pipelineCNA | R Documentation |
pipelineCNA Executes the entire SCEVAN pipeline that classifies tumour and normal cells from the raw count matrix, infer the clonal profile of cancer cells and looks for possible sub-clones in the tumour cell matrix automatically analysing the specific and shared alterations of each subclone and a differential analysis of pathways and genes expressed in each subclone.
pipelineCNA( count_mtx, sample = "", par_cores = 20, norm_cell = NULL, SUBCLONES = TRUE, beta_vega = 0.5, ClonalCN = FALSE, plotTree = FALSE, AdditionalGeneSets = NULL, SCEVANsignatures = TRUE )
count_mtx |
raw count matrix |
sample |
sample name (optional) |
par_cores |
number of cores (default 20) |
norm_cell |
vector of normal cells if already known (optional) |
SUBCLONES |
find subclones (default TRUE) |
beta_vega |
specifies beta parameter for segmentation, higher beta for more coarse-grained segmentation. (default 0.5) |
ClonalCN |
clonal profile inference from tumour cells (optional) |
plotTree |
find subclones (optional) |
AdditionalGeneSets |
list of additional signatures of normal cell types (optional) |
SCEVANsignatures |
FALSE if you only want to use only the signatures specified in AdditionalGeneSets (default TRUE) |
res_pip <- pipelineCNA(count_mtx)
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