README.md
In BioCor: Functional similarities

BioCor

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.

Installation

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")

How to use 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

Who might use this package?

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.

What is the goal of this project?

The goal of this project is to provide methods to calculate functional similarities based on pathways.

What can be BioCor used for?

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