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e3df29c
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Parent(s):
e9e3c0c
Update ASCARIS.py
Browse files- ASCARIS.py +9 -7
ASCARIS.py
CHANGED
@@ -33,18 +33,19 @@ st.write('')
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st.write('')
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with st.form('mform', clear_on_submit=False):
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source = st.selectbox('Select the protein structure resource (1: PDB-SwissModel-Modbase, 2: AlphaFold)',[1,2])
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impute = st.selectbox('Imputation',[True, False])
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input_data = st.text_input('Enter SAV data points (
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)
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parser = argparse.ArgumentParser(description='ASCARIS')
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parser.add_argument('-s', '--source_option',
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parser.add_argument('-i', '--input_datapoint',
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help='Input file or query datapoint\n Option 1: Comma-separated list of identifiers (UniProt ID-wt residue-position-mutated residue (e.g. Q9Y4W6-N-432-T or Q9Y4W6-N-432-T, Q9Y4W6-N-432-T)) \n Option 2: Enter comma-separated file path')
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@@ -64,6 +65,7 @@ with st.form('mform', clear_on_submit=False):
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selected_df = pd.DataFrame()
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if submitted:
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with st.spinner('In progress...This may take a while...'):
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try:
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@@ -89,11 +91,11 @@ if submitted:
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st.success('Feature vector successfully created.')
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csv = convert_df(selected_df)
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st.download_button("Press to Download the Feature Vector", csv,"
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else:
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st.success('Feature vector failed. Check log file.')
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st.write('')
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with st.form('mform', clear_on_submit=False):
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#source = st.selectbox('Select the protein structure resource (1: PDB-SwissModel-Modbase, 2: AlphaFold)',[1,2])
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source = 1
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impute = st.selectbox('Imputation',[True, False])
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input_data = st.text_input('Enter SAV data points (Example: Q9Y4W6-N-432-T')
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)
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parser = argparse.ArgumentParser(description='ASCARIS')
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#parser.add_argument('-s', '--source_option',
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# help='Selection of input structure data.\n 1: PDB Structures (default), 2: AlphaFold Structures',
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# default=1)
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parser.add_argument('-i', '--input_datapoint',
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help='Input file or query datapoint\n Option 1: Comma-separated list of identifiers (UniProt ID-wt residue-position-mutated residue (e.g. Q9Y4W6-N-432-T or Q9Y4W6-N-432-T, Q9Y4W6-N-432-T)) \n Option 2: Enter comma-separated file path')
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selected_df = pd.DataFrame()
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st.write('The online tool may be slow, especially while processing multiple SAVs, please consider using the local programmatic version at https://github.com/HUBioDataLab/ASCARIS/')
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if submitted:
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with st.spinner('In progress...This may take a while...'):
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try:
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st.success('Feature vector successfully created.')
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csv = convert_df(selected_df)
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st.download_button("Press to Download the Feature Vector", csv,f"ASCARIS_SAV_rep_{input_set}.csv","text/csv",key='download-csv')
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else:
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st.success('Feature vector failed. Check log file.')
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