_blast_path("/Users/wsx/anaconda3/bin/")

Then install required protein database with

install_database()

Major features

  • calc_iedb_score() - Calculate IEDB Score for Peptides.
  • calc_dissimilarity() - Calculate Dissimilarity Value to Reference Proteome for Peptides.

Examples

library(neopeptides)

calc_iedb_score(c("MTEYKLVVVGAGDVGKSALTIQLIQNHFVDEYDP", "MTEYKLVVVG"))
#> => Running blastp for homology to IEDB antigens..
#> => Summing IEDB local alignments...
#> => Done.
#> => Removing temporary files...
#>                               peptide   iedb_score
#> 1: MTEYKLVVVGAGDVGKSALTIQLIQNHFVDEYDP 5.038247e-01
#> 2:                         MTEYKLVVVG 5.895595e-05
#>                                                                                    annotation
#> 1:                      18142|polyprotein precursor|NP_041724.2|West Nile virus|11082 DVGVSAL
#> 2: 32238|polyprotein [Hepatitis C virus subtype 1a]|ABV46251.2|Hepatitis C virus|11103 KLVVLG
calc_dissimilarity(c("MTEYKLVVVGAGDVGKSALTIQLIQNHFVDEYDP", "MTEYKLVVVG"))
#> => Running blastp for homology to self antigens..
#> => Summing local alignments...
#> => Done.
#> => Removing temporary files...
#>                               peptide dissimilarity
#> 1: MTEYKLVVVGAGDVGKSALTIQLIQNHFVDEYDP             0
#> 2:                         MTEYKLVVVG             0

Citation

Revisiting neoantigen depletion signal in the untreated cancer genome. Shixiang Wang, Xuan Wang, Tao Wu, Zaoke He, Huimin Li, Xiaoqin Sun, Xue-Song Liu bioRxiv 2020.05.11.089540; doi: https://doi.org/10.1101/2020.05.11.089540

Researches used this tool

  • Wang X, Wang S, Han Y, Xu M, Li P, Ke M, Teng Z, Huang P, Diao Z, Yan Y, Meng Q, Kuang Y, Zheng W, Liu H, Liu X, Jia B. Association of CSMD1 with Tumor Mutation Burden and Other Clinical Outcomes in Gastric Cancer. Int J Gen Med. 2021;14:8293-8299 https://doi.org/10.2147/IJGM.S325910

Reference

  • Richman LP, Vonderheide RH, Rech AJ. Neoantigen Dissimilarity to the Self-Proteome Predicts Immunogenicity and Response to Immune Checkpoint Blockade. Cell Systems. 2019 Oct;9(4):375-382.e4. DOI: 10.1016/j.cels.2019.08.009.
  • R package antigen.garnish https://github.com/immune-health/antigen.garnish

LICENSE

MIT © 2019-2020 Shixiang Wang, Xue-Song Liu

About

Calculate and explore property indices of peptides for cancer immunotherapy study

Topics

Resources

License

Unknown, MIT licenses found

Licenses found

Unknown
LICENSE
MIT
LICENSE.md

Stars

Watchers

Forks

Packages

No packages published

Languages