README.md

AMTEC Manuscript Workflow

Workflow code supporting the manuscript 'Utilizing cohort-level and individual networks to predict best response in patients with metastatic triple negative breast cancer'

Required files

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/burstein
  • TNBC_Ding_77_gene_signatures.txt derived from Table S1
• data/tcga
  • TCGA_BRCA_counts.tsv.gz
  • TCGA_BRCA_tpm.tsv.gz
  • TCGA_ID_MAP.csv
  • brca_tcga_pan_can_atlas_2018_clinical_data.tsv
• data/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
• data/metabric
  • Download the following files from https://www.cbioportal.org/study/summary?id=brca_metabric:
    • data_clinical_patient.txt
    • data_clinical_sample.txt
    • data_mrna_agilent_microarray.txt
• data/amtec and data/wgcna - Request access to these files

Installation

#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"))

Pipeline Execution

mkdir output 
mkdir figures

targets::tar_make()

Licensing

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.