run.pca: Run PCA on the main data

In rezakj/iCellR: Analyzing High-Throughput Single Cell Sequencing Data

Run PCA on the main data

Description

This function takes an object of class iCellR and runs PCA on the main data.

Usage

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"
)

Arguments

x	An object of class iCellR.
data.type	Choose from "main" and "imputed", default = "main"
method	Choose from "base.mean.rank" or "gene.model", default is "base.mean.rank". If gene.model is chosen you need to provide gene.list.
top.rank	A number. Taking the top genes ranked by base mean, default = 500.
plus.log.value	A number to add to each value in the matrix before log transformasion to aviond Inf numbers, default = 0.1.
scale.data	If TRUE the data will be scaled (log2 + plus.log.value), default = TRUE.
gene.list	A charactor vector of genes to be used for PCA. If "clust.method" is set to "gene.model", default = "my_model_genes.txt".

Value

An object of class iCellR.

rezakj/iCellR documentation built on March 29, 2024, 6:55 p.m.