06 Visualization Dashboards
Jupyter notebook from the Antibiotic Resistance Hotspots in Microbial Pangenomes project.
Phase 6: Integration & Interactive Visualizations¶
This notebook creates publication-quality figures and interactive dashboards from analysis phases 1-5.
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import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
from plotly import express as px
from plotly import graph_objects as go
print("Phase 6: Visualization & Dashboards")
Load Analysis Results¶
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# TODO: Load results from previous phases
# arg_df = pd.read_csv('../data/arg_annotations.csv')
# hotspots_df = pd.read_csv('../data/hotspot_species.csv')
# fitness_df = pd.read_csv('../data/fitness_results.csv')
print("Results loading in progress...")
Figure 1: Top Hotspot Species¶
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# TODO: Create bar chart of top 20 hotspot species by prevalence and diversity
print("Figure 1 in progress...")
Figure 2: Phylogenetic Distribution¶
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# TODO: Create phylogenetic tree with ARG distribution heatmap
print("Figure 2 in progress...")
Figure 3: Fitness Trade-offs¶
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# TODO: Create scatter plot of ARG prevalence vs. fitness cost
print("Figure 3 in progress...")
Interactive Dashboard¶
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# TODO: Create Plotly dashboard with filters for:
# - Drug class selection
# - Phylogenetic level (phylum, class, order, species)
# - Prevalence range
# - Environment filters (if available)
print("Interactive dashboard in progress...")
Summary Statistics¶
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# TODO: Generate summary statistics for publication
print("Summary statistics in progress...")