This repository contains the code & data for the bulk analysis included the G34R/V HGG manuscript (Chen, Deshmukh, Jessa, Hadjadj, et al, Cell, 2020), for the analysis that was performed by our lab.

This repository is meant to enhance the STAR Methods section by providing code for the custom analyses in the manuscript and the exact R dependencies, in order to improve reproducibility for the main results. However, it is not a fully executable workflow. The code is permanently archived on Zenodo at the doi 10.5281/zenodo.7086446.

NOTE: if viewing on GitHub, only code is visible, as inputs, data, and outputs are generally not tracked in git.

Contents:

• Directory organization
• Map from figures to code
• Notes for reproducibility
• GitHub / version control

• reference_datasets: data, code, and processed outputs for scRNAseq normal brain reference datasets, with one sub-directory per publication. For external publications, the process of obtaining or deriving cluster markers used in later analysis is recorded here.
• bulk_transcriptome_epigenome: data, code, figures and output for bulk RNA-seq and ChIP-seq analysis of patient tumors and tumor-derived cell lines.
  • Gene expression in bulk RNAseq
  • GSEA enrichment of developmental signatures in tumor RNAseq
  • Integration of ChIPseq & RNAseq
  • Analysis of RNAseq data from isogenic cell lines
  • Virtual 4C from HiC data
  • Custom functions used within these analyses are stored in functions.R and ssgsea.R
• singlecell_normal: data, code, figures and output for analysis of the scRNAseq normal brain data
  • Analysis of gene expression along normal interneuron pseudotime
  • Bubbleplots of interneuron genes in the normal brain
  • Co-expression of astrocyte/interneuron expression in normal brain & tumors
  • Custom functions used within these analyses are stored in functions.R
• renv: directory maintained by the R package renv, containing the isolated project specific library
• include: shared templates, Rmd/HTML headers/footers, and R functions used throughout the analysis

This section contains a pointer from each figure in the paper to the section (§) where it's generated in the code. For each figure panel, I provide a partial path to the RMD/MD/HTML files within this repository/directory, and then the section in the rendered HTML which specifically produces that panel. As described below in the section on reproducibility, the source data for the figure is typically saved alongside the figure itself.

• Figure 2A: bulk_transcriptome_epigenome/02-GSEA..., § 6.1.1 Forebrain reference
• Figure 2C: bulk_transcriptome_epigenome/02-GSEA..., § 6.1.2 Striatal SVZ
• Figure 2D: bulk_transcriptome_epigenome/01-bulk_RNAseq_pipeline... § 4.3.2 Lineage specific TFs
• Figure 2E: bulk_transcriptome_epigenome/03-ChIPseq..., § 4.2.1 DGE
• Figure 2F: singlecell_normal/analysis/01-interneuron_pseudotime...,
  • top panel § 4.1 Cell type density along normal interneuron differentiation trajectory
  • bottom panel § 4.2 Plot genes of interest along pseudotime

• Figure S2A: bulk_transcriptome_epigenome/02-GSEA..., § 6.2 GSEA enrichment plots
• Figure S2B: bulk_transcriptome_epigenome/02-GSEA..., § 6.4 Confirmation of signal by direct expression of gene programs
• Figure S2D: bulk_transcriptome_epigenome/02-GSEA..., § 6.1.3 Adult V-SVZ
• Figure S2E: bulk_transcriptome_epigenome/01-bulk_RNAseq_pipeline... § 4.3.2 Lineage specific TFs

• Figure 3A: bulk_transcriptome_epigenome/analysis/04-isogenic_cell_lines...,
  • top panel § 4.4.3 Targeted DGE, for stem condition - GBM002
  • bottom panel § 4.4.2 Targeted DGE, for serum condition - GBM002
• Figure 3C: bulk_transcriptome_epigenome/analysis/04-isogenic_cell_lines... § 4.5.4 Visualize results
• Figure 3D: singlecell_normal/analysis/02-gene_bubbleplots...,
  • left § 4.1 Mouse developing forebrain
  • right § 4.3 Striatal SVZ

• Figure S5A: bulk_transcriptome_epigenome/01-bulk_RNAseq_pipeline... § 4.4.1 G34 mutants
• Figure S5B: singlecell_normal/analysis/02-gene_bubbleplots..., § 4.2 Human

• Figure 5D: singlecell_normal/analysis/03-astrocyte_interneuron_coexpression..., § 5.3 Developing mouse forebrain and 5.4 H3G34R/V tumors

• Figure S6C: singlecell_normal/analysis/03-astrocyte_interneuron_coexpression..., § 5.2 Human fetal telencephalon

This repository uses the rr template, which contains a set of R markdown templates to help ensure reproducibility. This template also provides a set of helper functions (located in rr_helpers.R and prefixed by rr_ in the function name) to help encourage documentation.

The R library for this project is managed with the package renv, which:

1. maintains an isolated project-specific library in the renv folder,
2. stores packages according to version
3. records the R, Bioconductor, and package versions in the file renv.lock, which can be used to reproduce the R package environment elsewhere

The R version used is 3.5.1. The analysis also makes use of our in-house package for scRNAseq visualization, cytobox.

Each markdown/HTML file has a "Reproducibility report" at the bottom, indicating when the document was last rendered, the most recent git commit when it was rendered, the seed, and the R session info.

For most figures, the source data underlying the plot is saved along side the figure in the respective figures directory. If so, a message is displayed in the markdown/HTML files underneath the chunk which produces the plot, giving the path for the figures/source data within this project directory.

e.g. [figure/source data @ G34-gliomas/bulk_transcriptome_epigenome/figures/01/gsx2_pdgfra_correlation…]

For most text file & R object outputs, there is a text file saved next to the object with the extension .desc, with a very brief one-line description of what's contained in the file.

e.g. for the output file bulk_transcriptome_epigenome/output/02/fgsea_df.tsv, there is an associated description file bulk_transcriptome_epigenome/output/02/fgsea_df.desc

This directory is tracked with git and has an associated GitHub repository in the Kleinman lab account at https://github.com/fungenomics/G34-gliomas.

The following are tracked / available on GitHub:

• .Rmd files, containing the code, and .md files, containing code and outputs
• Figures in png format
• Certain output files (tsv/Rda/Rds), if they're small
• The brief desc files for otputs
• The lockfile produced by the renv package

The following are not tracked / available on GitHub:

• Figures in pdf format, and figure source data
• Raw data and large analysis output / processed data files
• The actual packages in the R library

Selin Jessa (selin.jessa at mail.mcgill.ca)