Convert an enrichResult object for straightforward use in GeneTonic()
shake_enrichResult(obj)
A data.frame
compatible for use in GeneTonic()
as res_enrich
This function is able to handle the output of clusterProfiler
and reactomePA
,
as they both return an object of class enrichResult
- and this in turn
contains the information required to create correctly a res_enrich
object.
Other shakers:
shake_davidResult()
,
shake_enrichrResult()
,
shake_fgseaResult()
,
shake_gprofilerResult()
,
shake_gsenrichResult()
,
shake_topGOtableResult()
# dds
library("macrophage")
library("DESeq2")
data(gse)
dds_macrophage <- DESeqDataSet(gse, design = ~ line + condition)
#> using counts and average transcript lengths from tximeta
rownames(dds_macrophage) <- substr(rownames(dds_macrophage), 1, 15)
# res object
data(res_de_macrophage, package = "GeneTonic")
res_de <- res_macrophage_IFNg_vs_naive
de_symbols_IFNg_vs_naive <- res_macrophage_IFNg_vs_naive[
(!(is.na(res_macrophage_IFNg_vs_naive$padj))) &
(res_macrophage_IFNg_vs_naive$padj <= 0.05), "SYMBOL"
]
bg_ids <- rowData(dds_macrophage)$SYMBOL[rowSums(counts(dds_macrophage)) > 0]
if (FALSE) { # \dontrun{
library("clusterProfiler")
library("org.Hs.eg.db")
ego_IFNg_vs_naive <- enrichGO(
gene = de_symbols_IFNg_vs_naive,
universe = bg_ids,
keyType = "SYMBOL",
OrgDb = org.Hs.eg.db,
ont = "BP",
pAdjustMethod = "BH",
pvalueCutoff = 0.01,
qvalueCutoff = 0.05,
readable = FALSE
)
res_enrich <- shake_enrichResult(ego_IFNg_vs_naive)
head(res_enrich)
} # }