How to barplot select rows of data from a dataframe in R?

Question

This is my first time submitting a question, so apologies in advance if my formatting is not optimal.

I have a dataframe with roughly 6,000 rows of data in 2 columns, and I want to be able to pull out individual rows (and multiple rows together) to barplot.

I read my file in as a dataframe, here is a very small subset:

    gene     log2
1 SMa0002 0.457418
2 SMa0005 1.116950
3 SMa0007 0.686749
4 SMa0009 0.169450
5 SMa0011 0.393365
6 SMa0013 0.601940

So what I would want to be able to do is have a barplot where the x axis is a number of genes (SMaXXX, SMaXXX, SMaXXX, etc.), and the y-axis is the log2 column. It only has (+) values displayed, but there are (-) values as well. I have no real preference about whether I use barplot or geom_bar in ggplot2, or another plotter.

I know how to just plot the dataframe;

ggplot(df, aes(x = gene, y = log2)) + geom_bar(stat = "identity")

I've tried playing around with using 'match' but I haven't been able to figure out how to make that work. Ideally the code is versatile so I can just punch in different SMaXXXX codes to generate many different plots.

Thanks for reading!

Answer 1

It seems that you just need a way to subset your data.frame when plotting, right? Let's assume you've got a vector subset.genes of the genes you need to plot:

df=data.frame(gene=c("SMa0002","SMa0005","SMa0006","SMa0007","SMa0011","SMa0013"),
              "log2"=runif(6), stringsAsFactors=F)
subset.genes=sample(unique(df$gene), 4, replace=F)

A couples of ways: 1°) Inside ggplot2

ggplot(df, aes(x = gene, y = log2)) + geom_bar(stat = "identity") +
  scale_x_discrete(limits=subset.genes)

2°) before:

df2 <- subset(df, gene %in% subset.genes)
ggplot(df2, aes(x = gene, y = log2)) + geom_bar(stat = "identity")