Plot gene counts of different groups in the same graph

Question

[dianalves17]

I have the following dataset: Normalised gene counts of 6 different groups, 2 replicates per group( eg. group 1: E13_5_meninges; group 1 replicates: E13_5_meninges_1, E13_5_meninges_2. I want to plot in the same graph the normalised gene counts for each condition. Anyone can help on how I should do this?

     ensembl_gene_id E13_5_meninges_1 E13_5_meninges_2
   <chr>                      <dbl>            <dbl>
 1 ENSMUSG0000000…            6342.            6238.
 2 ENSMUSG0000000…             771.             768.
 3 ENSMUSG0000000…           40981.           43835.
 4 ENSMUSG0000000…             311.             265.
 5 ENSMUSG0000000…            1364.            1378.
 6 ENSMUSG0000000…            1035.            1106.
 7 ENSMUSG0000000…            4285.            3985.
 8 ENSMUSG0000000…             870.             866.
 9 ENSMUSG0000000…             918.             994.
10 ENSMUSG0000000…            1266.            1304.

[Benn]

Do you want a plot with a jitter like a beeswarm plot?

[dianalves17]

Yes. So, I have 18103 entries, but I am interested in looked at normalised counts of particular genes in my different groups.

[Benn]

It wouldn't make sense to plot all 18k entries with beeswarms, but for the particular genes of interest (significantly different between two or more groups) the beeswarm would be a solution. In the link you can read how to make these plots, if you get stuck in the code, please post your code and an example of the data.

Answer 1

[Corentin]

If you do not care about individual genes you can create a boxplot, one for each group. It will tell you how the overall expression is different.

If you care about individual genes and you do not have a lot of them, you can create a bar plot for each. For example, you can use geom_bar with the position_dodge() option of ggplot2 to plot bar plots next to one another, so you can compare the groups for each gene. (cf https://ggplot2.tidyverse.org/reference/geom_bar.html).