PANACEA: Personalized Network-based Anti-Cancer Therapy Evaluation
PANACEA: Personalized Network-based Anti-Cancer Therapy Evaluation
Identification of the most appropriate pharmacotherapy for each
patient based on genomic alterations is a major challenge in
personalized oncology. PANACEA is a collection of
personalized anti-cancer drug prioritization approaches utilizing
network methods. The methods utilize personalized “driverness” scores
from driveR to
rank drugs, mapping these onto a protein-protein interaction network.
The “distance-based” method scores each drug based on these scores and
distances between drugs and genes to rank given drugs. The “RWR” method
propagates these scores via a random-walk with restart framework to rank
the drugs.
The method is described in detail in Ulgen E, Ozisik O, Sezerman OU. PANACEA: network-based methods for pharmacotherapy prioritization in personalized oncology. Bioinformatics. 2023 Jan 1;39(1):btad022. https://doi.org/10.1093/bioinformatics/btad022
You can install the latest release version of PANACEA from CRAN via:
install.packages("PANACEA")You can install the development version of PANACEA from GitHub with:
# install.packages("devtools") @ if you don't have devtools installed
devtools::install_github("egeulgen/PANACEA", build_vignettes = TRUE)The wrapper function score_drugs() can be used to score
and rank drugs for an individual tumor sample via the “distance-based”
or “RWR” method. The required inputs are:
driveR_res: data frame of driveR results. Details on
how to obtain driveR output are provided in this
vignettedrug_interactions_df: data frame of drug-gene
interactions (defaults to interactions from DGIdb expert-curated
sources)W_mat: (symmetric) adjacency matrix for the protein
interaction network (defaults to STRING v11.5 interactions with combined
score > .4)method: scoring method (one of “distance-based” or
“RWR”)For detailed information on how to use PANACEA, please
see the vignette “How to use PANACEA” via
vignette("how_to_use") or visit this
link