This project wants to allow the user to calculate functional similarities (or biological correlation as it was named originally hence the name) and use them for network building or other purposes.
It is an R package you can install it from the Bioconductor project with:
if (!requireNamespace("BiocManager", quietly = TRUE)) {
install.packages("BiocManager")
}
BiocManager::install("BioCor")
You can install this version of BioCor with:
if (!requireNamespace("devtools", quietly = TRUE)) {
install.packages("devtools")
}
devtools::install_github("llrs/BioCor")
See the
vignette
in Bioconductor site and the advanced
vignette.
Here is a minimum example:
# The data must be provided, see the vignette for more details.
# Get some pathways from the pathway data
(pathways <- sample(unlist(genesReact, use.names = FALSE), 5))
#> [1] "R-HSA-372790" "R-HSA-168188" "R-HSA-450294" "R-HSA-109582" "R-HSA-194840"
# Calculate the pathway similarity of them
mpathSim(pathways, genesReact, NULL)
#> R-HSA-372790 R-HSA-168188 R-HSA-450294 R-HSA-109582 R-HSA-194840
#> R-HSA-372790 1.00000000 0.02341920 0.01924619 0.14301552 0.08478425
#> R-HSA-168188 0.02341920 1.00000000 0.79012346 0.02781641 0.00000000
#> R-HSA-450294 0.01924619 0.79012346 1.00000000 0.02335766 0.00000000
#> R-HSA-109582 0.14301552 0.02781641 0.02335766 1.00000000 0.03689065
#> R-HSA-194840 0.08478425 0.00000000 0.00000000 0.03689065 1.00000000
It is intended for bioinformaticians, both people interested in knowing the functionally similarity of some genes or clusters and people developing some other analysis at the top of it.
The goal of this project is to provide methods to calculate functional similarities based on pathways.
Here is a non-comprehensive list:
- Diseases or drug:
By observing which genes with the same pathways are more affected - Gene/protein functional analysis:
By testing how new pathways are similar to existing pathways - Protein-protein interaction:
By testing if they are involved in the same pathways - miRNA-mRNA interaction:
By comparing clusters they affect - sRNA regulation:
By observing the relationship between sRNA and genes - Evolution:
By comparing similarities of genes between species - Networks improvement:
By adding information about the known relationship between genes - Evaluate pathways databases:
By comparing scores of the same entities
See the advanced vignette
Please read how to contribute for details on the code of conduct, and the process for submitting pull requests.
Anyone that has contributed to make this package be as is, specially my advisor.