reactome.pathways: Reactome pathways collection

In fernandoPalluzzi/SEMdata: Datasets for SEM-based network analysis using the SEMgraph R package

Reactome pathways collection

Description

Collection of Reactome signaling pathways extracted using the graphite R package (update: April, 2020).

Usage

reactome.pathways

Format

"reactome.pathways" is a list of 1641 Reactome pathways, stored as igraph objects.

Source

https://reactome.org

References

Jassal B, Matthews L, Viteri G, Gong C, Lorente P, Fabregat A, Sidiropoulos K, Cook J, Gillespie M, Haw R, Loney F, May B, Milacic M, Rothfels K, Sevilla C, Shamovsky V, Shorser S, Varusai T, Weiser J, Wu G, Stein L, Hermjakob H, D'Eustachio P. The reactome pathway knowledgebase. Nucleic Acids Res. 2020 Jan 8;48(D1):D498-D503. <doi:10.1093/nar/gkz1031. PubMed PMID: 31691815.>

Martini P, Sales G, Massa MS, Chiogna M, Romualdi C. Along signal paths: anempirical gene set approach exploiting pathway topology. Nucleic Acids Res. 41(1):e19. <https://doi.org/10.1093/nar/gks866>

Examples

## Not run: 

# Number of nodes per pathway
react.nodes <- unlist(lapply(reactome.pathways, vcount))
names(react.nodes) <- NULL
# Number of edges per pathway
react.edges <- unlist(lapply(reactome.pathways, ecount))
names(react.edges) <- NULL
# Gene list per pathway
react.genes <- unlist(lapply(reactome.pathways, function(x) V(x)$name))
quantile(react.nodes)
quantile(react.edges)
length(unique(react.genes))  # Number of unique genes within the dataset

# Loading breast cancer KEGG network
i <- which(names(reactome.pathways) == "NOTCH4 Intracellular Domain Regulates Transcription")
notch4.graph <- reactome.pathways[[i]]
summary(notch4.graph)
gplot(notch4.graph)


## End(Not run)

fernandoPalluzzi/SEMdata documentation built on June 27, 2022, 7:04 a.m.