I am trying to run the script provided for this package
unfortunately, it gives an error,
I am using windows to run this


data(hyperLOPIT2015)
Warning message:
In data(hyperLOPIT2015) : data set ‘hyperLOPIT2015’ not found

FYI

> sessionInfo()
R version 3.4.0 (2017-04-21)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 7 x64 (build 7601) Service Pack 1

Matrix products: default

locale:
[1] LC_COLLATE=English_United States.1252  LC_CTYPE=English_United States.1252    LC_MONETARY=English_United States.1252
[4] LC_NUMERIC=C                           LC_TIME=English_United States.1252    

attached base packages:
[1] stats4    parallel  stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
 [1] pRolocGUI_1.10.0     pRoloc_1.16.1        MLInterfaces_1.56.0  cluster_2.0.6        annotate_1.54.0     
 [6] XML_3.98-1.7         AnnotationDbi_1.38.1 IRanges_2.10.2       S4Vectors_0.14.3     MSnbase_2.2.0       
[11] ProtGenerics_1.8.0   BiocParallel_1.10.1  mzR_2.10.0           Rcpp_0.12.11         Biobase_2.36.2      
[16] BiocGenerics_0.22.0  BiocInstaller_1.26.0 limma_3.32.2         ggplot2_2.2.1        reshape2_1.4.2      
[21] data.table_1.10.4    hash_2.2.6          

loaded via a namespace (and not attached):
  [1] minqa_1.2.4           colorspace_1.3-2      hwriter_1.3.2         class_7.3-14          modeltools_0.2-21    
  [6] mclust_5.3            pls_2.6-0             base64enc_0.1-3       proxy_0.4-17          hexbin_1.27.1        
 [11] MatrixModels_0.4-1    affyio_1.46.0         DT_0.2                flexmix_2.3-14        mvtnorm_1.0-6        
 [16] codetools_0.2-15      splines_3.4.0         doParallel_1.0.10     impute_1.50.1         robustbase_0.92-7    
 [21] knitr_1.16            jsonlite_1.5          nloptr_1.0.4          caret_6.0-76          pbkrtest_0.4-7       
 [26] rda_1.0.2-2           kernlab_0.9-25        vsn_3.44.0            sfsmisc_1.1-1         shiny_1.0.3          
 [31] compiler_3.4.0        sampling_2.8          assertthat_0.2.0      Matrix_1.2-9          lazyeval_0.2.0       
 [36] htmltools_0.3.6       quantreg_5.33         tools_3.4.0           ggvis_0.4.3           gtable_0.2.0         
 [41] glue_1.0.0            affy_1.54.0           dplyr_0.7.0           MALDIquant_1.16.2     trimcluster_0.1-2    
 [46] gdata_2.18.0          preprocessCore_1.38.1 nlme_3.1-131          iterators_1.0.8       fpc_2.1-10           
 [51] stringr_1.2.0         lme4_1.1-13           lpSolve_5.6.13        mime_0.5              gtools_3.5.0         
 [56] dendextend_1.5.2      DEoptimR_1.0-8        zlibbioc_1.22.0       MASS_7.3-47           scales_0.4.1         
 [61] pcaMethods_1.68.0     SparseM_1.77          RColorBrewer_1.1-2    memoise_1.1.0         gridExtra_2.2.1      
 [66] biomaRt_2.32.1        rpart_4.1-11          stringi_1.1.5         RSQLite_1.1-2         genefilter_1.58.1    
 [71] randomForest_4.6-12   foreach_1.4.3         e1071_1.6-8           rlang_0.1.1           prabclus_2.2-6       
 [76] bitops_1.0-6          mzID_1.14.0           lattice_0.20-35       htmlwidgets_0.8       labeling_0.3         
 [81] gbm_2.1.3             plyr_1.8.4            magrittr_1.5          R6_2.2.1              DBI_0.6-1            
 [86] whisker_0.3-2         mgcv_1.8-17           survival_2.41-3       RCurl_1.95-4.8        nnet_7.3-12          
 [91] tibble_1.3.3          car_2.1-4             mlbench_2.1-1         viridis_0.4.0         grid_3.4.0           
 [96] FNN_1.1               ModelMetrics_1.1.0    threejs_0.2.2         digest_0.6.12         diptest_0.75-7       
[101] xtable_1.8-2          httpuv_1.3.3          munsell_0.4.3         viridisLite_0.2.0    
> 

The hyperLOPIT2015 data lives in the pRolocdata package, which you need to load first:

> library("pRolocdata")
> data(hyperLOPIT2015)
> hyperLOPIT2015
MSnSet (storageMode: lockedEnvironment)
assayData: 5032 features, 20 samples
  element names: exprs
protocolData: none
phenoData
  sampleNames: X126.rep1 X127N.rep1 ... X131.rep2 (20 total)
  varLabels: Replicate TMT.Reagent ... Iodixonal.Density (5 total)
  varMetadata: labelDescription
featureData
  featureNames: Q9JHU4 Q9QXS1-3 ... Q9Z2R6 (5032 total)
  fvarLabels: entry.name protein.description ... markers2015 (25 total)
  fvarMetadata: labelDescription
experimentData: use 'experimentData(object)'
Annotation:  
- - - Processing information - - -
Loaded on Mon Aug 22 13:47:10 2016.
Normalised to sum of intensities.
 MSnbase version: 1.21.7