get_aggrscores {GeneTonic} | R Documentation |
Computes for each gene set in the res_enrich
object a Z score and an aggregated
score (using the log2FoldChange values, provided in the res_de
)
get_aggrscores(res_enrich, res_de, annotation_obj, gtl = NULL, aggrfun = mean)
res_enrich |
A |
res_de |
A |
annotation_obj |
A |
gtl |
A |
aggrfun |
Specifies the function to use for aggregating the scores for
each term. Common values could be |
A data.frame
with the same columns as provided in the input, with
additional information on the z_score
and the aggr_score
for each gene set.
This information is used by other functions such as gs_volcano()
or
enrichment_map()
gs_volcano()
and enrichment_map()
make efficient use of the computed
aggregated scores
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 )