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import streamlit as st
st.sidebar.markdown('''
# Sections
- [How to use](#how-to-use)
''', unsafe_allow_html=True)
st.markdown('''
# ProtHGT User Guide
''')
import streamlit as st
st.markdown("""
ProtHGT is a web-based tool for **automated protein function prediction** using heterogeneous graph transformers and knowledge graphs. Follow the steps below to generate predictions for your proteins.
""")
st.subheader("1. Select Proteins")
st.markdown("""
In the **sidebar**, choose how to input your proteins:
- **Search Proteins**: Select or search UniProt IDs from the available dataset.
- **Upload a File**: Upload a text file (.txt) containing UniProt IDs (one per line, max 100).
""")
st.warning("⚠️ Only proteins included in our input knowledge graph can be processed. If your protein is missing, real-time retrieval from external sources is not yet supported.")
st.info("📥 Selected proteins can be downloaded as a txt file.")
st.subheader("2. Choose Gene Ontology (GO) Category")
st.markdown("""
Select which **Gene Ontology (GO) sub-ontology** to use for function prediction:
- **Molecular Function (MF)** – Biochemical activity of the protein
- **Biological Process (BP)** – Biological roles and pathways
- **Cellular Component (CC)** – Location within the cell
- **All Categories** – Runs predictions for all three categories
""")
st.subheader("3. Generate Predictions")
st.markdown("""
Click **"Generate Predictions"** to start the analysis. The model will process the selected proteins and return predicted functional annotations.
🔄 **Processing time**: A few minutes (depending on input size).
""")
st.subheader("4. View and Filter Results")
st.markdown("""
Once predictions are generated, use the filter options to refine the output:
- **Filter by Protein** (UniProt ID)
- **Filter by GO Category**
- **Set Probability Range** (Adjust prediction confidence thresholds)
Results are displayed in a sortable table, with **probabilities** indicating prediction confidence.
""")
st.info("📥 Filtered predictions can be downloaded as a CSV file.")
st.subheader("5. Reset and Start Over")
st.markdown("""
To reset your selections and run new predictions, click **"Reset"** in the sidebar.
""")
st.subheader("🚀 Running Locally?")
st.markdown("""
For **larger datasets** or **custom analyses**, you can run ProtHGT locally using our **GitHub repository**:
[🔗 ProtHGT GitHub](https://github.com/HUBioDataLab/ProtHGT)
""")
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