1 Install R packages

1.1 Install SBGNview

Install SBGNview through Bioconductor

BiocManager::install(c("SBGNview"))

1.2 Install package ‘gage’ for pathway enrichment analysis

Install gage through Bioconductor

BiocManager::install(c("gage"))

2 IFNg dataset

In this example, we analyze a RNA-SEQ dataset of wild type mice and IFNg KO mice. It contains normalized RNA-seq gene expression data described in this study: Greer, Renee L., Xiaoxi Dong, et al. “Akkermansia muciniphila mediates negative effects of IFNg on glucose metabolism.” Nature communications 2016.

2.1 Load RNA-seq data

The RNA abundance data was quantile normalized and log2 transformed, stored in a “SummarizedExperiment” object

library(SBGNview)
library(SummarizedExperiment)
library(SBGNview.data)
data("IFNg")
count.data <- assays(IFNg)$counts
wt <- colnames(IFNg)[IFNg$group == "wt"]
ko <- colnames(IFNg)[IFNg$group == "ko"]
head(count.data)

2.2 Pathway enrichment analysis: run SBGNview gene set

2.2.1 Load gene list: mouse ensemble IDs.

ensemble.to.pathway <- getMolList(
    database = "pathwayCommons"
    ,mol.list.ID.type = "ENSEMBL"
    ,org = "mmu"
    ,cpd.or.gene = "gene"
    ,output.pathway.name = TRUE
)
head(ensemble.to.pathway[[2]])

2.2.2 Run gage

gage is an R package for pathway enrichment analysis.

library(gage)
degs <- gage(exprs = count.data
           ,gsets = ensemble.to.pathway
           ,ref = which(colnames(count.data) %in% wt)
           ,samp = which(colnames(count.data) %in% ko)
           ,compare = "as.group"
           )
head(degs$greater)[,c(1,4:5)]
head(degs$less)
down.pathways <- degs$less
head(down.pathways)

2.3 Visualize fold change on pathway maps

2.3.1 Generate fold change data for visualization.

The abundance table was log2 transformed. Here we calculate the fold change of KO group v.s. WT group.

mean.wt <- apply(count.data[,wt] ,1 ,"mean")
head(mean.wt)
mean.ko <- apply(count.data[,ko],1,"mean")
head(mean.ko)
ensemble.to.koVsWt <- mean.ko - mean.wt
head(ensemble.to.koVsWt)

2.3.2 Visualize fold change data

down.pathways <- do.call(rbind,strsplit(row.names(down.pathways),"::"))[,1]
head(down.pathways)
sbgnview.obj <- SBGNview(
    gene.data = ensemble.to.koVsWt,
    gene.id.type = "ENSEMBL",
    input.sbgn = down.pathways[1],
    output.file = "ifn.sbgnview.less",
    show.pathway.name = TRUE,
    max.gene.value = 2,
    min.gene.value = -2,
    mid.gene.value = 0,
    node.sum = "mean",
    label.spliting.string = c("-","_"," "), 
    output.format = c("png"),
    
    inhibition.edge.end.shift = 1,
    font.size = 2,
    logic.node.font.scale = 6,
    font.size.scale.compartment = 1.5,
    org = "mmu",
    
    text.length.factor.macromolecule = 0.8,
    text.length.factor.compartment = 2,
    text.length.factor.complex = 3,
    if.scale.compartment.font.size = TRUE,
    node.width.adjust.factor.compartment = 0.058 
)
sbgnview.obj
\label{fig:SBGNview map from sbgnview}SBGNview

Figure 2.1: SBGNview

2.3.3 Visualize RNA abundance data: SummarizedExperiment object as input.

data("cancer.ds")
sbgnview.obj <- SBGNview(
    gene.data = cancer.ds,
    gene.id.type = "ENTREZID",
    input.sbgn = "R-HSA-877300",
    output.file = "demo.SummarizedExperiment",
    show.pathway.name = TRUE,
    max.gene.value = 1,
    min.gene.value = -1,
    mid.gene.value = 0,
    node.sum = "mean",
    label.spliting.string = c("-","_"," "), 
    output.format = c("png"),
    
    inhibition.edge.end.shift = 1,
    font.size = 2,
    logic.node.font.scale = 6,
    font.size.scale.compartment = 1.5,
    org = "hsa",
    
    text.length.factor.macromolecule = 0.8,
    text.length.factor.compartment = 2,
    text.length.factor.complex = 3,
    if.scale.compartment.font.size = TRUE,
    node.width.adjust.factor.compartment = 0.058 
   )
sbgnview.obj

3 Session Info

sessionInfo()
## R version 4.0.0 RC (2020-04-19 r78255)
## Platform: x86_64-pc-linux-gnu (64-bit)
## Running under: Ubuntu 18.04.4 LTS
## 
## Matrix products: default
## BLAS:   /home/biocbuild/bbs-3.12-bioc/R/lib/libRblas.so
## LAPACK: /home/biocbuild/bbs-3.12-bioc/R/lib/libRlapack.so
## 
## 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] parallel  stats4    stats     graphics  grDevices utils     datasets 
## [8] methods   base     
## 
## other attached packages:
##  [1] gage_2.39.0                 SummarizedExperiment_1.19.0
##  [3] DelayedArray_0.15.0         matrixStats_0.56.0         
##  [5] GenomicRanges_1.41.0        GenomeInfoDb_1.25.0        
##  [7] SBGNview_1.3.0              SBGNview.data_1.1.0        
##  [9] pathview_1.29.0             org.Hs.eg.db_3.10.0        
## [11] AnnotationDbi_1.51.0        IRanges_2.23.0             
## [13] S4Vectors_0.27.0            Biobase_2.49.0             
## [15] BiocGenerics_0.35.0         knitr_1.28                 
## 
## loaded via a namespace (and not attached):
##  [1] KEGGREST_1.29.0        xfun_0.13              lattice_0.20-41       
##  [4] vctrs_0.2.4            htmltools_0.4.0        yaml_2.2.1            
##  [7] blob_1.2.1             XML_3.99-0.3           rlang_0.4.5           
## [10] DBI_1.1.0              Rgraphviz_2.33.0       bit64_0.9-7           
## [13] GenomeInfoDbData_1.2.3 stringr_1.4.0          zlibbioc_1.35.0       
## [16] Biostrings_2.57.0      memoise_1.1.0          evaluate_0.14         
## [19] rsvg_1.3               gbRd_0.4-11            highr_0.8             
## [22] Rcpp_1.0.4.6           graph_1.67.0           XVector_0.29.0        
## [25] bit_1.1-15.2           png_0.1-7              digest_0.6.25         
## [28] stringi_1.4.6          bookdown_0.18          grid_4.0.0            
## [31] bibtex_0.4.2.2         Rdpack_0.11-1          tools_4.0.0           
## [34] bitops_1.0-6           magrittr_1.5           RCurl_1.98-1.2        
## [37] RSQLite_2.2.0          crayon_1.3.4           pkgconfig_2.0.3       
## [40] Matrix_1.2-18          xml2_1.3.2             KEGGgraph_1.49.0      
## [43] rmarkdown_2.1          httr_1.4.1             R6_2.4.1              
## [46] igraph_1.2.5           compiler_4.0.0