example: Normalized RNA-seq count data

In AbsFilterGSEA: Improved False Positive Control of Gene-Permuting GSEA with Absolute Filtering

Description

This is toy example of RNA-seq raw read count table. It containes 5000 genes and 6 samples (three for case and other three for control group).

Usage

data("example")

Format

A data frame with 5000 observations on the following 6 variables.

groupA1

a numeric vector for RNA-seq counts for case samples 1.

groupA2

a numeric vector for RNA-seq counts for case samples 2.

groupA3

a numeric vector for RNA-seq counts for case samples 3.

groupB1

a numeric vector for RNA-seq counts for control samples 1.

groupB2

a numeric vector for RNA-seq counts for control samples 2.

groupB3

a numeric vector for RNA-seq counts for control samples 3.

Details

This read count dataset was simulated based on the negative binomial distribution. Mean and dispersion parameters were assessed from TCGA KIRC RNA-seq dataset. Normalization was done by using edgeR package.Geneset_41~45 are up-regulated and Geneset_46~50 are down-regulated gene sets.

Source

Cancer Genome Atlas Research, N. Comprehensive molecular characterization of clear cell renal cell carcinoma. Nature 2013;499(7456):43-49.

References

Chen, Y., et al. edgeR: differential expression analysis of digital gene expression data User's Guide. 2015.

Examples

data(example)

AbsFilterGSEA documentation built on May 2, 2019, 1:28 p.m.