shake_gsenrichResult {GeneTonic} | R Documentation |
Convert a gseaResult object for straightforward use in GeneTonic()
shake_gsenrichResult(obj)
obj |
A |
This function is able to handle the output of clusterProfiler
's gseGO
and
GSEA
, as they both return an object of class gseaResult
- and this in turn
contains the information required to create correctly a res_enrich
object.
A data.frame
compatible for use in GeneTonic()
as res_enrich
Other shakers:
shake_davidResult()
,
shake_enrichResult()
,
shake_enrichrResult()
,
shake_fgseaResult()
,
shake_gprofilerResult()
,
shake_topGOtableResult()
# dds library("macrophage") library("DESeq2") data(gse) dds_macrophage <- DESeqDataSet(gse, design = ~ line + condition) rownames(dds_macrophage) <- substr(rownames(dds_macrophage), 1, 15) # res object data(res_de_macrophage, package = "GeneTonic") sorted_genes <- sort( setNames(res_macrophage_IFNg_vs_naive$log2FoldChange, res_macrophage_IFNg_vs_naive$SYMBOL), decreasing = TRUE ) ## Not run: library("clusterProfiler") library("org.Hs.eg.db") gsego_IFNg_vs_naive <- gseGO( geneList = sorted_genes, ont = "BP", OrgDb = org.Hs.eg.db, keyType = "SYMBOL", minGSSize = 10, maxGSSize = 500, pvalueCutoff = 0.05, verbose = TRUE ) res_enrich <- shake_gsenrichResult(gsego_IFNg_vs_naive) head(res_enrich) gtl_macrophage <- GeneTonic_list( dds = dds_macrophage, res_de = res_macrophage_IFNg_vs_naive, res_enrich = res_enrich, annotation_obj = anno_df ) ## End(Not run)