Load data

We load the scRNA data of three samples MGH102 , MGH104 and MGH105 from the public dataset of Gliobastoma (GSE131928)

load(url("https://www.dropbox.com/s/6zns12amobs39g8/HNSCC26_data.RData?raw=1"))

Run pipeline

We run the pipeline that performs the classification of malignant and non-malignant cells of each sample and then the compare the inferred copy number between the different samples.

library(SCEVAN)
listCountMtx <- list(primary = count_mtx_prim, lymph = count_mtx_lymph)
results <- SCEVAN::multiSampleComparisonClonalCN(listCountMtx, analysisName = "HeadNeck", organism = "human" , par_cores = 20)
## [1] " raw data - genes: 23686 cells: 130"
## [1] "1) Filter: cells > 200 genes"
## [1] "2) Filter: genes > 10% of cells"
## [1] "10262 genes past filtering"
## [1] "3) Annotations gene coordinates"
## [1] "found 2 confident non malignant cells"
## [1] "9266 genes annotated"
## [1] "4) Filter: genes involved in the cell cycle"
## [1] "8774 genes past filtering "
## [1] "5)  Filter: cells > 5genes per chromosome "
## [1] "6) Log Freeman Turkey transformation"
## [1] "A total of 130 cells, 8774 genes after preprocessing"
## [1] "7) Measuring baselines (confident normal cells)"
## [1] "8) Smoothing data"
## [1] "9) Segmentation (VegaMC)"
## [1] "10) Adjust baseline"
## [1] "11) plot heatmap"
## [1] "found 58 tumor cells"
## [1] "time classify tumor cells:  35.5675704479218"
## [1] " raw data - genes: 23686 cells: 298"
## [1] "1) Filter: cells > 200 genes"
## [1] "2) Filter: genes > 10% of cells"
## [1] "12199 genes past filtering"
## [1] "3) Annotations gene coordinates"
## [1] "found 3 confident non malignant cells"
## [1] "10954 genes annotated"
## [1] "4) Filter: genes involved in the cell cycle"
## [1] "10429 genes past filtering "
## [1] "5)  Filter: cells > 5genes per chromosome "
## [1] "6) Log Freeman Turkey transformation"
## [1] "A total of 298 cells, 10429 genes after preprocessing"
## [1] "7) Measuring baselines (confident normal cells)"
## [1] "8) Smoothing data"
## [1] "9) Segmentation (VegaMC)"
## [1] "10) Adjust baseline"
## [1] "11) plot heatmap"
## [1] "found 222 tumor cells"
## [1] "time classify tumor cells:  48.9024002552032"

Output

The pipeline returns in results a data frame containing for each sample the classification (tumor/normal)

Copy Number (compareClonalCN.png)

Copy Number of each sample.

heatmap

OncoPrint-like plot (OncoHeat.png)

OncoPrint-like plot that highlighting specific alteration, shared alteration between subclones, or clonal alteration.

heatmap