Intratumoral Heterogeneity in Glioblastoma

Introduction

This vignette demonstrates SCEVAN’s ability to detect intratumoral heterogeneity in a glioblastoma sample. We analyze the MGH106 sample from the public dataset GSE131928.

Load Data

# Load scRNA data of MGH106 sample from GSE131928
load(url("https://www.dropbox.com/s/b9udpvhnc2ez9pc/MGH106_data.RData?raw=1"))

# Check dimensions
dim(count_mtx)

Run Pipeline

Run the complete SCEVAN pipeline with subclone detection enabled:

library(SCEVAN)

results <- pipelineCNA(
  count_mtx, 
  sample = "MGH106", 
  par_cores = 20, 
  SUBCLONES = TRUE, 
  plotTree = TRUE
)

Results

The pipeline returns a data frame containing: - Cell classification (tumor/normal) - Confident normal cell status - Subclone assignment

head(results)

Output files are saved to ./output/:

list.files(path = "./output", pattern = "MGH106")

Output Visualizations

1. Classification Heatmap

Heatmap showing CNA matrix with malignant/non-malignant classification:

File: MGH106heatmap.png

2. Subclone Heatmap

CNA matrix colored by clonal subpopulations:

File: MGH106heatmap_subclones.png

3. Phylogenetic Tree

Clonal tree inferred from subclone profiles:

File: MGH106CloneTree.png

4. Consensus Plot

Compact visualization of alterations per subpopulation:

File: MGH106consensus.png

5. OncoPrint Plot

Shows specific, shared, and clonal alterations:

File: MGH106OncoHeat2.png

6. Differential Expression

Volcano plots from DE analysis of genes in specific alterations:

Files: MGH106-DEchr*_subclones.png

7. Pathway Analysis

REACTOME pathway activity via GSEA for each subclone:

Files: MGH106pathwayAnalysis_subclones*.png

Summary

SCEVAN successfully:

  1. Classified cells into tumor and normal populations
  2. Identified multiple tumor subclones
  3. Characterized subclone-specific copy number alterations
  4. Performed differential expression analysis
  5. Generated pathway enrichment results

Session Info

sessionInfo()
## R version 4.6.1 (2026-06-24)
## Platform: x86_64-pc-linux-gnu
## Running under: Ubuntu 26.04 LTS
## 
## Matrix products: default
## BLAS:   /usr/lib/x86_64-linux-gnu/openblas-pthread/libblas.so.3 
## LAPACK: /usr/lib/x86_64-linux-gnu/openblas-pthread/libopenblasp-r0.3.32.so;  LAPACK version 3.12.0
## 
## locale:
##  [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
##  [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8    
##  [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
##  [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
##  [9] LC_ADDRESS=C               LC_TELEPHONE=C            
## [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       
## 
## time zone: Etc/UTC
## tzcode source: system (glibc)
## 
## attached base packages:
## [1] stats     graphics  grDevices utils     datasets  methods   base     
## 
## other attached packages:
## [1] rmarkdown_2.31
## 
## loaded via a namespace (and not attached):
##  [1] digest_0.6.39    R6_2.6.1         fastmap_1.2.0    xfun_0.59       
##  [5] maketools_1.3.2  cachem_1.1.0     knitr_1.51       htmltools_0.5.9 
##  [9] buildtools_1.0.0 lifecycle_1.0.5  cli_3.6.6        sass_0.4.10     
## [13] jquerylib_0.1.4  compiler_4.6.1   sys_3.4.3        tools_4.6.1     
## [17] evaluate_1.0.5   bslib_0.11.0     yaml_2.3.12      otel_0.2.0      
## [21] jsonlite_2.0.0   rlang_1.2.0