Workflow code supporting the manuscript 'Utilizing cohort-level and individual networks to predict best response in patients with metastatic triple negative breast cancer'
Retrieve the below files and place them in the corresponding directory
data/annotation- gencode.v24.annotation.gtf.gz
- h.all.v7.5.1.symbols.gmt
- Cell_marker_Human.xlsx
10780432ccr173509-sup-192911_3_supp_4675335_p6rxmz.xlsx- This is Table S1 from Tamborero et al 2018
data/bursteinTNBC_Ding_77_gene_signatures.txtderived from Table S1
data/tcgadata/zhang- bcell_wrkbk.xlsx derived from Zhang et al 2021
- Copy the gene list embedded in the 'Survival analysis' section of the 'Method details' into an Excel file with two columns: signature and genes
- bcell_wrkbk.xlsx derived from Zhang et al 2021
data/metabric- Download the following files from https://www.cbioportal.org/study/summary?id=brca_metabric:
data_clinical_patient.txtdata_clinical_sample.txtdata_mrna_agilent_microarray.txt
- Download the following files from https://www.cbioportal.org/study/summary?id=brca_metabric:
data/amtecanddata/wgcna- Request access to these files
#CRAN:
install.packages(c("data.table", "targets", "tidymodels",
"openxlsx", "ggplot2", "stringr", "ggrepel", "WGCNA",
"caret", "partykit", "patchwork", "viridis", "ggsurvfit"))
#BioConductor
##May need to install "BiocManager" first from CRAN
BiocManager::install(c("limma", "edgeR", "sva", "GSVA", "ComplexHeatmap"))mkdir output
mkdir figurestargets::tar_make()GNU General Public License v3.0
This code was developed by Daniel Bottomly, a member of the McWeeney Lab and is protected under copyright by the Oregon Health and Science University Knight Cancer Institute, 2024.