export_for_iSEE: export_for_iSEE

In GeneTonic: Enjoy Analyzing And Integrating The Results From Differential Expression Analysis And Functional Enrichment Analysis

Description

Combine data from a typical DESeq2 run

Usage

export_for_iSEE(dds, res_de)

Arguments

dds	A DESeqDataSet object.
res_de	A DESeqResults object.

Details

Combines the DESeqDataSet input and DESeqResults into a SummarizedExperiment object, which can be readily explored with iSEE.

A typical usage would be after running the DESeq2 pipeline and/or after exploring the functional enrichment results with GeneTonic()

Value

A SummarizedExperiment object, with raw counts, normalized counts, and variance-stabilizing transformed counts in the assay slots; and with colData and rowData extracted from the corresponding input parameters - mainly the results for differential expression analysis.

Examples

library("macrophage")
library("DESeq2")

# dds object
data("gse", package = "macrophage")
dds_macrophage <- DESeqDataSet(gse, design = ~line + condition)
rownames(dds_macrophage) <- substr(rownames(dds_macrophage), 1, 15)
dds_macrophage <- estimateSizeFactors(dds_macrophage)

# res object
data(res_de_macrophage, package = "GeneTonic")
res_de <- res_macrophage_IFNg_vs_naive

# now everything is in place to launch the app
# dds_macrophage <- DESeq2::DESeq(dds_macrophage)
se_macrophage <- export_for_iSEE(dds_macrophage, res_de)
# iSEE(se_macrophage)

GeneTonic documentation built on Nov. 8, 2020, 5:27 p.m.