R package for the identification of functionally important subnetworks
Crosstalkr provides a general implementation of a random-walk with
restarts on graph structured data. We also provide user-friendly
implementations of the common use-case of using random-walk with
restarts to identify subnetworks of biological protein-protein
interaction databases. Given a user-defined set of seed proteins, the
main compute_crosstalk function will compute affinity
scores for all other proteins in the network. It will then compute a
null distribution using a permutation test and compare the computed
affinity scores to the null distribution to identify proteins with a
statistically significant association to the user-defined seed-proteins.
Thanks to integration with stringdb, users can evaluate biological
networks from 1540 different species. For a list of supported species -
just call:
crosstalkr::supported_species()To install, use the following code:
install.packages("crosstalkr")
For the latest development version:
install.packages("remotes") #can skip if already installed
remotes::install_github("https://github.com/DavisWeaver/crosstalkr")Given a set of user-provided set of seeds, crosstalkr will identify enriched an enriched subgraph where all nodes have a high affinity for the provided seeds.
crosstalkr is optimized for use with the human cell signaling network. For example, running the code below will return a dataframe containing the user-provided seeds as well as all other proteins in the human protein-protein interaction network with a statistically significant association to these genes.
compute_crosstalk(c("EGFR", "KRAS"))Users can use any other kind of graph-structured data, provided they are stored in an igraph object. For example:
g <- igraph::sample_gnp(n = 1000, p = 10/1000)
compute_crosstalk(c(1,3,5,8,10), g = g, use_ppi = FALSE)We also provide rudimentary plotting functions to allow users to quickly assess the identified subnetworks:
ct_df <- compute_crosstalk(c("EGFR", "KRAS"))
plot_ct(ct_df)A more detailed overview of the available functionality is provided in the introductory vignette (under development).
vignette(package = "crosstalkr")More detailed methodology can be found here: “Nibbe et al., An Integrative -omics Approach to Identify Functional Sub-Networks in Human Colorectal Cancer, Comput Biol 6(1): e1000639. doi:10.1371/journal.pcbi.1000639”
Please feel free to submit issues here. You can also contact me at davis.weaver@case.edu if you have any questions.