GeneTonic: GeneTonic

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

Description

GeneTonic, main function for the Shiny app

Usage

GeneTonic(dds, res_de, res_enrich, annotation_obj, project_id = "")

Arguments

dds	A DESeqDataSet object, normally obtained after running your data through the DESeq2 framework.
res_de	A DESeqResults object. As for the dds parameter, this is also commonly used in the DESeq2 framework.
res_enrich	A data.frame object, storing the result of the functional enrichment analysis. Required columns for enjoying the full functionality of GeneTonic() include: a gene set identifier (e.g. GeneOntology id, gs_id) and its term description (gs_description) a numeric value for the significance of the enrichment (gs_pvalue) a column named gs_genes containing a comma separated vector of the gene names associated to the term, one for each term the number of genes in the geneset of interest detected as differentially expressed (gs_de_count), or in the background set of genes (gs_bg_count) See shake_topGOtableResult() or shake_enrichResult() for examples of such formatting helpers
annotation_obj	A data.frame object, containing two columns, gene_id with a set of unambiguous identifiers (e.g. ENSEMBL ids) and gene_name, containing e.g. HGNC-based gene symbols. This object can be constructed via the org.eg.XX.db packages, e.g. with convenience functions such as pcaExplorer::get_annotation_orgdb().
project_id	A character string, which can be considered as an identifier for the set/session, and will be e.g. used in the title of the report created via happy_hour()

Value

A Shiny app object is returned, for interactive data exploration

Author(s)

Federico Marini

Examples

library("macrophage")
library("DESeq2")
library("org.Hs.eg.db")
library("AnnotationDbi")

# 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)

# annotation object
anno_df <- data.frame(
  gene_id = rownames(dds_macrophage),
  gene_name = mapIds(org.Hs.eg.db,
                     keys = rownames(dds_macrophage),
                     column = "SYMBOL",
                     keytype = "ENSEMBL"),
  stringsAsFactors = FALSE,
  row.names = rownames(dds_macrophage)
)

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

# res_enrich object
data(res_enrich_macrophage, package = "GeneTonic")
res_enrich <- shake_topGOtableResult(topgoDE_macrophage_IFNg_vs_naive)
res_enrich <- get_aggrscores(res_enrich, res_de, anno_df)

# now everything is in place to launch the app
if (interactive())
  GeneTonic(dds = dds_macrophage,
            res_de = res_de,
            res_enrich = res_enrich,
            annotation_obj = anno_df,
            project_id = "myexample")

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