Hello,

I'm having trouble generating a dotplot of functionally enriched pathways across different groups. Most of them are mapped as NA via

Warning message: In order(as.numeric(unique(result$Cluster))) : NAs introduced by coercion

I'm trying to figure out why this happens. I've included the code to the original code I am adapting it from, retrieved from https://f1000research.com/articles/9-709. However, even if I follow their code, I get NAs, so I wonder if someone else can replicate it without NAs. I appreciate any help I can get!

Here is my code below:

    ## gprofiler 

    # load the package 
library(gprofiler2)

    # installing additional packages
    # if (!requireNamespace("BiocManager", quietly = TRUE))
    # install.packages("BiocManager") BiocManager::install(c("clusterProfiler", "enrichplot", "DOSE"))

    # loading the additional packages 
library(clusterProfiler) 
library(enrichplot) 
library(DOSE) # needed to convert to enrichResult object 
library(airway) 
library(DESeq2) 
library(gprofiler2)

    # load the airway data data(airway)
    # construct the DESeqDataSet object 
ddsMat = DESeqDataSetFromMatrix(countData = assay(airway),
                                    colData = colData(airway),
                                    design = ~ cell + dex)
    # run DESeq2 pipeline 
dds = DESeq(ddsMat)
    # get the results 
results = results(dds, contrast = c("dex", "trt", "untrt"),
                      alpha = 0.05, lfcThreshold = 1)
    # keep only the significant genes 
results_sig = subset(results, padj < 0.05)
    # get the significant up-regulated genes 
up = subset(results_sig, log2FoldChange > 0)
    # get the significant down-regulated genes 
down = subset(results_sig, log2FoldChange < 0)


    up_names = gconvert(row.names(up)) down_names = gconvert(row.names(down))

    # enrichment analysis using gene names 
multi_gp = gost(list("up-regulated" = up_names$name,
                         "down-regulated" = down_names$name), multi_query = FALSE, evcodes = TRUE)

    # modify the g:Profiler data frame 
gp_mod = multi_gp$result[,c("query", "source", "term_id",
                                "term_name", "p_value", "query_size", 
                                "intersection_size", "term_size", 
                                "effective_domain_size", "intersection")] 

gp_mod$GeneRatio = paste0(gp_mod$intersection_size,  "/", gp_mod$query_size)


    gp_mod$BgRatio = paste0(gp_mod$term_size, "/", gp_mod$effective_domain_size) names(gp_mod) = c("Cluster", "Category", "ID", "Description", "p.adjust", 
                      "query_size", "Count", "term_size", "effective_domain_size", 
                      "geneID", "GeneRatio", "BgRatio") 

gp_mod$geneID = gsub(",", "/", gp_mod$geneID) 
row.names(gp_mod) = gp_mod$ID

    # define as compareClusterResult object 
gp_mod_cluster = new("compareClusterResult", compareClusterResult = gp_mod)

    # define as enrichResult object 
gp_mod_enrich  = new("enrichResult", result = gp_mod)


    enrichplot::dotplot(gp_mod_cluster)