Refactor to reduce duplication when there is only protein as input

[taylorreiter]

Note that this PR is against the branch in #39, which has already been approved. The changes were substantial enough that I did them in another branch. Once this one passes review, I intend to merge into #39 and then merge #39 w/o additional review.

PR checklist

• [x] Tag the issue(s) or milestones this PR fixes (e.g. Fixes #123, Resolves #456).
• [x] Describe the changes you've made.
• [x] Describe any tests you have conducted to confirm that your changes behave as expected.
• [x] If you've added new software dependencies, make sure that those dependencies are included in the appropriate conda environments.
• [x] If you've added new functionality, make sure that the documentation is updated accordingly.
• [x] If you encountered bugs or features that you won't address, but should be addressed eventually, create new issues for them.

Issues or milestones

• Addresses PR feedback from #39

PR description

This PR refactors extract_deeppeptide_sequences.py and run_nlpprecursor.py so that these scripts can be used when there is only protein or protein & nucleotide inputs. In #39, I had duplicated the scripts. This removes that duplication.

Tests

For the deeppeptide script, I checked by eye that the results were correct. Learning my lesson, I then compared md5sums for the nlpprecursor to make sure that the outputs were the same before and after the refactor.

Other

• no new dependencies
• punting on docs. I started documenting peptigate tho so expect a pr soon!

[taylorreiter]

Thank you so much @keithchev! I addressed all of your feedback and made sure I still get the same results after the changes. merging now!