Commit 3ba0c079 authored by Lena Hersemann's avatar Lena Hersemann

updated numbering, removed comment

parent 75610eeb
......@@ -66,7 +66,7 @@ resultsBaseName <- if (str_length(opts$project) > 0) paste0(opts$project, ".") e
q_cutoff <- as.numeric(opts$qcutoff)
########################################################################################################################
#' ## Enrichment Analysis
#' # Enrichment Analysis
#' Run configuration was
vec_as_df(unlist(opts)) %>%
......@@ -97,7 +97,7 @@ annoDb <- guess_anno_db(geneLists$ensembl_gene_id) # e.g. "org.Hs.eg.db"
## supported ids
#idType("org.Hs.eg.db")
#' ### Convert to entrez gene ids
#' ## Convert to entrez gene ids
install_package("clusterProfiler")
......@@ -361,7 +361,7 @@ session::save.session(".cp_enrichment.dat");
# session::restore.session(".cp_enrichment.dat");
########################################################################################################################
#' ## Enriched KEGG Pathways
#' # Enriched KEGG Pathways
#' To understand spatio-temporal changes in gene expression better we now overlay enriched kegg pathways with the -log10(q_value) of each contrast. The direction of the expression changes is encoded as color, whereby red indicates that sample_1 is overexpressed. Because we have multiple contrasts of interest, this defines a slice-color barcode for each gene. To relate the barcode to contrasts we define the following slice order:
hasEnrPathways=(!is.null(opts$overlay_expr_data) & (nrow(enrResults %>% filter(ontology=="kegg")) >0))
......@@ -506,7 +506,7 @@ pathwayPlots <- pathwayPlots[lapply(pathwayPlots, is.character) == 0]
# pathwayPlots[!map_lgl(pathwayPlots, ~ file.exists(.$plotfile))] %>% map("pathway_id")
# purriefied solution: discard(pathwayPlots, ~ file.exists(.$plotfile)) %>% map("pathway_id")
#' make sure that all files exist
# make sure that all files exist
stopifnot(map_lgl(pathwayPlots, ~ file.exists(.$plotfile)) %>% all)
......
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