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<!DOCTYPE html>
<html lang="en">
<head>
    <meta charset="UTF-8">
    <meta name="viewport" content="width=device-width, initial-scale=1.0">
    <title>spCellEval Methods</title>
    <script src="https://cdn.tailwindcss.com"></script>
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    <style>
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</head>
<body class="solid-bg font-sans antialiased">
    <header class="fixed top-0 left-0 right-0 z-50 bg-gray-900/70 backdrop-blur-lg border-b border-gray-700/50">
        <div class="container mx-auto px-6 py-3 flex justify-between items-center">
            <a href="index.html" class="flex items-center space-x-3">
                <img src="./plotly_figures/logo_example.png" alt="Cell Phenotyping Logo" width="56" height="56" class="transition-transform duration-300 hover:scale-110">
                <span class="text-xl font-bold tracking-tight text-white">spCellEval</span>
            </a>
            <nav class="hidden md:flex space-x-10">
                <a href="index.html#about" class="text-gray-300 hover:text-indigo-400 transition-colors">About</a>
                <a href="results.html" class="text-gray-300 hover:text-indigo-400 transition-colors">Results</a>
                <a href="methods.html" class="text-indigo-300 font-semibold">Methods</a>
                <a href="datasets.html" class="text-gray-300 hover:text-indigo-400 transition-colors">Datasets</a>
                <a href="index.html#cta" class="text-gray-300 hover:text-indigo-400 transition-colors">Contact</a>
            </nav>
        </div>
    </header>

    <main class="container mx-auto px-4 pt-32 pb-10">
        <section class="text-center text-white mb-10">
            <h1 class="text-4xl md:text-5xl font-extrabold tracking-tight">Methods</h1>
            <p class="mt-4 max-w-3xl mx-auto text-gray-300">
                This page summarizes the algorithmic families included in spCellEval and the criteria used to assess method performance across datasets.
            </p>
        </section>

        <section class="grid grid-cols-1 md:grid-cols-4 gap-6 mb-8">
            <div class="bg-white/10 rounded-xl p-6 card-hover">
                <i class="fas fa-user-check text-indigo-300 text-2xl mb-3"></i>
                <h2 class="text-white font-semibold text-lg mb-2">Supervised</h2>
                <p class="text-indigo-100 text-sm">Learns explicit labels and generally achieves strongest recovery when high-quality annotations are available.</p>
            </div>
            <div class="bg-white/10 rounded-xl p-6 card-hover">
                <i class="fas fa-project-diagram text-indigo-300 text-2xl mb-3"></i>
                <h2 class="text-white font-semibold text-lg mb-2">Prior-Knowledge Based</h2>
                <p class="text-indigo-100 text-sm">Uses marker panels and biological priors for robust cell typing when labels are scarce.</p>
            </div>
            <div class="bg-white/10 rounded-xl p-6 card-hover">
                <i class="fas fa-layer-group text-indigo-300 text-2xl mb-3"></i>
                <h2 class="text-white font-semibold text-lg mb-2">Unsupervised</h2>
                <p class="text-indigo-100 text-sm">Identifies structure in large cohorts and supports exploratory phenotyping in novel tissues.</p>
            </div>
            <div class="bg-white/10 rounded-xl p-6 card-hover">
                <i class="fas fa-plug-circle-check text-indigo-300 text-2xl mb-3"></i>
                <h2 class="text-white font-semibold text-lg mb-2">Pre-trained</h2>
                <p class="text-indigo-100 text-sm">Enables rapid cell typing in novel tissues using pre-existing models.</p>
            </div>
        </section>

        <section class="bg-white rounded-xl shadow-sm overflow-hidden mb-8">
            <div class="border-b border-gray-100 px-6 py-4">
                <h2 class="text-xl font-semibold text-gray-800">Method Papers</h2>
                <p class="text-gray-500 text-sm">Open the primary paper or publication page for each method in the benchmark.</p>
            </div>
            <div id="methodPaperGrid" class="p-6 space-y-8"></div>
        </section>

        <!-- 
        <section class="bg-white rounded-xl shadow-sm overflow-hidden mb-8">
            <div class="border-b border-gray-100 px-6 py-4">
                <h2 class="text-xl font-semibold text-gray-800">Method Comparison Snapshot</h2>
                <p class="text-gray-500 text-sm">Illustrative examples of method profiles used in the benchmark.</p>
            </div>
            <div class="p-4 overflow-x-auto">
                <table class="w-full border-collapse min-w-[760px]">
                    <thead class="sticky-header">
                        <tr>
                            <th class="method-cell py-3 px-4 text-left font-semibold text-gray-700 border-b text-sm">Method</th>
                            <th class="py-3 px-4 text-left font-semibold text-gray-700 border-b text-sm">Family</th>
                            <th class="py-3 px-4 text-left font-semibold text-gray-700 border-b text-sm">Strength</th>
                            <th class="py-3 px-4 text-left font-semibold text-gray-700 border-b text-sm">Best Use Case</th>
                        </tr>
                    </thead>
                    <tbody>
                        <tr class="border-b hover:bg-gray-50">
                            <td class="method-cell py-3 px-4 text-sm font-medium text-gray-900">scimap</td>
                            <td class="py-3 px-4 text-sm text-gray-700">Prior-knowledge / Gating</td>
                            <td class="py-3 px-4 text-sm text-gray-700">Marker-aware interpretability</td>
                            <td class="py-3 px-4 text-sm text-gray-700">Marker-guided discovery workflows</td>
                        </tr>
                        <tr class="border-b hover:bg-gray-50">
                            <td class="method-cell py-3 px-4 text-sm font-medium text-gray-900">Phenograph</td>
                            <td class="py-3 px-4 text-sm text-gray-700">Unsupervised</td>
                            <td class="py-3 px-4 text-sm text-gray-700">Community detection in high-dimensional space</td>
                            <td class="py-3 px-4 text-sm text-gray-700">Discovery of novel cell states</td>
                        </tr>
                        <tr class="hover:bg-gray-50">
                            <td class="method-cell py-3 px-4 text-sm font-medium text-gray-900">Leiden + UMAP</td>
                            <td class="py-3 px-4 text-sm text-gray-700">Clustering + Visualization</td>
                            <td class="py-3 px-4 text-sm text-gray-700">Scalable exploratory segmentation</td>
                            <td class="py-3 px-4 text-sm text-gray-700">Initial stratification before supervision</td>
                        </tr>
                    </tbody>
                </table>
            </div>
        </section> -->

        <section class="bg-gradient-to-r from-indigo-700 to-teal-700 rounded-xl p-8 text-center">
            <h2 class="text-2xl font-bold text-white">Need Full Quantitative Results?</h2>
            <p class="mt-2 text-indigo-100">Explore the full metric matrix and ranking tables on the homepage Results section.</p>
            <a href="results.html" class="inline-block mt-5 px-6 py-3 bg-white text-indigo-700 font-semibold rounded-lg hover:bg-gray-100 transition-colors">Open Results</a>
        </section>
    </main>
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        "XGBoost": "https://doi.org/10.1145/2939672.2939785",
        "Logistic Regression": "https://doi.org/10.1038/nmeth.3904",
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        "MAPS": "https://doi.org/10.1038/s41467-023-44188-w",
        "CellSighter": "https://doi.org/10.1038/s41467-023-40066-7",
        "Phenograph": "https://doi.org/10.1016/j.cell.2015.05.047",
        "Leiden": "https://doi.org/10.1038/s41598-019-41695-z",
        "CellLENS_Lite": "https://doi.org/10.1038/s41590-025-02163-1",
        "CellLENS_Full": "https://doi.org/10.1038/s41590-025-02163-1",
        "FuseSOM": "https://doi.org/10.1093/bioadv/vbad141",
        "Starling": "https://doi.org/10.1038/s41467-024-55214-w",
        "FlowSOM Meta Clusters": "https://doi.org/10.1002/cyto.a.22625",
        "Scyan": "https://doi.org/10.1093/bib/bbad260",
        "Tacit": "https://doi.org/10.1038/s41467-025-58874-4",
        "Tribus": "https://doi.org/10.1093/bioinformatics/btaf082",
        "Astir": "https://doi.org/10.1016/j.cels.2021.08.012",
        "Nimbus": "https://doi.org/10.1038/s41592-025-02826-9",
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