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Bioscript

Biology Scripts

Copyright 2023 Hal W Canary III, Lindsay R Saunders PhD. Use of this program is governed by contents of the LICENSE file.

Install

  1. Open a terminal. For MacOS, get the instructions here: https://google.com/search?q=OPEN+MACOS+TERMINAL

  2. Install Python (version ≥ 3.) https://www.python.org/downloads/

    Verify that the command

    python3 --version

    works.

  3. Install git. Check if it is installed with the command git --version . "If you don’t have it installed already, it will prompt you to install it."

  4. Clone this repo with git:

    cd ~
git clone https://github.com/HalCanary/bioscript.git

    or, if you have Github permissions:

    cd ~
git clone [email protected]:HalCanary/bioscript.git

    This will install into the directory ~/bioscript/ .

Unit Testing

To execute all tests:

./test_bioscript.py

Running concat_fasta.py

After installing the bioscript repository, execute the following, (after changing the filenames appropriately:

~/bioscript/concat_fasta.py \
    --outfile ~/Desktop/EnvUn_SP24_Round1.fasta \
    ~/Desktop/SP24_Round1_Environmental_Sequences_seq/*.seq

Running bestSequenceEachSpecies.py

Suppose the input file is ~/Desktop/foobar.fasta and the genus to be filterted is Foobar.

Run:

~/bioscript/bestSequenceEachSpecies.py -g Foobar ~/Desktop/foobar.fasta -o ~/Desktop/foobar_new.fasta

This should write to a file ~/Desktop/foobar_new.fasta.

What it does:

  • Descriptions of the form

    >XX999999.9 Foobar baz strain Ind Int 3 16S ribosomal RNA gene, partial sequence

    will be renamed

    >Foobar_baz XX999999.9 strain Ind Int 3 16S ribosomal RNA gene, partial sequence

  • Given the above input description, the genus is assumed to be Foobar. Only exact matches for the genus are used.

  • Given the above input description, the species is assumed to be Foobar_baz.

    Only the "best" sequence for each species is kept, according to the following criteria:

    1. If one has the string "type strain" in its description and the other does not, use the former, otherwise:

    2. If one has a higher ratio of AGTC characters in the sequence than the other, use that one, but otherwise:

    3. If one's accession string starts with "NR_", and the other does not, use that one, otherwise:

    4. Use the one with the longer sequence.

Running ranked_match.py

To run the ranked match program, first install python3 and ~/bioscript as described above. Then, from a Terminal, first navigate to the directory where your rankings CSV file is located.

$ cd ~/Desktop
$

(Here, the string "$" represents your entire prompt. You don't type it, only the text after the $.)

To see what files are located here, use the ls command. For example:

$ ls
Bio212_FA20_Topic_Rankings.csv	Bio212_FA20_Topic_Rankings_OUTPUT.txt
$

To produce rankings:

$ ~/bioscript/ranked_match.py Bio212_FA20_Topic_Rankings.csv
Francesca Russo    topic=36 (ranked=1)
Jamie Costa        topic=68 (ranked=1)
Robin Ortega       topic=37 (ranked=1)
Kobe Davis         topic=77 (ranked=1)
Mia Beard          topic=7 (ranked=1)
Nathanael Rangel   topic=76 (ranked=2)
Gloria Conley      topic=55 (ranked=1)
Marvin Richmond    topic=13 (ranked=1)
Whitney Wang       topic=6 (ranked=1)
Cohen Aguilar      topic=19 (ranked=1)
Josie Rodriguez    topic=72 (ranked=1)
Henry Zimmerman    topic=34 (ranked=1)
Ariyah Valdez      topic=10 (ranked=3)
Kyler McDaniel     topic=35 (ranked=2)
Dahlia Taylor      topic=20 (ranked=3)
Jackson Avalos     topic=38 (ranked=1)
Paloma Williams    topic=52 (ranked=2)
Oliver Moon        topic=57 (ranked=1)
Naya Riley         topic=63 (ranked=3)
Amari Fischer      topic=53 (ranked=2)
Maci Fuentes       topic=54 (ranked=5)
Bowen Potter       topic=24 (ranked=2)
Rory Pollard       topic=50 (ranked=3)
Jad Warren         topic=65 (ranked=3)
Sloane Pham        topic=27 (ranked=1)
Russell Tapia      topic=69 (ranked=2)
Michaela Rodriguez topic=43 (ranked=1)
Henry Archer       topic=49 (ranked=1)
Kadence Lyons      topic=71 (ranked=1)
Cyrus Ball         topic=None (ranked=2)
Abby Decker        topic=None (ranked=2)

Alternatively, to save the output to a text file:

$ ~/bioscript/ranked_match.py Bio212_FA20_Topic_Rankings.csv > Bio212_FA20_Topic_Rankings_OUTPUT.txt