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Empirical and estimated homorepeat frequencies.

Calculate the frequencies of amino acids in annotated regions for a sequence base

Calculate the frequencies of amino acids in disordered regions in Swiss-Prot:

export MYDIR=/proj/bioinfo/users/x_oxasa/sp
# Repeat for every type of disorderd regions
export MYTAG=mobidb_regions_dis465
export MYTAG=mobidb_regions_disHL
export MYTAG=mobidb_regions_espD
export MYTAG=mobidb_regions_espN
export MYTAG=mobidb_regions_espX
export MYTAG=mobidb_regions_inverted
export MYTAG=mobidb_regions_iupl
export MYTAG=mobidb_regions_iups
export MYTAG=mobidb_regions_jronn
export MYTAG=mobidb_regions_vsl
export MYTAG=mobidb_regions

python $MYDIR/src/nucleotide_counts.py -f $MYDIR/data/seq/uniprot_sprot.fasta -a $MYDIR/results/disorder_annotations/$MYTAG.csv -o $MYDIR/results/swiss_prot_aa_frequencies/$MYTAG

Use create_regions_file_from_annotations_file in nucleotide_counts.py to create an input file for nucleotide_counts.py allowing to calculate the frequency of amino acids in entire fasta files.

create_regions_file_from_annotations_file("$MYDIR/data/uniprot/swissprot_annotations.tab", "$MYDIR/data/uniprot/swissprot_annotations_for_aa_counts.csv")

With this, calculate the frequencies of amino acids in the entire Swiss-Prot:

python $MYDIR/src/nucleotide_counts.py -f $MYDIR/data/seq/uniprot_sprot.fasta -a $MYDIR/data/uniprot/swissprot_annotations_for_aa_counts.csv -o $MYDIR/results/swiss_prot_aa_frequencies/swissprot_kingdomwise

Calculate amino acids frequencies for ordered regions.

Also calculate the frequencies of amino acids in all regions which are not annotated as disordered. We assume these to be inverted compared to ordered regions. To create the region annotation file for ordered regions; in the src directory, start Python3 and run:

import os
import nucleotide_counts
path_trunk = "/path/to/swissrepeat"
tags = ["mobidb_regions_dis465", "mobidb_regions_disHL", "mobidb_regions_espD", "mobidb_regions_espN", "mobidb_regions_espX", "mobidb_regions_iupl", "mobidb_regions_iups", "mobidb_regions_jronn", "mobidb_regions_vsl", "mobidb_regions"]
tag = tags[4]
# Load region annotations
for tag in tags[4:]:
    regions_file = os.path.join(path_trunk, "results", "disorder_annotations", "{}.csv".format(tag))
    inverted_regions, kingdoms = nucleotide_counts.read_regions(regions_file, min_region_length=1)
    annotation_input_file = os.path.join(path_trunk, "data/swissprot_annotations.tsv")
    regions_result_file = os.path.join(path_trunk, "results", "disorder_annotations", "{}_inverted.csv".format(tag))
    delimiter_input="\t"
    delimiter_result=","
    nucleotide_counts.create_regions_file_from_annotations_file(annotation_input_file,regions_result_file,delimiter_input,delimiter_result,inverted_regions)

Next, calculate the frequencies of amino acids in disordered regions in Swiss-Prot:

export MYTAG=mobidb_regions_dis465_inverted
export MYTAG=mobidb_regions_disHL_inverted
export MYTAG=mobidb_regions_espD_inverted
export MYTAG=mobidb_regions_espN_inverted
export MYTAG=mobidb_regions_espX_inverted
export MYTAG=mobidb_regions_iupl_inverted
export MYTAG=mobidb_regions_iups_inverted
export MYTAG=mobidb_regions_jronn_inverted
export MYTAG=mobidb_regions_vsl_inverted
export MYTAG=mobidb_regions_inverted

python $MYDIR/src/nucleotide_counts.py -f $MYDIR/data/seq/uniprot_sprot.fasta -a $MYDIR/results/disorder_annotations/$MYTAG.csv -o $MYDIR/results/swiss_prot_aa_frequencies/$MYTAG

Calculate empirical homorepeat frequencies.

Calculate expected homorepeat frequencies and connect empirical and expected data.

Requirements:

  • Annotations of empirical homorepeat counts

  • Amino acid frequencies

    Ordered regions

    python3 homorepeat_counts.py -r results/disorder_annotations/mobidb_regions_inverted.csv -t swissprot_disorder_inverse_kingdomwise -p path/to/swissrepeat

    Disordered regions

    python3 homorepeat_counts.py -r results/disorder_annotations/mobidb_regions.csv -t swissprot_disorder_kingdomwise -p path/to/swissrepeat