diff --git a/R/figure.R b/R/figure.R
index 07a53b12b79def0de188d9d2044cd29add17931a..1b98bd794319fb4903e968d0b9128b6778d6e02b 100644
--- a/R/figure.R
+++ b/R/figure.R
@@ -17,10 +17,12 @@ build_figure <- function(top_go_result, go_term_type, outfile) {
     }
     top_go_result$fish <- as.numeric(gsub("< ", "", top_go_result$fish))
     top_go_result <- top_go_result %>%
-        mutate(sigv = -log10(padj),
-        significance = ifelse(sigv < 400, sigv, 400),
-        ft = paste(GO.ID, ":", Term)) %>%
-        filter(padj <= 0.05) %>%
+        mutate(
+            sigv = -log10(padj),
+            significance = ifelse(sigv < 400, sigv, 400),
+            ft = paste(GO.ID, ":", Term)
+        ) %>%
+        filter(pvalue <= 0.05) %>%
         arrange(desc(significance))
     fig <- ggplot(top_go_result, mapping = aes(
         x = significance, y = fct_reorder(ft, significance),
@@ -30,19 +32,23 @@ build_figure <- function(top_go_result, go_term_type, outfile) {
     if (min(top_go_result$significance) * 0.95 < -log10(0.05)) {
         fig <- fig +
             geom_vline(aes(xintercept = -log10(0.05), linetype = "significance"),
-                       size = 0.5, color = "black") +
+                size = 0.5, color = "black"
+            ) +
             scale_linetype_manual(
-                name = "Vertical line", values=c(2, 2),
-                guide = guide_legend(override.aes = list(size = c(0.5))))
+                name = "Vertical line", values = c(2, 2),
+                guide = guide_legend(override.aes = list(size = c(0.5)))
+            )
     }
     fig <- fig +
-    geom_point() +
-    xlab("-log10(pvalue)") +
-    ylab(go_name) +
-    theme_bw() +
-    coord_cartesian(xlim = c(min(top_go_result$significance, 50) * 0.95,
-                             max(top_go_result$significance)) * 1.05) +
-    guides(color = "none", size = guide_legend(title = "# input genes"))
+        geom_point() +
+        xlab("-log10(padj)") +
+        ylab(go_name) +
+        theme_bw() +
+        coord_cartesian(xlim = c(
+            min(top_go_result$significance, 50) * 0.95,
+            max(top_go_result$significance)
+        ) * 1.05) +
+        guides(color = "none", size = guide_legend(title = "# input genes"))
     if (max(top_go_result$significance) > 100) {
         fig <- fig + scale_x_log10()
     }