app.py

import os
os.system("pip install streamlit pandas xlsxwriter openpyxl")

import streamlit as st
import pandas as pd
import xlsxwriter
from io import BytesIO
from collections import defaultdict

# Utility to check homo repeat
def is_homo_repeat(s):
    return all(c == s[0] for c in s)

def find_homorepeats(protein):
    n = len(protein)
    freq = defaultdict(int)
    i = 0
    while i < n:
        curr = protein[i]
        repeat = ""
        while i < n and curr == protein[i]:
            repeat += protein[i]
            i += 1
        if len(repeat) > 1:
            freq[repeat] += 1
    return freq

def find_hetero_amino_acid_repeats(sequence):
    repeat_counts = defaultdict(int)
    for length in range(2, len(sequence) + 1):
        for i in range(len(sequence) - length + 1):
            substring = sequence[i:i+length]
            repeat_counts[substring] += 1
    return {k: v for k, v in repeat_counts.items() if v > 1}

def fragment_protein_sequence(sequence, max_length=1000):
    return [sequence[i:i+max_length] for i in range(0, len(sequence), max_length)]

def check_boundary_repeats(fragments, final_repeats, overlap=50):
    for i in range(len(fragments) - 1):
        left_overlap = fragments[i][-overlap:]
        right_overlap = fragments[i + 1][:overlap]
        overlap_region = left_overlap + right_overlap
        boundary_repeats = find_hetero_amino_acid_repeats(overlap_region)
        for substring, count in boundary_repeats.items():
            if any(aa in left_overlap for aa in substring) and any(aa in right_overlap for aa in substring):
                final_repeats[substring] += count
    return final_repeats

def find_new_boundary_repeats(fragments, final_repeats, overlap=50):
    new_repeats = defaultdict(int)
    for i in range(len(fragments) - 1):
        left_overlap = fragments[i][-overlap:]
        right_overlap = fragments[i + 1][:overlap]
        overlap_region = left_overlap + right_overlap
        boundary_repeats = find_hetero_amino_acid_repeats(overlap_region)
        for substring, count in boundary_repeats.items():
            if any(aa in left_overlap for aa in substring) and any(aa in right_overlap for aa in substring):
                if substring not in final_repeats:
                    new_repeats[substring] += count
    return new_repeats

def process_protein_sequence(sequence, analysis_type, overlap=50):
    fragments = fragment_protein_sequence(sequence)
    final_repeats = defaultdict(int)

    if analysis_type == "Hetero":
        for fragment in fragments:
            fragment_repeats = find_hetero_amino_acid_repeats(fragment)
            for k, v in fragment_repeats.items():
                final_repeats[k] += v
        final_repeats = check_boundary_repeats(fragments, final_repeats, overlap)
        new_repeats = find_new_boundary_repeats(fragments, final_repeats, overlap)
        for k, v in new_repeats.items():
            final_repeats[k] += v
        final_repeats = {k: v for k, v in final_repeats.items() if not is_homo_repeat(k)]

    elif analysis_type == "Homo":
        final_repeats = find_homorepeats(sequence)

    elif analysis_type == "Both":
        hetero_repeats = defaultdict(int)
        for fragment in fragments:
            fragment_repeats = find_hetero_amino_acid_repeats(fragment)
            for k, v in fragment_repeats.items():
                hetero_repeats[k] += v
        hetero_repeats = check_boundary_repeats(fragments, hetero_repeats, overlap)
        new_repeats = find_new_boundary_repeats(fragments, hetero_repeats, overlap)
        for k, v in new_repeats.items():
            hetero_repeats[k] += v
        hetero_repeats = {k: v for k, v in hetero_repeats.items() if not is_homo_repeat(k)]

        homo_repeats = find_homorepeats(sequence)

        final_repeats = homo_repeats.copy()
        for k, v in hetero_repeats.items():
            final_repeats[k] += v

    return final_repeats

def process_excel(excel_data, analysis_type):
    repeats = set()
    sequence_data = []
    for sheet_name in excel_data.sheet_names:
        df = excel_data.parse(sheet_name)
        if len(df.columns) < 3:
            st.error(f"Error: The sheet '{sheet_name}' must have at least three columns: ID, Protein Name, Sequence")
            return None, None
        for _, row in df.iterrows():
            entry_id = str(row[0])
            protein_name = str(row[1])
            sequence = str(row[2]).replace('"', '').replace(' ', '')
            freq = process_protein_sequence(sequence, analysis_type)
            sequence_data.append((entry_id, protein_name, freq))
            repeats.update(freq.keys())
    return repeats, sequence_data

def create_excel(sequences_data, repeats, filenames):
    output = BytesIO()
    workbook = xlsxwriter.Workbook(output, {'in_memory': True})
    for file_index, file_data in enumerate(sequences_data):
        filename = filenames[file_index]
        worksheet = workbook.add_worksheet(filename[:31])
        worksheet.write(0, 0, "Entry ID")
        worksheet.write(0, 1, "Protein Name")
        col = 2
        for repeat in sorted(repeats):
            worksheet.write(0, col, repeat)
            col += 1
        row = 1
        for entry_id, protein_name, freq in file_data:
            worksheet.write(row, 0, entry_id)
            worksheet.write(row, 1, protein_name)
            col = 2
            for repeat in sorted(repeats):
                worksheet.write(row, col, freq.get(repeat, 0))
                col += 1
            row += 1
    workbook.close()
    output.seek(0)
    return output

st.title("Protein Repeat Analysis")
analysis_type = st.radio("Select analysis type:", ["Homo", "Hetero", "Both"], index=2)
uploaded_files = st.file_uploader("Upload Excel files", accept_multiple_files=True, type=["xlsx"])

if uploaded_files:
    all_repeats = set()
    all_sequences_data = []
    filenames = []
    for file in uploaded_files:
        excel_data = pd.ExcelFile(file)
        repeats, sequence_data = process_excel(excel_data, analysis_type)
        if repeats is not None:
            all_repeats.update(repeats)
            all_sequences_data.append(sequence_data)
            filenames.append(file.name)
    if all_sequences_data:
        st.success(f"Processed {len(uploaded_files)} files successfully!")
        excel_file = create_excel(all_sequences_data, all_repeats, filenames)
        st.download_button(
            label="Download Excel file",
            data=excel_file,
            file_name="protein_repeat_results.xlsx",
            mime="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
        )
        if st.checkbox("Show Results Table"):
            rows = []
            for file_index, file_data in enumerate(all_sequences_data):
                filename = filenames[file_index]
                for entry_id, protein_name, freq in file_data:
                    row = {"Filename": filename, "Entry ID": entry_id, "Protein Name": protein_name}
                    row.update({repeat: freq.get(repeat, 0) for repeat in sorted(all_repeats)})
                    rows.append(row)
            result_df = pd.DataFrame(rows)
            st.dataframe(result_df)