Task for Introduction to Computational Biology at MIM UW (http://regulomics.mimuw.edu.pl/wp/2020/05/wbo-assignment-2-zadanie-2/)
data/protein_fragments.fa contains protein fragments from 2 tested groups: A and B. We speculate (based on the empirical evidence), that these groups of genes should have different regulatory mechanisms.
The script performs a series of 3 tasks:
- Identifies the closest related protein-coding sequences in the E. coli genome for each of the input protein sequences from
data/protein_fragments.fa. The result is a csv filetask1.csvcontaining: input sequence id, best matching E. coli gene id and the associated e-value.
E. coli protein-coding sequences are read from: data/genes_e_coli.fa.
- For each of the identified E. coli genes, finds the associated promoter DNA sequence. Motif analysis is done with MEME-suite.
The result is two sets of motif position-specific matrices in a .pfm format.
E. coli promoter sequences are read from: data/proms_e_coli.fa.
- Given the two sets of motifs, selects only the motifs specific to group A or group B by obtaining a number of positions in these promoter sequences that have a log-odds score higher than 0 and using the binomial test.
The result is a csv file task3.csv containing motifs, their associated number of hits in the promoters from group A, and promoters from group B and the associated p-values for enrichment in group A and group B.
First, download NCBI BLAST+ suite. The code will run the following command for creating a local BLAST db with this command:
makeblastdb -in data/protein_e_coli.fa -parse_seqids -blastdb_version 5 -taxid 1 -title "ecoli" -dbtype prot
where data/protein_e_coli.fa will contain proteins obtained by translation of data/genes_e_coli.fa.
Install dependencies:
pip install -r requirements.txt
Then run the script with:
python main.py PATH_TO_BLAST
where PATH_TO_BLAST is a path to NCBI BLAST+ suite.