You sed what? Modifying variables with sed in bash

July 27, 2020 • PD Schloss • 5 min read

In the last two episodes we’ve created a few bash scripts and a Makefile to help automate running those scripts while keeping track of the dependencies. You may recall that we aren’t tracking changes to our data files because they’re too big. But with our bash scripts and make, we can regenerate them if they somehow got deleted or we needed start over. Of course, you should be able to use my files to reproduce what I’ve already done, which is a win for reproducibility. Because these tools are so powerful, I want to spend a little more time with them.

In today’s episode we’re going to clean up our scripts and Makefile a bit. If you look at our Makefile and bash scripts for downloading the rrnDB files, you’ll see that we pass in the name of the file we want to download. We didn’t include the path indicating where it should go once it is extracted. Instead, we hardcoded that it should be outputted to our data/raw/ directory. If I ended up wanting to change where to put the files, then I’d have to change the bash script rather than the Makefile rule.

Today, we’ll learn a bash command, sed, that will allow us to give the script the file’s name with its path. I admit that this is a relatively small improvement for our overall project. But, along the way we’ll learn a few other bash tools including the pipe and how to capture output to a variable. We’ll also see how we can use variables that are built into make that simplify our Makefiles. Because these improvements will make our analyses easier to develop, they will also be more reproducible.

Even if you haven’t been following along with the past episodes, I’m sure you’ll get a lot out of today’s video. Please take the time to follow along on your own computer and attempt the exercises. Don’t worry if you aren’t sure how to solve the exercises, at the end of the video I will provide solutions. If you haven’t been following along but would like to, please check out the notes below where you’ll find instructions on catching up, reference notes, and links to supplemental material. You can find my version of the project on GitHub.

Important things to remember

Installations

If you haven’t been following along, you can get caught up by doing the following:

Exercises

1. Can you explain what happens if we leave off the echo command in our script? You might remember we got a similar error in the episode where we were developing our bash scripts.

path=`$target | sed -E "s/(.*\/).*/\1/"`

We get the following error message:

-bash: data/raw/rrnDB-5.6.tsv: Permission denied

This is the same error we got when trying to run a bash script as an executable before we used chmod +x. You might have thought this should have run our sed command on the contents of the file. To do that, we need a slightly different syntax

path=`sed -E "s/(.*\/).*/\1/" < $target`

2. Write the command to extract the variable region (i.e. V4) from data/V4/rrndb.align and save it to a variable named region. Try to make your regular expression as general as you can

file=data/V4/rrndb.align
region=`echo $file | sed -E "s/.*\/(.*)\/.*/\1/"`
echo $region

or

file=data/V4/rrndb.align
region=`echo $file | sed -E "s_.*/(.*)/.*_\1_"`
echo $region

3. We discussed using the automatic variable $@ to represent the target name in the recipes of our Makefile. You can also use $< to represent the name of the first prerequisite and $^ to represent all of the names of the prerequisites. How would you edit the rule to generate data/raw/rrnDB-5.6_16S_rRNA.fasta and data/raw/rrnDB-5.6_16S_rRNA.align so that the recipe only includes these automatic variables? Any thoughts about the revised syntax?

data/raw/rrnDB-5.6_16S_rRNA.fasta : code/get_rrndb_files.sh
	$^ $@

data/raw/rrnDB-5.6_16S_rRNA.align : code/align_sequences.sh\
			data/references/silva_seed/silva.seed_v138.align\
			data/raw/rrnDB-5.6_16S_rRNA.fasta									
	$^

Although the extra typing is reduced in these revised scripts, the recipe line might be a bit too cryptic. There is a tradeoff between simplicity and ease of reading. Regardless, this exercise highlights that it would be good to have a practice of putting the script prerequisite first followed by the data.

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