e50-estimateScore: Calculation of stromal, immune, and ESTIMATE scores

Description Usage Arguments Details Value Author(s) References Examples

Description

This function computes stromal, immune, and ESTIMATE scores per sample using gene expression data.

Usage

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estimateScore(input.ds,
              output.ds,
              platform = c("affymetrix", "agilent", "illumina"))

Arguments

input.ds

character string specifying name of input GCT file containing stromal, immune, and estimate scores for each sample

output.ds

character string specifying name of output file

platform

character string indicating platform type. Defaults to "affymetrix"

Details

This method is based on single sample gene set enrichment analysis (ssGSEA) algorithm. This function computes stromal, immune, and ESTIMATE scores using gene-level expression data. For Affymetrix platform data, tumor purity are derived from ESTIMATE scores by applying non-linear squares methods to TCGA Affymetrix expression data (n=995).

Value

Returns data.frame with components:

Author(s)

Kosuke Yoshihara kyoshihara@mdanderson.org

References

Subramanian A, et al.
"Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles."
Proc Natl Acad Sci U S A 2005, 102:15545-15550.

Barbie DA, et al.
" Systematic RNA interference reveals that oncogenic KRAS-driven cancers require TBK1."
Nature 2009, 462:108-112.

Verhaak RG, et al.
" Integrated genomic analysis identifies clinically relevant subtypes of glioblastoma characterized by abnormalities in PDGFRA, IDH1, EGFR, and NF1."
Cancer Cell 2010, 17:98-110.

Carter SL, et al.
"Absolute quantification of somatic DNA alterations in human cancer."
Nat Biotechnol 2012, 30:413-421.

Examples

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in.file <- system.file("extdata", "sample_input.gct", package="estimate")
out.file <- tempfile(pattern="estimate", fileext=".gct")
estimateScore(in.file, out.file)

estimate documentation built on May 2, 2019, 4:38 p.m.