This Github repo contains the code needed to download and preprocess the data, build the SVM classifier and regenerate all the figures associated with the publication RAS oncogenic activity predicts response to chemotherapy and outcome in lung adenocarcinoma
First step, clone the repo.
git clone https://github.com/FrancisCrickInstitute/RAS84.git
cd RAS84
To run the analysis code you will need R-3.6.0
installed along with
the libraries contained in renv.lock
. The renv
environment can be
reinitialised
by running R
within the RAS84
directory and running renv::restore()
data/scripts
contains shell scripts to download each of the
dependent datasets. The paths are configured to run these scripts from
within data/scripts
. Raw data files are downloaded to
data/downloads
There are also R scripts to preprocess the raw data and build
SummarizedExperiment
objects. The SE objects are written to
data/objects
The following analysis Rmd
scripts can be found in the top level of
the repo.
-
1_build_RAS84_CCLE.Rmd - The CCLE analysis to build RAS84 from the parent signatures
-
2_drug_screen_GDSC_CTRP_CCLE.Rmd - The CCLE drug screen analysis
-
3_RAS84_patient_classification_TCGA_LUAD.Rmd - TCGA LUAD classification analysis
-
4_RAS84_RAG_mutation_analysis_TCGA_LUAD.Rmd - TCGA LUAD RAS Activity Group (RAG) mutation analysis
-
5_survival_analysis_TCGA_LUAD.Rmd - TCGA LUAD and Uppsala survival analysis
-
6_RAS84_pancancer_analysis_TCGA.Rmd - TCGA pancancer RAS84 analysis
-
7_RAS84_pancancer_survival_analysis.Rmd - TCGA pancancer RAS84 survival analysis
-
build_SVM.R - SVM build script
All the Rmd
scripts contain global variables in the first code block
that set the paths to the required data resources and output paths for the
figures. All the defined data resources must be downloaded and build
using the download and init scripts described above before the
analysis scripts can be run. All figures are written to figures/
.