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demo

library(knitr)
library(mhcnuggetsr)
library(testthat)

For this vignette, we use the same example as the MHCnuggets Python notebooks.

Get the path to the testing peptides, and show them:

if (is_mhcnuggets_installed()) {
  peptides_path <- get_example_filename("test_peptides.peps")
  expect_true(file.exists(peptides_path))
  readLines(peptides_path, warn = FALSE)
}

Pick an MHC-I haplotype:

if (is_mhcnuggets_installed()) {
  mhc_1_haplotype <- "HLA-A02:01"
  expect_true(mhc_1_haplotype %in% get_trained_mhc_1_haplotypes())
}

Predict:

if (is_mhcnuggets_installed()) {
  mhcnuggets_options <- create_mhcnuggets_options(
    mhc = mhc_1_haplotype
  )
  df <- predict_ic50_from_file(
    peptides_path = peptides_path,
    mhcnuggets_options = mhcnuggets_options
  )
  kable(df)
}

Predict:

if (is_mhcnuggets_installed()) {
  mhcnuggets_options <- create_mhcnuggets_options(
    mhc = mhc_1_haplotype,
    ba_models = TRUE
  )
  df <- predict_ic50_from_file(
    peptides_path = peptides_path,
    mhcnuggets_options = mhcnuggets_options
  )
  kable(df)
}

Use MCH-II haplotype:

if (is_mhcnuggets_installed()) {
  mhc_2_haplotype <- "HLA-DRB101:01"
  expect_true(mhc_2_haplotype %in% get_trained_mhc_2_haplotypes())
}

Predict:

if (is_mhcnuggets_installed()) {
  mhcnuggets_options <- create_mhcnuggets_options(
    mhc = mhc_2_haplotype
  )
  df <- predict_ic50_from_file(
    peptides_path = peptides_path,
    mhcnuggets_options = mhcnuggets_options
  )
  kable(df)
}

Use another MHC-I haplotype. In this case, MHCnuggets has not been trained upon it, but it is a valid supertype:

if (is_mhcnuggets_installed()) {
  mhc_1_haplotype <- "HLA-A02:60"
  expect_false(mhc_1_haplotype %in% get_trained_mhc_1_haplotypes())
}

Predict:

if (is_mhcnuggets_installed()) {
  mhcnuggets_options <- create_mhcnuggets_options(
    mhc_class = "I",
    mhc = mhc_1_haplotype
  )
  df <- predict_ic50_from_file(
    peptides_path = peptides_path,
    mhcnuggets_options = mhcnuggets_options
  )
  kable(df)
}

if (is_mhcnuggets_installed()) {
  basename(get_example_filenames())
}

if (is_mhcnuggets_installed()) {
  cat(get_trained_mhc_1_haplotypes())
}

if (is_mhcnuggets_installed()) {
  cat(get_trained_mhc_2_haplotypes())
}

mhcnuggetsr_report()
#> ***************
#> * mhcnuggetsr *
#> ***************
#> OS: unix
#> Python location: /usr/bin/python3
#> Is pip installed: TRUE
#> pip version: 20.0.2
#> Python NumPy available: TRUE
#> Python mhcnuggets available: TRUE
#> **************
#> * MHCnuggets *
#> **************
#> Is MHCnuggets installed: FALSE
#> Tip: when working on the Groninger Peregrine computer cluster, 
#> type: 
#> 
#> ~/.local/share/r-miniconda/envs/r-reticulate/bin/python -m pip  install mhcnuggets
#> ***************
#> * sessionInfo *
#> ***************
#> R version 3.6.3 (2020-02-29)
#> Platform: x86_64-pc-linux-gnu (64-bit)
#> Running under: Ubuntu 20.04.1 LTS
#> 
#> Matrix products: default
#> BLAS:   /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.9.0
#> LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.9.0
#> 
#> locale:
#>  [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
#>  [3] LC_TIME=en_US.UTF-8        LC_COLLATE=C              
#>  [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
#>  [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
#>  [9] LC_ADDRESS=C               LC_TELEPHONE=C            
#> [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       
#> 
#> attached base packages:
#> [1] stats     graphics  grDevices utils     datasets  methods   base     
#> 
#> other attached packages:
#> [1] testthat_2.3.2  mhcnuggetsr_1.1 knitr_1.30     
#> 
#> loaded via a namespace (and not attached):
#>  [1] Rcpp_1.0.5           magrittr_1.5         rappdirs_0.3.1      
#>  [4] lattice_0.20-40      R6_2.4.1             rlang_0.4.8         
#>  [7] highr_0.8            stringr_1.4.0        tools_3.6.3         
#> [10] grid_3.6.3           xfun_0.18            htmltools_0.5.0.9001
#> [13] ellipsis_0.3.1       yaml_2.2.1           digest_0.6.27       
#> [16] tibble_3.0.4         lifecycle_0.2.0      crayon_1.3.4        
#> [19] Matrix_1.2-18        vctrs_0.3.4          evaluate_0.14       
#> [22] rmarkdown_2.4        stringi_1.5.3        compiler_3.6.3      
#> [25] pillar_1.4.6         reticulate_1.16      jsonlite_1.7.1      
#> [28] pkgconfig_2.0.3

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.