adapt ToxoCEN-Network here

app.py

@@ -0,0 +1,251 @@
+
+import numpy as np
+import pandas as pd
+import datasets
+import streamlit as st
+from streamlit_cytoscapejs import st_cytoscapejs
+import networkx as nx
+
+st.set_page_config(layout='wide')
+
+# parse out gene_ids from URL query args to it's possible to link to this page
+query_params = st.query_params
+if "gene_ids" in query_params.keys():
+    input_gene_ids = query_params["gene_ids"]
+else:
+    input_gene_ids = "CNAG_04365"
+    
+# use "\n" as the separator so it shows correctly in the text area
+input_gene_ids = input_gene_ids.replace(",", "\n")
+
+if "coexp_score_threshold" in query_params.keys():
+    coexp_score_threshold = query_params["coexp_score_threshold"]        
+else:
+    coexp_score_threshold = "0.85"
+
+if "max_per_gene" in query_params.keys():
+    max_per_gene = query_params["max_per_gene"]        
+else:
+    max_per_gene = "25"
+
+st.markdown("""
+# CryptoCEN Top50 co-expressed partners
+**CryptoCEN** is a co-expression network for *Cryptococcus neoformans* built on 1,524 RNA-seq runs across 34 studies.
+A pair of genes are said to be co-expressed when their expression is correlated across different conditions and
+is often a marker for genes to be involved in similar processes. 
+To Cite:
+    O'Meara MJ, Rapala JR, Nichols CB, Alexandre C, Billmyre RB, Steenwyk JL, A Alspaugh JA, O'Meara TR
+    CryptoCEN: A Co-Expression Network for Cryptococcus neoformans reveals novel proteins involved in DNA damage repair.
+    PLoS Genet 20(2): e1011158. (2024) https://doi.org/10.1371/journal.pgen.1011158
+* Code available at https://github.com/maomlab/CalCEN/tree/master/vignettes/CryptoCEN
+* Full network and dataset: https://huggingface.co/datasets/maomlab/CryptoCEN
+## Plot a network for a set of genes
+Put a ``CNAG_#####`` gene_id, one one each row to seed the network
+""")
+
+
+transcript_annotations = datasets.load_dataset(
+    path = "maomlab/CryptoCEN",
+    data_files = {"transcript_annotations": "transcript_annotations.tsv"})
+transcript_annotations = transcript_annotations["transcript_annotations"].to_pandas()
+
+top_coexp_hits = datasets.load_dataset(
+    path = "maomlab/CryptoCEN",
+    data_files = {"top_coexp_hits": "top_coexp_hits.tsv"})
+top_coexp_hits = top_coexp_hits["top_coexp_hits"].to_pandas()
+
+
+col1, col2, col3 = st.columns(spec = [0.3, 0.2, 0.5])
+with col1:
+    input_gene_ids = st.text_area(
+        label = "Gene IDs",
+        value = f"{input_gene_ids}",
+        height = 130,
+        help = "CNAG Gene ID e.g. CNAG_04365")
+
+
+with col2:
+    coexp_score_threshold = st.text_input(
+        label = "Co-expression threshold [0-1]",
+        value = f"{coexp_score_threshold}",
+        help = "Default: 0.85")
+
+    try:
+        coexp_score_threshold = float(coexp_score_threshold)
+    except:
+        st.error(f"Co-expression threshold should be a number between 0 and 1, instead it is '{coexp_score_threshold}'")
+    if coexp_score_threshold < 0 or 1 < coexp_score_threshold:
+        st.error(f"Co-expression threshold should be a number between 0 and 1, instead it is '{coexp_score_threshold}'")
+
+    max_per_gene = st.text_input(
+        label = "Max per gene",
+        value = f"{max_per_gene}",
+        help = "Default: 25")
+
+    try:
+        max_per_gene = int(max_per_gene)
+    except:
+        st.error(f"Max per gene should be a number greater than 0, instead it is '{max_per_gene}'")
+    if max_per_gene <= 0:
+        st.error(f"Max per gene should be a number greater than 0, instead it is '{max_per_gene}'")
+    
+    
+##################################
+# Parse and check the user input #
+##################################
+
+seed_gene_ids = []
+for input_gene_id in input_gene_ids.split("\n"):
+    gene_id = input_gene_id.strip()
+    if gene_id == "":
+        continue
+    else:
+        seed_gene_ids.append(gene_id)
+
+neighbors = []
+for seed_gene_id in seed_gene_ids:
+    hits = top_coexp_hits[
+            (top_coexp_hits.gene_id_1 == seed_gene_id) & (top_coexp_hits.coexp_score > coexp_score_threshold)]
+    if len(hits.index) > max_per_gene:
+        hits = hits[0:max_per_gene]
+    neighbors.append(hits)
+
+neighbors = pd.concat(neighbors)
+    
+neighbor_gene_ids = list(set(neighbors.gene_id_2))
+gene_ids = seed_gene_ids + neighbor_gene_ids
+gene_types = ['seed'] * len(seed_gene_ids) + ['neighbor'] * len(neighbor_gene_ids)
+
+cnag_ids = []
+gene_names = []
+descriptions = []
+    
+for gene_id in gene_ids:
+    try:
+        cnag_id = transcript_annotations.loc[transcript_annotations["cnag_id"] == gene_id]["cnag_id"].values[0]
+        gene_name = transcript_annotations.loc[transcript_annotations["gene_id"] == gene_id]["gene_name"].values[0]
+        description = transcript_annotations.loc[transcript_annotations["gene_id"] == gene_id]["description"].values[0]
+    except:
+        st.error(f"Unable to locate cnag_id for Gene ID: {gene_id}, it should be of the form 'cnag_######'")
+        cnag_id = None
+        gene_name = None
+        description = None
+
+    cnag_ids.append(cnag_id)
+    gene_names.append(gene_name)
+    descriptions.append(description)
+
+node_info = pd.DataFrame({
+    "gene_index": range(len(gene_ids)),
+    "gene_id" : gene_ids,
+    "gene_type" : gene_types,
+    "cnag_id": cnag_ids,
+    "gene_name": gene_names,
+    "description": description})
+
+neighbors = neighbors.merge(
+    right = node_info,
+    left_on = "gene_id_1",
+    right_on = "gene_id")
+
+neighbors = neighbors.merge(
+    right = node_info,
+    left_on = "gene_id_2",
+    right_on = "gene_id",
+    suffixes = ("_a", "_b"))
+
+################################
+# Use NetworkX to layout graph #
+################################
+# note I think CytoscapeJS can layout graphs
+# but I'm unsure how to do it through the streamlit-cytoscapejs interface :(
+
+st.write(neighbors)
+
+
+G = nx.Graph()
+for i in range(len(neighbors.index)):
+    edge = neighbors.iloc[i]
+    G.add_edge(
+        edge["gene_index_a"],
+        edge["gene_index_b"],
+        weight = edge["coexp_score"])
+layout = nx.spring_layout(G)
+
+
+
+
+node_color_lut = {
+    "seed" : "#4866F0",    # blue
+    "neighbor" : "#F0C547" # gold
+}
+
+elements = []
+singleton_index = 0
+for i in range(len(node_info.index)):
+    node = node_info.iloc[i]
+
+    if node["gene_index"] in layout.keys():
+        layout_x = layout[node["gene_index"]][0] * 600 + 1500/2
+        layout_y = layout[node["gene_index"]][1] * 600 + 1500/2
+    else:
+        layout_x = (singleton_index % 8) * 150 + 100
+        layout_y = np.floor(singleton_index / 8) * 50 + 30
+        singleton_index += 1
+
+    
+    elements.append({
+        "data": {
+            "id": node["gene_id"],
+            "label": node["gene_name"] if node["gene_name"] is not None else node["gene_id"],
+            "color": node_color_lut[node["gene_type"]]},
+        "position": {
+            "x" : layout_x,
+            "y" : layout_y}})
+
+for i in range(len(neighbors.index)):
+    edge = neighbors.iloc[i]
+    elements.append({
+        "data" : {
+            "source" : edge["gene_id_1"],
+            "target" : edge["gene_id_2"],
+            "width" :
+                20 if edge["coexp_score"] > 0.98 else
+                15 if edge["coexp_score"] > 0.93 else
+                10 if edge["coexp_score"] > 0.90 else
+                8  if edge["coexp_score"] > 0.88 else
+                5}})
+
+with col3:
+    st.text('') # help alignment with input box
+    st.download_button(
+        label = "Download as as TSV",
+        data = neighbors.to_csv(sep ='\t').encode('utf-8'),
+        file_name = f"CryptoCEN_network.tsv",
+        mime = "text/csv")
+
+##########################################################
+
+stylesheet = [
+    {"selector": "node", "style": {
+        "width": 140,
+        "height": 30,
+        "shape": "rectangle",
+        "label" : "data(label)",
+        "labelFontSize": 100,
+        'background-color': 'data(color)',
+        "text-halign": "center",
+        "text-valign": "center",
+    }},
+    {"selector": "edge", "style": {
+        "width": "data(width)"
+    }}
+]
+
+st.title("ToxoCEN Network")
+clicked_elements = st_cytoscapejs(
+    elements = elements,
+    stylesheet = stylesheet,
+    width = 1000,
+    height= 1000,
+    key = "1")