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More fun manipulating sequence files with Python

Question 0

git pull from the Git project to get the More_python_fun_data directory containing the files we are going to use here.

Question 1

Write a python script that will:

  • Read into the Sheet1 within the metadata_file.xlsx file present in the More_python_fun_data/ directory.

  • Extract UID and accessions (columns 1 & 2) for the Z. mays and P. porosa species and save these accessions in a text file called selected_ids.txt.

Question 2

Write a Python script that:

  • Uses the accessions in selected_ids.txt to parse and filter the corresponding fasta sequences from the resistance_proteins.fasta file. Save these fasta sequences in a file called filtered_resistance_proteins.fasta. NB: The script should give a warning if the corresponding/matching fasta sequence for an accession is missing and save all accessions with missing sequences in a file called missing.txt.

  • For each fasta sequence in filtered_resistance_proteins.fasta, search and replace (using accessions from selected_ids.txt) the sequence header (example: >HB413228.1 Sequence 13 from Patent WO2009070569) with ">" + corresponding UID (> 0595f4adb333). The results should be as shown below in (b) and saved in a file called hidden_IDs_file.fasta.

a)

>gi|75163199|sp|Q93VV9.1|TM16B_ARATH RecName: Full=Mitochondrial import inner membrane translocase subunit PAM16 like 2; Short=AtPAM16; Short=AtPAM16L2; AltName: Full=Presequence translocated-associated motor subunit PAM16; AltName: Full=Protein MUTANT SNC1-ENHANCING 5; AltName: Full=Protein THAXTOMIN A RESISTANT 1; Flags: Precursor MAGRLLANLIVMGSGIIGRAVFQAYRQALANASKSGVAQEAMQNGVRQAGKAITEQEARQILGVTEKTSW EEILQKYDKLFENNAKAGSFYLQSKVHRAKECLEVVYRSQGNGTPS

becomes:

b)

> 0595f4adb333 MAGRLLANLIVMGSGIIGRAVFQAYRQALANASKSGVAQEAMQNGVRQAGKAITEQEARQILGVTEKTSW EEILQKYDKLFENNAKAGSFYLQSKVHRAKECLEVVYRSQGNGTPS

Create a neat directory and save all your scripts and output files pertaining to this exercise there.