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This function takes an object of class iCellR and runs PCA on the main data.
run.pca( x = NULL, data.type = "main", method = "base.mean.rank", top.rank = 500, plus.log.value = 0.1, scale.data = TRUE, gene.list = "character" )
An object of class iCellR.
Choose from "main" and "imputed", default = "main"
Choose from "base.mean.rank" or "gene.model", default is "base.mean.rank". If gene.model is chosen you need to provide gene.list.
A number. Taking the top genes ranked by base mean, default = 500.
A number to add to each value in the matrix before log transformasion to aviond Inf numbers, default = 0.1.
If TRUE the data will be scaled (log2 + plus.log.value), default = TRUE.
A charactor vector of genes to be used for PCA. If "clust.method" is set to "gene.model", default = "my_model_genes.txt".
# NOT RUN { demo.obj <- run.pca(demo.obj, method = "gene.model", gene.list = demo.obj@gene.model) head(demo.obj@pca.data)[1:5] # }
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