Introduction

This project comprises two exercises to help you learn some basics of Python (Exercise 1) and regular expressions (Exercise 2) by manipulating nucleotide sequences.

Contents

• Getting set up
• Exercise 1
• Exercise 2
  • Part 1
  • Part 2
• Acknowledgments
• License

Getting set up

At this point, you should have (1) an account on Github and (2) been introduced to the very basics of Git.

1. Login to your Github account.

2. Fork this repository, by clicking the 'Fork' button on the upper right of the page.

   After a few seconds, you should be looking at your copy of the repo in your own Github account.

3. Click the 'Clone or download' button, and copy the URL of the repo via the 'copy to clipboard' button.

4. In your terminal, navigate to where you want to keep this repo (you can always move it later, so just your home directory is fine). Then type:

   $ git clone the-url-you-just-copied
   

   and hit enter to clone the repository. Make sure you are cloning your fork of this repo.

5. Next, cd into the directory:

   $ cd the-name-of-directory-you-just-cloned
   

6. At this point, you should be in your own local copy of the repository.

7. As you work on the exercise below, be sure to frequently add and commit your work and push changes to the remote copy of the repo hosted on GitHub. Don't enter these commands now; this is just to jog your memory:

   $ # Do some work
   $ git add file-you-worked-on.py
   $ git commit
   $ git push origin master
   

---

Exercise 1

Learning objective

Learn some basics of Python by filling in code for functions that manipulate nucleotide sequences.

The goal

The goal of this exercise is for you to practice Python coding by editing a script (or module) for manipulating nucleotide sequences until it runs and passes a suite of tests.

Type ls in the directory of the repo you just cloned. You should see something like:

$ ls
find_orf.py
LICENSE.txt
README.md
test_find_orf.py
test_translate.py
test_util.py
translate.py

The file translate.py is where you will write your Python code for this exercise. Go ahead and open it with your preferred text editor. You will see that the file is mostly filled with functions and their docstrings. Currently these functions don't do anything; they only call the pass statement, which does nothing and causes them to return None.

The file test_translate.py is a Python script that runs a series of tests on the translate.py script. Since that code doesn't exist yet, all of these tests currently fail. Try it:

$ python3 test_translate.py

You can also run the tests for only one of the functions in translate.py. For example, to run only the tests for the get_reverse function, try:

$ python3 test_translate.py TestGetReverse

For each function, your goal is to delete the pass statement and add your own Python code until all the tests of the function pass. Based on the functions' docstrings and the messages reported by failing tests, it should be clear what the functions in translate.py should be doing to pass the tests.

Because the functions range from relatively simple to challenging, and the more challenging functions might use the simpler ones, I strongly recommend that you get all the tests working for one function before moving onto another, and do so in the following order:

1. Get tests of get_reverse function working:

   $ python3 test_translate.py TestGetReverse
   

2. Get tests of get_complement function working:

   $ python3 test_translate.py TestGetComplement
   

3. Get tests of reverse_and_complement function working:

   $ python3 test_translate.py TestReverseAndComplement
   

4. Get tests of translate_sequence function working:

   $ python3 test_translate.py TestTranslateSequence
   

5. Get tests of get_all_translations function working:

   $ python3 test_translate.py TestGetAllTranslations
   

6. Get tests of get_longest_peptide function working:

   $ python3 test_translate.py TestGetLongestPeptide
   

NOTE: You do NOT need to know how the tests work! You only need to add code to translate.py. The tests only care about what each function returns, not how the functions work.

NOTE: You do NOT need to change the code below the if __name__ == '__main__': line. Only the functions themselves need work.

Suggestions

• Make sure you are using Git to commit and push your work often as you work on this exercise.
• print statements are your friend while you are debugging.
• assert statements are also your friend.
• If a function is getting long, define your own new functions to keep the code as modular as possible.
• Once you get the script working and all the tests passing, think about how you might improve the script. For example:
  • What happens if a DNA sequence is passed to your functions? How would you want to handle this?
  • Should your functions only accommodate strings for the sequence argument? What if someone passes a list? a tuple? How do you want your functions to behave?
  • Should you have a default genetic code, so the caller doesn't always have to create and pass a big dictionary to your functions? How would you do this in a way that does not rely on global variables? How could you avoid globals and avoid creating multiple instances of the genetic code? This is a bit advanced, but a good solution might involve creating a class that manages genetic codes.

Good luck!

---

Exercise 2

Part 1

Learning Objective: The goal is for you to practice using regular expressions in Python to find open-reading frames (ORFs) in sequences of nucleotides.

Open the file find_orf.py with your preferred text editor. In this file you will find functions with detailed docstrings, and three places in the code marked with comments like:

##########################################################################
############################ EDIT CODE BELOW #############################
# `codon_pattern_str` needs to be a regular expression that will match any
# codon (but only one codon).
# Currently, `codon_pattern_str` is only a string of literal characters.
# This is a valid regular expression, but it will only match 'AUG' exactly.
# Change `codon_pattern_str` so that it will match any valid codons, and
# only valid codons.
# Read the docstring above for additional clues.
codon_pattern_str = r'AUG'
##########################################################################

Here is where you will need to edit the code to get a regular expression that accomplishes the task at hand. In the example above, codon_pattern_str is the regular expression that you would need to edit. Read the function's docstring and the comments carefully to help guide your composing of the regular expression.

Once you have successfully composed the regular expressions in find_orf.py, all the tests in test_find_orf.py will pass.

$ python3 test_find_orf.py

Read the error and failure messages reported by test_find_orf.py (and the docstrings in find_orf.py) carefully to help you get the regular expressions in find_orf.py working correctly.

You can run the tests for each function separately:

$ python3 test_find_orf.py TestVetNucleotideSequence
$ python3 test_find_orf.py TestVetCodon
$ python3 test_find_orf.py TestFindFirstOrf

These commands will run the tests for the functions vet_nucleotide_sequence, vet_codon, and find_first_orf, respectively. It can be helpful to only run the tests for the function your working on.

Start with the vet_nucleotide_sequence and vet_codon functions first. These regular expressions are easier, and the find_first_orf function depends on them (i.e., it uses them), so working on find_first_orf will be easier if the tests for vet_nucleotide_sequence and vet_codon are passing.

NOTE: You do NOT need to know how the tests work! You only need to add code to find_orf.py. The tests only care about what each function returns, not how the functions work.

Suggestions

• Make sure you are using Git to add, commit, and push your work often as you work on Part 1 of this exercise.
• Play around with 'mini examples' of the regular expressions in the python interpreter.

Some fun with argparse

Once all the tests are passing, you can use find_orf.py as a script to find the first open reading frame in a nucleotide sequence. Check out the help menu:

$ python3 find_orf.py -h

This help menu is created automatically by the argparse package using the information provided by the code in the main function in find_orf.py.

You can give the script a nucleotide sequence to search at the command line:

$ python3 find_orf.py AUGGUAUAA

The sequence can also be provided in a file if you specify the -p flag:

$ python3 find_orf.py -p path-to-a-file-with-a-sequence.py 

You can also specify start and stop codons with -s and -x arguments, respectively:

$ python3 -s AUG -x UAA UAG find_orf.py AUGGUAUAA

All of this command-line interface is specified and handled in the main function of find_orf.py using the argparse package.

This package can be very useful for making your scripts portable and user friendly. You will use it in Part 2!

Part 2

Learning Objective: The goal is for you to practice writing your own scripts in Python "from scratch" (from the shebang line to the command-line interface).

Create a new script (file) called translate_orf.py. Now, add code to translate_orf.py so that it can translate the first ORF found in a nucleotide sequence. This script will have a command-line interface very similarly to find_orf.py. The only difference is that it will translate the ORF that it finds and report the amino acid sequence (to standard output).

Some tips that might be helpful:

• Write a main function very similar to the one in find_orf.py to set up the command-line interface and process command-line arguments.
• import and use the find_first_orf function in find_orf.py to find the first ORF.
• import and use the translate_sequence function in translate.py to translate the ORF.
• import and use the parse_sequence_from_path function in find_orf.py, just like it is currently used in the main function of find_orf.py.
• Don't worry about accommodating genetic codes; just use (i.e., copy and paste) the same genetic code that is defined in translate.py; you will need it in your main function.

A main function similar to the one in find_orf.py should be all you need to get this working, because you can do the ORF searching and translation within your main function using the functions you imported from find_orf.py and translate.py and the genetic code you pasted in.

Suggestions

• Make sure you are using Git to commit and push your work often as you work on Part 2 of this exercise.

Extra challenges (i.e., not required)

After completing Part 2, you likely have code in the main functions of find_orf.py and translate_orf.py that is largely redundant.

Can you think of a way of reorganizing the code to avoid this redundancy?

Also, can you update translate_orf.py so that it can accommodate any genetic code?

Acknowledgments

Material

This exercise was inspired by, and borrowed heavily from, the class notes and Python scripts written by Mark Holder, which can be found at https://github.com/mtholder/eebprogramming.

Support

This work was made possible by funding provided to Jamie Oaks from the National Science Foundation (DEB 1656004).

License

This work is licensed under a Creative Commons Attribution 4.0 International License.