29  DNA Analyzer with Streamlit

Author

Affiliation

Dr Randy Johnson

Hood College

Today we will build a functioning Streamlit application that takes a DNA sequence as input and outputs basic biological metrics and a visualization.

Starter code

Complete the following starter code:

########## import correct python libraries here ##########

# Page config
st.set_page_config(page_title="DNA Sequence Analyzer", layout="wide")

########## Add title and description for the app ##########

########## Add a side bar for data input ##########

# Clean the sequence
sequence = sequence_input.upper().replace(" ", "").replace("\n", "")

if sequence:
    st.subheader("Sequence Statistics")
    
    # Calculations
    seq_length = len(sequence)
    a_count = sequence.count('A')
    t_count = sequence.count('T')
    g_count = sequence.count('G')
    c_count = sequence.count('C')
    
    # Calculate GC content safely
    if seq_length > 0:
        gc_content = ((g_count + c_count) / seq_length) * 100
    else:
        gc_content = 0.0

    ######## Add metrics for sequence length and GC content statistics in two equally spaced columns ##########

    st.divider()

    # Create a DataFrame for the counts
    st.subheader("Nucleotide Frequencies")
    nucleotide_dict = {
        'Nucleotide': ['A', 'T', 'G', 'C'],
        'Count': [a_count, t_count, g_count, c_count]
    }
    df = pd.DataFrame(nucleotide_dict)
    
    # Display table and chart side-by-side
    col3, col4 = st.columns(2)
    with col3:
        ########## Display DataFrame as table ########
    with col4:
        # Streamlit's native bar chart requires the index to be the categorical variable
        chart_data = df.set_index('Nucleotide')
        st.bar_chart(chart_data)
else:
    st.warning("Please enter a DNA sequence to begin analysis.")

Assignment

After testing and completing your app, submit the following on Blackboard: a copy of your completed script and a screenshot of the app running in your browser.