Genomic, transcriptomic, and immunogenomic landscape of over 1,300 sarcomas of diverse histology subtypes: A report from the ORIEN collaborative network

This repository contains code to reproduce the results of the manuscript "Genomic, transcriptomic, and immunogenomic landscape of over 1,300 sarcomas of diverse histology subtypes: a report from the ORIEN collaborative network". The manuscript can be obtained from [LINK/DOI].

Data used in this code is not contained in this repository and is managed by the ORIEN network. When feasible, we have include an example file to help the reader understand the code. Analysis of copy number variation and mutational data was carried out by Dr. Alex Soupir. Analyses of gene expression data were carried out by Oscar Ospina.

Data Analyses

somatic_mutations

Processing of somatic mutation data from the ORIEN network's sarcoma cohort can be found in the somatic_mutations folder. This includes the filtering of VCF somatic mutation files, annotation with AnnoVar, and then comparision/plots of the resulting somatic mutations.

copy_number

Scripts for using both gene- and segment-level copy number can be found in the copy_number folder. Code at the bottom of 5.0.Comparing_total_perMB.R is modified from the compareTCGA() function within the maftools package to handle samples with differing capture technologies/lengths.

fusions

Fusion data was processed after all other scripts were written then used to update the clinical information with histology reassignments. After updating, all scripts were rerun with the update histology subtypes.

gene_expression_analyses

The Gene expression analyses folder contains code to perform exploratory data analysis, unsupervised clustering, differential gene expression, and gene set enrichment analysis of the sarcoma RNAseq samples in the cohort. Code is also provided for immune cell type deconvolution and survival analysis using Cox models.

• gene_expression_analyses_code/sarcoma_manuscript_figures.Rmd: Code to reproduce the figures pertaining to RNAseq analysis. The script takes outputs from other scripts included here.
• gene_expression_analyses_code/sarcoma_avatar_rnaseq_mcpdeconv.Rmd: Code to reproduce the immune cell type abundance estimation using devonvolution with MCPcounter.
• gene_expression_analyses_code/differential_expression_immunegroups.Rmd: Code to reproduce the differential gene expression analysis among the MCPcounter-predicted groups.
• gene_expression_analyses_code/differential_expression_histologies.Rmd: Code to reproduce the differential gene expression analysis among the histologies in the data set.
• gene_expression_analyses_code/gene_set_enrichment_immunegroups.Rmd: Code to reproduce the estimation of gene set enrichment scores for each MCPcounter-predicted group.
• gene_expression_analyses_code/gene_set_enrichment_histologies.Rmd: Code to reproduce the estimation of gene set enrichment scores for each histology in the data set.

Analysis Softwares

For somatic mutations, copy number, and fusions:

• System programs

  • R v4.3.0
  • Python v3.9.12
  • BEDTools v2.30.0
  • BCFtools v1.12
  • table_annovar.pl v2020-06-08
  • samtools v1.6
  • htslib v1.6
  • perl v5.22.0

• R Packages

  • maftools v2.16.0
  • tidyverse v2.0.0
  • openxlsx v4.2.5.2
  • vcfR v1.15.0
  • data.table v1.15.4
  • parallel v4.3.0
  • plotly v4.10.3
  • pals v1.8
  • ComplexHeatmap v2.16.0
  • pbmcapply v1.5.1
  • patchwork v1.1.3
  • MCPcounter v1.2.0
  • fgsea v1.28.0
  • survival v3.5
  • survminer v0.4.9
  • limma v3.58.1
  • umap v0.2.10
  • msigdbr v7.5.1
  • dynamicTreeCut v1.63

• Python libraries

  • HTSeq v2.0.2
  • pandas v1.5.2