In csbl-usp/CEMiTool: Co-expression Modules identification Tool

cat("#", title, "{.tabset}")

Modules

    mod_df <- as.data.frame(table(cem@module$modules), stringsAsFactors=FALSE)
    colnames(mod_df) <- c("Module", "No.Genes")
    hub_list <- lapply(get_hubs(cem, n=5, "adjacency"), names)
    Hubs <- sapply(hub_list, paste, collapse=", ")
    mod_df <- merge(mod_df, as.data.frame(Hubs), by.x="Module", by.y="row.names")
    modules <- as.character(mod_df[, "Module"])
    ord <- order(as.numeric(stringr::str_extract(modules, "\\d+")))
    DT::datatable(mod_df[ord, ], rownames=FALSE)

    mod_genes <- module_genes(cem)
    colnames(mod_genes) <- c("Gene", "Module") 
    DT::datatable(mod_genes)

Profile Plot

    if(length(cem@profile_plot) > 0){
        .null <- lapply(cem@profile_plot, print)
    } else {
        writeLines("### Please create profile plots!")
    }

if(is.null(cem@enrichment$nes)){
    height <- 7
}else{
    height <- 1.1*nrow(cem@enrichment$nes)
    height <- ifelse(height == 0, 7, height)
}

#height <- 1.1*nrow(cem@enrichment$nes)
#height <- ifelse(height == 0, 7, height)

Gene Set Enrichment Analysis

    #knitr::opts_current$set('fig.height'=height)
    if(length(cem@enrichment) == 0){
        writeLines("### Please provide a sample annotation!")
    } else if(length(cem@enrichment_plot) > 0){
        plot(cem@enrichment_plot[[1]])
    } else if(nrow(cem@enrichment$nes) == 0) {
        writeLines("### No module enriched.")
    }else {
        writeLines("### Please create enrichment plots!")
    }

    if(length(cem@enrichment) > 0){
        nes <- cem@enrichment$nes
        nes[, -1] <- round(nes[, -1], digits=2)
        pv <- cem@enrichment$padj
        pv[, -1] <- round(pv[, -1], digits=5)

        colnames(nes)[-1] <- paste0(colnames(nes)[-1], ": NES")
        colnames(pv)[-1] <- paste0(colnames(pv)[-1], ": Adjusted p-value")

        # join p-values and nes
        enrich_df <- merge(nes, pv, by.x="pathway")

        # reorder columns
        enrich_df <- enrich_df[, c("pathway", sort(colnames(enrich_df)[-1]))]
        DT::datatable(enrich_df, rownames=FALSE)
    } else {
        writeLines("### Please run enrichment analysis!")
    }

    if(nrow(cem@ora) > 0){
        writeLines("## Over Representation Analysis {.tabset}")

        columns <- c("ID", "Count", "GeneRatio", "BgRatio", "p.adjust")
        ora_df <- cem@ora[, columns]
        ora_df[, "p.adjust"] <- round(ora_df[, "p.adjust"], digits=5)
        ora_list <- split(ora_df, cem@ora$Module)
        there_is_barplot <- length(cem@barplot_ora) > 0
        modules <- names(ora_list)
        modules <- modules[order(as.numeric(stringr::str_extract(modules, "\\d+")))]

        for(n in modules){
            h3n <- paste("###", n) 
            writeLines(h3n)
            if(there_is_barplot){
                print(cem@barplot_ora[[n]]$pl)
            }
            print(htmltools::tagList(DT::datatable(ora_list[[n]][1:max_rows_ora, ], 
                                                   options = list(pageLength=5), 
                                                   rownames = FALSE)))
        }
    } else {
        writeLines("## Over Representation Analysis")
        writeLines("### Please run over representation analysis!")
    }

Interaction Network

    if(length(cem@interaction_plot) > 0){
        x <- lapply(cem@interaction_plot, print)
    } else {
        writeLines("### Please add interactions to the CEMiTool object")
    }

Parameters

desc <- c("cor_method" = "Correlation method.",
          "min_ngen" = "Minimum number of genes per module.",
          "merge_similar" = "Should similar modules be merged?",
          "diss_thresh" = "Dissimilarity threshold to be used as cutoff on hierarchical clustering.",
          "r2" = 'Determination coefficient. Reflects the "scale-freeness" of the resulting network.',
          "beta" = "Value of beta chosen.",
          "phi" = "Area under curve / Total area in the Beta vs R squared graph.",
          "n_genes" = "Number of genes after filtering.",
          "filter_pval" = "p-value used on filtering.",
      "n_mods" = "Number of modules returned by CEMiTool."
          )
desc_df <- data.frame(Parameter=names(desc), Description=desc)

params_list <- cem@parameters
numeric_params <- c("r2", "diss_thresh", "phi", "filter_pval")
for(np in numeric_params){
    if(np %in% names(params_list)){
        params_list[[np]] <- round(params_list[[np]], digits=3)
    }
}
params <- data.frame(Parameter=names(params_list), 
                     Value=as.character(params_list))
params <- merge(desc_df, params, all.y=TRUE)
DT::datatable(params, rownames=FALSE)