make.gene.model {iCellR} | R Documentation |
This function takes an object of class iCellR and provides a gene list for clustering based on the parameters set in the model.
make.gene.model( x = NULL, dispersion.limit = 1.5, base.mean.rank = 500, gene.num.max = 2000, non.sig.col = "darkgray", right.sig.col = "chartreuse3", left.sig.col = "cadetblue3", disp.line.col = "black", rank.line.col = "red", my.out.put = "data", cell.size = 1.75, cell.transparency = 0.5, no.mito.model = TRUE, no.cell.cycle = TRUE, mark.mito = TRUE, interactive = TRUE, out.name = "plot" )
x |
An object of class iCellR. |
dispersion.limit |
A number for taking the genes that have dispersion above this number, default = 1.5. |
base.mean.rank |
A number taking the top genes ranked by base mean, default = 500. |
gene.num.max |
Maximum number of genes , default = 2000. |
non.sig.col |
Color for the genes not used for the model, default = "darkgray". |
right.sig.col |
Color for the genes above the dispersion limit, default = "chartreuse3". |
left.sig.col |
Color for the genes above the rank limit, default = "cadetblue3". |
disp.line.col |
Color of the line for dispersion limit, default = "black". |
rank.line.col |
Color of the line for rank limit, default = "red". |
my.out.put |
Chose from "data" or "plot", default = "data". |
cell.size |
A number for the size of the points in the plot, default = 1.75. |
cell.transparency |
Color transparency for the points in the plot, default = 0.5. |
no.mito.model |
If set to TRUE, mitochondrial genes would be excluded from the gene list made for clustering, default = TRUE. |
no.cell.cycle |
If TRUE the cell cycle genes will be removed (s.phase and g2m.phase), default = TRUE. |
mark.mito |
Mark mitochondrial genes in the plot, default = TRUE. |
interactive |
If set to TRUE an interactive HTML file will be created, default = TRUE. |
out.name |
If "interactive" is set to TRUE, the out put name for HTML, default = "plot". |
An object of class iCellR.
make.gene.model(demo.obj, dispersion.limit = 1.5, base.mean.rank = 500, no.mito.model = TRUE, mark.mito = TRUE, interactive = FALSE, my.out.put = "plot", out.name = "gene.model") demo.obj <- make.gene.model(demo.obj, dispersion.limit = 1.5, base.mean.rank = 500, no.mito.model = TRUE, mark.mito = TRUE, interactive = FALSE, out.name = "gene.model") head(demo.obj@gene.model)