MetaGxPancreas: A Package for Pancreatic Cancer Gene Expression Analysis

list(name = “Michael Zon”, affiliation = “Department of Medical Biophysics, University of Toronto, Toronto, Canada”) list(name = “Vandana Sandhu”, affiliation = “Department of Medical Biophysics, University of Toronto, Toronto, Canada”) list(name = “Benjamin Haibe-Kains”, email = “benjamin.haibe.kains@utoronto.ca”, affiliation = c(“Department of Medical Biophysics, University of Toronto, Toronto, Canada”, “Bioinformatics and Computational Genomics Laboratory, Princess Margaret Cancer Center, University Health Network, Toronto, Ontario, Canada”))

Installing the Package

The MetaGxPancreas package is a compendium of Pancreatic Cancer datasets. The package is publicly available and can be installed from Bioconductor into R version 3.6.0 or higher. Currently, the phenoData for the datasets is overall survival status and overall survival time. This survival information is available for 11 of the 15 datasets.

if (!requireNamespace("BiocManager", quietly = TRUE))
    install.packages("BiocManager")
BiocManager::install("MetaGxPancreas")

Loading Datasets

First we load the MetaGxPancreas package into the workspace.

library(MetaGxPancreas)
## Loading required package: SummarizedExperiment
## Loading required package: MatrixGenerics
## Loading required package: matrixStats
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## Attaching package: 'MatrixGenerics'
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##     colMads, colMaxs, colMeans2, colMedians, colMins, colOrderStats,
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##     rowCumsums, rowDiffs, rowIQRDiffs, rowIQRs, rowLogSumExps,
##     rowMadDiffs, rowMads, rowMaxs, rowMeans2, rowMedians, rowMins,
##     rowOrderStats, rowProds, rowQuantiles, rowRanges, rowRanks,
##     rowSdDiffs, rowSds, rowSums2, rowTabulates, rowVarDiffs, rowVars,
##     rowWeightedMads, rowWeightedMeans, rowWeightedMedians,
##     rowWeightedSds, rowWeightedVars
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## Attaching package: 'S4Vectors'
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## Loading required package: ExperimentHub
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pancreasData <- loadPancreasDatasets()
## Filtered out duplicated samples: ICGC_0400, ICGC_0402, GSM388116, GSM388118, GSM388120, GSM388145, GSM299238, GSM299239, GSM299240
duplicates <- pancreasData$duplicates
SEs <- pancreasData$SEs

This will load 15 expression datasets. Users can modify the parameters of the function to restrict datasets that do not meet certain criteria for loading. Some example parameters are shown below:

Obtaining Sample Counts in Datasets

To obtain the number of samples per dataset, run the following:

numSamples <- vapply(SEs, function(SE) length(colnames(SE)), FUN.VALUE=numeric(1))

sampleNumberByDataset <- data.frame(numSamples=numSamples,
                                    row.names=names(SEs))

totalNumSamples <- sum(sampleNumberByDataset$numSamples)
sampleNumberByDataset <- rbind(sampleNumberByDataset, totalNumSamples)
rownames(sampleNumberByDataset)[nrow(sampleNumberByDataset)] <- 'Total'

knitr::kable(sampleNumberByDataset)
X0
Total 0

SessionInfo

sessionInfo()
## R version 4.3.0 RC (2023-04-18 r84287)
## Platform: x86_64-pc-linux-gnu (64-bit)
## Running under: Ubuntu 22.04.2 LTS
## 
## Matrix products: default
## BLAS:   /home/biocbuild/bbs-3.18-bioc/R/lib/libRblas.so 
## LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.10.0
## 
## locale:
##  [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
##  [3] LC_TIME=en_GB              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       
## 
## time zone: America/New_York
## tzcode source: system (glibc)
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## attached base packages:
## [1] stats4    stats     graphics  grDevices utils     datasets  methods  
## [8] base     
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## other attached packages:
##  [1] MetaGxPancreas_1.21.0       ExperimentHub_2.9.0        
##  [3] AnnotationHub_3.9.0         BiocFileCache_2.9.0        
##  [5] dbplyr_2.3.2                SummarizedExperiment_1.31.0
##  [7] Biobase_2.61.0              GenomicRanges_1.53.0       
##  [9] GenomeInfoDb_1.37.0         IRanges_2.35.0             
## [11] S4Vectors_0.39.0            BiocGenerics_0.47.0        
## [13] MatrixGenerics_1.13.0       matrixStats_0.63.0         
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##  [7] bitops_1.0-7                  generics_0.1.3               
##  [9] curl_5.0.0                    AnnotationDbi_1.63.0         
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## [13] RSQLite_2.3.1                 blob_1.2.4                   
## [15] pkgconfig_2.0.3               Matrix_1.5-4                 
## [17] lifecycle_1.0.3               GenomeInfoDbData_1.2.10      
## [19] compiler_4.3.0                Biostrings_2.69.0            
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## [55] knitr_1.42                    rlang_1.1.0                  
## [57] Rcpp_1.0.10                   xtable_1.8-4                 
## [59] glue_1.6.2                    DBI_1.1.3                    
## [61] BiocManager_1.30.20           R6_2.5.1                     
## [63] zlibbioc_1.47.0