diff --git a/RNA-arry.R b/RNA-arry.R
index 5e3adcd..5ae2a15 100644
--- a/RNA-arry.R
+++ b/RNA-arry.R
@@ -38,28 +38,28 @@ exp <- exp[, -1]
 #将样本按pData$title分为normal组和cancer组，并转换为factor
 grp <- grp[colnames(exp),]
 grp <- ifelse(str_detect(grp$title,"Normal"),"normal","cancer") %>%
-  factor(c("normal","cancer"))
+  factor(c("normal","cancer"))
 
 ############################样本质量控制与标准化################################
 
 pca_plot1 <- as.data.frame(prcomp(t(exp))$x) %>%
-  ggplot(aes(x = PC1, y = PC2, colour = grp)) +
-  geom_point() +
-  stat_ellipse(level = 0.95, show.legend = F) +
-  theme_bw() +
-  theme(panel.grid.major=element_blank(), panel.grid.minor=element_blank()) +
-  ggtitle("Before Normalize")
+  ggplot(aes(x = PC1, y = PC2, colour = grp)) +
+  geom_point() +
+  stat_ellipse(level = 0.95, show.legend = F) +
+  theme_bw() +
+  theme(panel.grid.major=element_blank(), panel.grid.minor=element_blank()) +
+  ggtitle("Before Normalize")
 
 exp <- normalizeBetweenArrays(exp, method="quantile")
 if(max(exp)>50) exp <- log2(exp + 1)
 
 pca_plot2 <- as.data.frame(prcomp(t(exp))$x) %>%
-  ggplot(aes(x = PC1, y = PC2, colour = grp)) +
-  geom_point() +
-  stat_ellipse(level = 0.95, show.legend = F) +
-  theme_bw() +
-  theme(panel.grid.major=element_blank(), panel.grid.minor=element_blank()) +
-  ggtitle("After Normalize")
+  ggplot(aes(x = PC1, y = PC2, colour = grp)) +
+  geom_point() +
+  stat_ellipse(level = 0.95, show.legend = F) +
+  theme_bw() +
+  theme(panel.grid.major=element_blank(), panel.grid.minor=element_blank()) +
+  ggtitle("After Normalize")
 
 pca_plot1 + theme(legend.position = "none") + pca_plot2