R/customCnet.R

In fpsanz/enrichGene:

customCnetKegg <- function(kgg, category=NULL, nPath=NULL, byDE=FALSE){
    if(! "ggraph" %in% .packages()) require("ggraph")
    if(! "igraph" %in% .packages()) require("igraph")
    if(! "dplyr" %in% .packages()) require("dplyr")
    if(! "tidyr" %in% .packages()) require("tidyr")
    color_palette <- function(colors) colorRampPalette(colors)(n = 299)
    if(byDE){
        kgg <- kgg %>% arrange(-DE)
    }
    if(!is.null(category)){
        if(is.numeric(category)){
            tmp <- kgg[category,]
        } else{
            tmp <- kgg[kgg$Pathway %in% category,]
        }
    } else{
        tmp <- kgg
    }
    if(!is.null(nPath)){
        if(is.numeric(nPath)){
            tmp <- tmp[1:nPath, ]
        } else{ stop("nPath must be numeric or NULL")}
    }
    pval <- tmp[,c(1,4)]
    tmp <- tmp[,c(1,6)]
    tmp2 <- tmp %>%  separate_rows( genes, convert=TRUE)
    g <- igraph::graph.data.frame(tmp2, directed=FALSE)
    size <- tmp2 %>% dplyr::select(Pathway) %>% group_by(Pathway) %>%  summarise(n=n())
    size <- left_join(tmp, size, by=c("Pathway"))
    pval <- left_join(tmp, pval, by=c("Pathway"))
    size <- size$n
    pval <- pval$P.DE
    V(g)$size <- min(size)/2
    n <- dim(tmp)[1]
    V(g)$size[1:n] <- size
    V(g)$pval <- NA
    V(g)$pval[1:n] <- pval
    edge_layer <- geom_edge_link(alpha=.8, colour='darkgrey')
    fc <- V(g)$pval
    V(g)$color <- fc
    palette <- color_palette(c("red", "blue"))
    p <- ggraph(g, layout="stress", circular=FALSE) +
        edge_layer +
        geom_node_point( aes_(color=~pval, size=~size) ) +
        scale_size(range=c(3, 10), breaks=unique(round(seq(min(size), max(size), length.out=4)))) +
        theme_void()
    p <- p + geom_node_text(aes_(label=~name), data = p$data[1:n,]) +
        scale_color_gradientn(name = "pval", colors=palette, na.value = "#E5C494")
    return(p)
}


customCnetGo <- function(gos, category=NULL, nTerm=NULL, byDE=FALSE, ont="BP"){
    if(! "ggraph" %in% .packages()) require("ggraph")
    if(! "igraph" %in% .packages()) require("igraph")
    if(! "dplyr" %in% .packages()) require("dplyr")
    if(! "tidyr" %in% .packages()) require("tidyr")
    gos <- gos[gos$Ont == ont, ]
    color_palette <- function(colors) colorRampPalette(colors)(n = 299)
    if(byDE){
        gos <- gos %>% arrange(-DE)
    }
    if(!is.null(category)){
        if(is.numeric(category)){
            tmp <- gos[category,]
        } else{
            tmp <- gos[gos$Pathway %in% category,]
        }
    } else{
        tmp <- gos
    }
    if(!is.null(nTerm)){
        if(is.numeric(nTerm)){
            tmp <- tmp[1:nTerm, ]
        } else{ stop("nTerm must be numeric or NULL")}
    }
    pval <- tmp[,c(1,5)]
    tmp <- tmp[,c(1,7)]
    tmp2 <- tmp %>%  separate_rows( genes, convert=TRUE)
    g <- igraph::graph.data.frame(tmp2, directed=FALSE)
    size <- tmp2 %>% dplyr::select(Term) %>% group_by(Term) %>%  summarise(n=n())
    size <- left_join(tmp, size, by=c("Term"))
    pval <- left_join(tmp, pval, by=c("Term"))
    size <- size$n
    pval <- pval$P.DE
    V(g)$size <- min(size)/2
    n <- dim(tmp)[1]
    V(g)$size[1:n] <- size
    V(g)$pval <- NA
    V(g)$pval[1:n] <- pval
    edge_layer <- geom_edge_link(alpha=.8, colour='darkgrey')
    fc <- V(g)$pval
    V(g)$color <- fc
    palette <- color_palette(c("red", "blue"))
    p <- ggraph(g, layout="stress", circular=FALSE) +
        edge_layer +
        geom_node_point( aes_(color=~pval, size=~size) ) +
        scale_size(range=c(3, 10), breaks=unique(round(seq(min(size), max(size), length.out=4)))) +
        theme_void()
    p <- p + geom_node_text(aes_(label=~name), data = p$data[1:n,]) +
        scale_color_gradientn(name = "pval", colors=palette, na.value = "#E5C494")
    return(p)
}