GitHub - ELELAB/Moonlight2R: MoonlightR 2.0 development repository (original) (raw)

Cancer Systems Biology, Section of Bioinformatics, Department of Health and Technology, Technical University of Denmark, 2800, Lyngby, Copenhagen

Repository associated to the publications:

Interpreting pathways to discover cancer driver genes with Moonlight. Colaprico A, Olsen C, Bailey MH, Odom GJ, Terkelsen T, Silva TC, Olsen AV, Cantini L, Zinovyev A, Barillot E, Noushmehr H, Bertoli G, Castiglioni I, Cava C, Bontempi G, Chen XS, Papaleo E. Nat Commun. 2020 Jan 3;11(1):69. doi: 10.1038/s41467-019-13803-0., PMID: 31900418

A workflow to study mechanistic indicators for driver gene prediction with Moonlight. Mona Nourbakhsh, Astrid Saksager, Nikola Tom, Xi Steven Chen, Antonio Colaprico, Catharina Olsen, Matteo Tiberti, Elena Papaleo*, Briefings in Bioinformatics, 2023, bbad274, https://doi.org/10.1093/bib/bbad274

contacts for repository: Elena Papaleo, elpap-at-dtu.dk, elenap-at-cancer.dk; Matteo Tiberti: tiberti-at-cancer.dk

Introduction

This repository contains a new release fo our MoonlightR R package, called Moonlight2R, which implements the new and improved Moonlight2 workflow. Moonlight2R contains a number of differences and improvements respect to the original MoonlightR package. For a full overview of what the package can do, please see and cite when appropriate:

Mona Nourbakhsh, Astrid Saksager, Nikola Tom, Xi Steven Chen, Antonio Colaprico, Catharina Olsen, Matteo Tiberti, Elena Papaleo* A workflow to study mechanistic indicators for driver gene prediction with Moonlight, Briefings in Bioinformatics, 2023, bbad274, https://doi.org/10.1093/bib/bbad274

Documentation

please see the material included in the repository. The Moonlight2R vignette is publicly available on RPubs

Changes respect to MoonlightR

• The following user-facing functions were added to Moonlight2R:
  • DMA and plotDMA, for the new driver mutation analysis layer
  • GLS, for automated gene literature search for the most interesting identified driver genes
  • plotMoonlight function to generate a heatmap of Moonlight gene z-scores for selected genes
  • new helper functions: LiftMAF, MAFtoCscape, PRAtoTibble, RunCscape_somatic,confidence, plotHeatmap, and tabix_func
• Deprecation and removal of the following functions, which were available in MoonlightR: DPA and getDataTCGA. This means that users now needs to supply their own differential expression analysis results (see vignettes) to run predictions with Moonlight2R
• The moonlight function, which implements the whole Moonlight pipeline in a single function, was updated accordingly to the new changes in Moonlight2R
• Example data has been updated which follows changes in the functions. Specifically, the following data files have been added to Moonlight2R:DEG_Mutations_Annotations.rda, EncodePromoters.rda, LOC_protein.rda, LOC_transcription.rda,LOC_translation.rda, NCG.rda, Oncogenic_mediators_mutation_summary.rda, cscape_somatic_output.rda,dataDMA.rda, dataGLS.rda, and dataMAF.rda. The following data files were not included in Moonlight2R: GDCprojects.rda and geneInfo.rda as these files were connected to the deleted functions.
• the vignette has been updated in light of changes implemented in Moonlight2R

Installation

Installation from BioConductor

To install this package from the BioConductor repositories, start R (version "4.3") and enter:

if (!require("BiocManager", quietly = TRUE)) install.packages("BiocManager")

BiocManager::install("Moonlight2R")

Installation from GitHub

devtools::install_github(repo = "ELELAB/Moonlight2R")

Installation from GitHub with accompanying vignette

You need the BiocStyle Bioconductor package to install Moonlight2R with the vignette. This package can be installed like:

if (!require("BiocManager", quietly = TRUE)) install.packages("BiocManager")

BiocManager::install("BiocStyle")

To install Moonlight2R with its vignette:

devtools::install_github(repo = "ELELAB/Moonlight2R", build_vignettes = TRUE)

To view the vignette:

vignette( "Moonlight2R", package="Moonlight2R")

Installation of other requirements

To make the best out of Moonlight2R the user should download the CSCapeSomatic pre-computed scores. More detailed instructions are available in the INSTALL file