diff --git a/DESCRIPTION b/DESCRIPTION
index c1791343536172517a4ff7aae82268912b5cb252..5441fb4fe1a7bea560f44572cbc187591c484d6d 100755
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -2,7 +2,7 @@ Package: ChIPuanaR
 Type: Package
 Title: Differential analysis of ChIP-Seq data
 Version: 0.99.0
-Date: 2020-01-13
+Date: 2020-04-06
 Author: Marie-Agnes Dillies, Hugo Varet and Maëlle Daunesse
 Maintainer: Maëlle Daunesse <maelle.daunesse@pasteur.fr>
 Depends: R (>= 3.4.0), DESeq2, limma, kableExtra, knitr, ggplot2
diff --git a/R/run.DESeq2.r b/R/run.DESeq2.r
index 823f9975a62a9a33a95b7140a06a5817ab034496..e36ec136c3d4aa688cf69669630497bd18b7bc0b 100755
--- a/R/run.DESeq2.r
+++ b/R/run.DESeq2.r
@@ -44,7 +44,11 @@ run.DESeq2 <- function(counts, conditions, batch=NULL, pAdjustMethod="BH", spike
     colnames(counts.norm) <- paste0("norm.",colnames(counts))
     res <- results(dds, contrast=c("conditions", levelTest, levelRef),
                    pAdjustMethod=pAdjustMethod, cooksCutoff=TRUE, independentFiltering=FALSE)
-    res <- res[, c("baseMean", "log2FoldChange", "pvalue", "padj", "lfcSE", "stat")]
+    res <- res[, c("baseMean", "log2FoldChange", "lfcSE", "stat", "pvalue", "padj")]
+    res$baseMean <- round(res$baseMean, 2)
+    res$log2FoldChange <- round(res$log2FoldChange, 2)
+    res$lfcSE <- round(res$lfcSE, 2)
+    res$stat <- round(res$stat, 2)
     resAnDif <- data.frame(counts, counts.norm, res)
     results[[paste0(levelTest,"_vs_",levelRef)]] <- resAnDif
     cat(paste("Comparison", levelTest, "vs", levelRef, "done\n"))
diff --git a/R/run.Limma.r b/R/run.Limma.r
index 865733014c59942d2eb9b0b98fcb50bddc630a49..9a4dc8039ea02aeb3d9caa515813d263dc0cd4df 100644
--- a/R/run.Limma.r
+++ b/R/run.Limma.r
@@ -51,9 +51,10 @@ run.Limma <- function(counts, conditions, normalize.method="quantile", spikes=NU
     fit2 <- contrasts.fit(fit=fit, contrasts=cont.matrix)
     efit <- eBayes(fit=fit2)
     colnames(v$E) <- paste0("norm.", colnames(counts))
-    resAnDif <- data.frame(counts,v$E,
-                           baseMean=efit$Amean,
-                           log2FoldChange=as.numeric(efit$coefficients),
+    resAnDif <- data.frame(counts, 
+                           round(v$E, 2),
+                           baseMean=round(efit$Amean, 2),
+                           log2FoldChange=round(as.numeric(efit$coefficients), 2),
                            pvalue=as.numeric(efit$p.val),
                            padj=p.adjust(efit$p.value, method=pAdjustMethod))
     results[[paste0(levelTest,"_vs_",levelRef)]] <- resAnDif