--- a
+++ b/Functions/IDConvert.R
@@ -0,0 +1,44 @@
+#### convert gene ID
+#author: Zhilin long
+#time: 2021.1.19
+
+#'@author Zhilin Long
+#'@param gene Character vector, ID vector to be converted
+#'@param fromType Character vector, initial ID type
+#'@param toType Character vector, ID type to be converted
+#'
+#'@return data.frame has removed duplication and NA, and can be used directly
+
+
+IDConvert <- function(genes, 
+                       method = c("clusterProfiler", "org.Hs.eg.db"),
+                       fromType = c("ENTREZID", "SYMBOL", "ENSEMBL"), 
+                       toType = c("ENTREZID", "SYMBOL", "ENSEMBL")
+                       ){
+    require(org.Hs.eg.db)
+    require(clusterProfiler)
+
+    method <- match.arg(method)
+    fromType <- match.arg(fromType)
+    toType <- match.arg(toType)
+
+    if(method == "clusterProfiler"){
+        gene.df <- bitr(genes, fromType = fromType, toType = toType, OrgDb = "org.Hs.eg.db")
+        #By default, IDs that are not mapped will be filtered, that is, the entries will be reduced
+    }else{
+        gene.df <- mapIds(org.Hs.eg.db, 
+                          keys = genes, 
+                          column = toType, 
+                          keytype = fromType,
+                          multiVals="first")
+        gene.df <- data.frame(ENSEMBL = names(gene.df), SYMBOL = gene.df)
+        colnames(gene.df) <- c(fromType, toType)
+        # If there is no map, it is NA, that is, the entry remains unchanged
+        gene.df <- na.omit(gene.df) 
+    }
+
+    #remove duplicates
+    gene.df <- gene.df[!duplicated(gene.df[,2]),]
+    gene.df <- gene.df[!duplicated(gene.df[,1]),]
+    return(gene.df)
+}
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