--- a
+++ b/Functions/plot.violin.R
@@ -0,0 +1,32 @@
+#Draw the expression of features in each cluster
+
+#'@param data Generally requires the expression matrix after log, behavioral genes, listed as samples
+#'@param features character vector,
+#'@param clusters The sample classification situation is required to be a vector, that is, names (clusters) correspond to the column names of the expression matrix, and you need to arrange the display order yourself
+
+plot.violin <- function(data, features, clusters, clusters.levels = NULL, xlab = NULL, ylab = NULL, title = NULL, normalizedMethod = "min-max"){
+    
+    # Corresponding gene expression
+    index <- match(features, rownames(data))
+    data <- data[na.omit(index),]
+    if(normalizedMethod == "min-max"){
+        data <- decostand(data, "range", 1)
+    }
+    # Corresponding cell classification
+    index <- match(names(clusters), colnames(data))
+    data <- data[, index]
+    data <- as.data.frame(data)
+    data$gene <- rownames(data)
+
+    require(tidyr)
+    data.reshape <- gather(data, sample, expression, colnames(data)[-length(colnames(data))])
+    data.reshape$cluster <- rep(clusters, each = nrow(data))
+    if(!is.null(clusters.levels)){
+        data.reshape$cluster <- factor(data.reshape$cluster, levels = clusters.levels)
+    }
+
+    require(ggpubr)
+    p <- ggviolin(data.reshape, x = "cluster", y = "expression", fill = "cluster", color = "cluster", add = "mean", add.params = list(color = "black", size = 0.01), xlab = xlab, ylab = ylab, title = title)
+    p <- p + facet_grid(gene ~ ., scales="free_y") + theme(legend.position="none")
+    return(p)
+}
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