From 8b953a77d3e886ad4fc05134719e4baf63d057e0 Mon Sep 17 00:00:00 2001 From: Meeta Mistry Date: Wed, 18 Oct 2023 00:21:38 -0400 Subject: [PATCH] Update 08_figure_specific_packages.md --- lessons/08_figure_specific_packages.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/lessons/08_figure_specific_packages.md b/lessons/08_figure_specific_packages.md index 9dec93b..34a2fba 100644 --- a/lessons/08_figure_specific_packages.md +++ b/lessons/08_figure_specific_packages.md @@ -66,7 +66,7 @@ length(which(row.names(up1) %in% row.names(up2))) length(which(row.names(down1) %in% row.names(down2))) ``` -Now, to create the figures we first take the union of genes for each direction of change and use those gene identifiers to create dataframes. The row names correspond to gene identifiers, and we add two columns of logical values for PAX6 and TBR2. +To create the figures using ggvenn we first take the union of genes for each direction of change and use those gene identifiers to create dataframes. The row names correspond to gene identifiers, and we add two columns of logical values for PAX6 and TBR2. ```r # Combine results from datasets and remove duplicated values @@ -88,7 +88,7 @@ data_down$PAX6 <- data_down$value %in% rownames(down1) data_down$TBR2 <- data_down$value %in% rownames(down2) ``` -Now to create a simple Venn diagram, we can use the `ggvenn()` function from the ggvenn package: +Next, we can use the `ggvenn()` function from the ggvenn package to create a simple Venn diagram: ```r ggvenn(data_up)