CIBERSORT: CIBERSORT is an analytical tool developed by Newman et al. to...

In IOBR/IOBR: Immune Oncology Biological Research

CIBERSORT is an analytical tool developed by Newman et al. to provide an estimation of the abundances of member cell types in a mixed cell population, using gene expression data.

Description

CIBERSORT is an analytical tool developed by Newman et al. to provide an estimation of the abundances of member cell types in a mixed cell population, using gene expression data.

Usage

CIBERSORT(
  sig_matrix = lm22,
  mixture_file,
  perm,
  QN = TRUE,
  absolute,
  abs_method = "sig.score"
)

Arguments

sig_matrix	Cell type GEP barcode matrix: row 1 = sample labels; column 1 = gene symbols; no missing values; default =LM22.txt download from CIBERSORT (https://cibersort.stanford.edu/runcibersort.php)
mixture_file	GEP matrix: row 1 = sample labels; column 1 = gene symbols; no missing values
perm	Set permutations for statistical analysis (≥100 permutations recommended).
QN	Quantile normalization of input mixture (default = TRUE)
absolute	Run CIBERSORT in absolute mode (default = FALSE) - note that cell subsets will be scaled by their absolute levels and will not be represented as fractions (to derive the default output, normalize absolute levels such that they sum to 1 for each mixture sample) - the sum of all cell subsets in each mixture sample will be added to the ouput ('Absolute score'). If LM22 is used, this score will capture total immune content.
abs_method	if absolute is set to TRUE, choose method: 'no.sumto1' or 'sig.score' - sig.score = for each mixture sample, define S as the median expression level of all genes in the signature matrix divided by the median expression level of all genes in the mixture. Multiple cell subset fractions by S. - no.sumto1 = remove sum to 1 constraint

Value

A matrix object containing the estimated cibersort-cell fractions, p-values, correlation coefficients, and RMSE values.

Author(s)

Aaron M. Newman, Stanford University ([e-mail])

Examples

data("eset_gse62254", package = "IOBR")
cibersort<-CIBERSORT(sig_matrix = lm22, mixture_file = eset_gse62254, perm = 100, QN=TRUE, absolute=FALSE)
head(cibersort)

IOBR/IOBR documentation built on Nov. 13, 2024, 5:22 a.m.