Overview of pathway network databases
2021-10-26
Contents
1 Introduction
1.1 Load required packages
Load the package with the library function.
library(tidyverse)
library(ggplot2)
library(dce)
set.seed(42)dce::df_pathway_statistics %>%
sample_n(10) %>%
arrange(desc(node_num)) %>%
knitr::kable()| database | pathway_id | pathway_name | node_num | edge_num |
|---|---|---|---|---|
| kegg | hsa:04151 | PI3K-Akt signaling pathway | 354 | 4552 |
| kegg | hsa:04371 | Apelin signaling pathway | 134 | 942 |
| kegg | hsa:04520 | Adherens junction | 68 | 170 |
| kegg | hsa:04970 | Salivary secretion | 48 | 96 |
| kegg | hsa:05321 | Inflammatory bowel disease | 48 | 81 |
| nci | pid_4166 | Beta2 integrin cell surface interactions | 29 | 140 |
| kegg | hsa:00563 | Glycosylphosphatidylinositol (GPI)-anchor biosynthesis | 23 | 116 |
| kegg | hsa:00900 | Terpenoid backbone biosynthesis | 21 | 69 |
| biocarta | pid_10459 | rna polymerase iii transcription | 7 | 42 |
| biocarta | pid_9732 | estrogen responsive protein efp controls cell cycle and breast tumors growth | 4 | 2 |
2 Pathway database overview
We provide access to the following topological pathway databases using graphite (Sales et al. 2012):
dce::df_pathway_statistics %>%
count(database, sort = TRUE, name = "pathway_number") %>%
knitr::kable()| database | pathway_number |
|---|---|
| kegg | 317 |
| biocarta | 247 |
| nci | 212 |
| panther | 94 |
| pharmgkb | 66 |
dce::df_pathway_statistics %>%
ggplot(aes(x = node_num)) +
geom_histogram(bins = 30) +
facet_wrap(~ database, scales = "free") +
theme_minimal()
3 Plotting pathways
It is easily possible to plot pathways:
pathways <- get_pathways(
pathway_list = list(
kegg = c("Citrate cycle (TCA cycle)")
)
)## 'select()' returned 1:1 mapping between keys and columns
## 'select()' returned 1:1 mapping between keys and columns
## 'select()' returned 1:1 mapping between keys and columns
## 'select()' returned 1:1 mapping between keys and columnslapply(pathways, function(x) {
plot_network(as(x$graph, "matrix"), visualize_edge_weights = FALSE) +
ggtitle(x$pathway_name)
})## [[1]]
4 Session information
sessionInfo()## R version 4.1.1 (2021-08-10)
## Platform: x86_64-pc-linux-gnu (64-bit)
## Running under: Ubuntu 20.04.3 LTS
##
## Matrix products: default
## BLAS: /home/biocbuild/bbs-3.14-bioc/R/lib/libRblas.so
## LAPACK: /home/biocbuild/bbs-3.14-bioc/R/lib/libRlapack.so
##
## 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
##
## attached base packages:
## [1] stats4 stats graphics grDevices utils datasets methods
## [8] base
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## other attached packages:
## [1] org.Hs.eg.db_3.14.0 AnnotationDbi_1.56.0
## [3] dce_1.2.0 graph_1.72.0
## [5] cowplot_1.1.1 forcats_0.5.1
## [7] stringr_1.4.0 dplyr_1.0.7
## [9] purrr_0.3.4 readr_2.0.2
## [11] tidyr_1.1.4 tibble_3.1.5
## [13] tidyverse_1.3.1 TCGAutils_1.14.0
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## [25] matrixStats_0.61.0 ggraph_2.0.5
## [27] ggplot2_3.3.5 BiocStyle_2.22.0
##
## loaded via a namespace (and not attached):
## [1] rappdirs_0.3.3 rtracklayer_1.54.0
## [3] prabclus_2.3-2 bit64_4.0.5
## [5] knitr_1.36 multcomp_1.4-17
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## [197] gtable_0.3.0 rbibutils_2.2.4References
Sales, Gabriele, Enrica Calura, Duccio Cavalieri, and Chiara Romualdi. 2012. “Graphite-a Bioconductor Package to Convert Pathway Topology to Gene Network.” BMC Bioinformatics 13 (1): 20.