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Main Author: zhanglknt
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Published: Zenodo 2026
Online Access:https://doi.org/10.5281/zenodo.20405459
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author zhanglknt
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contents <h2>CKI v0.2.0</h2> <p>Cell-state Kinetic Index -- automated cell-type identification from single-cell transcriptomics.</p> <h3>What's New</h3> <ul> <li><strong>Auto gene-set detection</strong>: HK genes via detection_rate / CV / combined; functional genes via HVG / markers</li> <li><strong>Simplified API</strong>: <code>compute(adata, species="human", groupby="cell_type", group_a="T", group_b="B")</code></li> <li><strong>Built-in HRT Atlas reference</strong>: Cross-tissue housekeeping gene reference, human & mouse</li> <li><strong>Bootstrap significance testing</strong>: Automatic gene sets with non-parametric p-values</li> <li><strong>Cross-species support</strong>: Human and mouse</li> </ul> <h3>Installation</h3> <pre><code class="language-bash">pip install -e . </code></pre> <h3>Quick Start</h3> <pre><code class="language-python">from cki import compute result = compute(adata, species="human", groupby="cell_type", group_a="T", group_b="B") # -> {"omega": 0.87, "kn": 0.92, "kf": 0.85, ...} </code></pre>
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spellingShingle zhanglknt/CKI-cell-type-identification: CKI v0.2.0
zhanglknt
<h2>CKI v0.2.0</h2> <p>Cell-state Kinetic Index -- automated cell-type identification from single-cell transcriptomics.</p> <h3>What's New</h3> <ul> <li><strong>Auto gene-set detection</strong>: HK genes via detection_rate / CV / combined; functional genes via HVG / markers</li> <li><strong>Simplified API</strong>: <code>compute(adata, species="human", groupby="cell_type", group_a="T", group_b="B")</code></li> <li><strong>Built-in HRT Atlas reference</strong>: Cross-tissue housekeeping gene reference, human & mouse</li> <li><strong>Bootstrap significance testing</strong>: Automatic gene sets with non-parametric p-values</li> <li><strong>Cross-species support</strong>: Human and mouse</li> </ul> <h3>Installation</h3> <pre><code class="language-bash">pip install -e . </code></pre> <h3>Quick Start</h3> <pre><code class="language-python">from cki import compute result = compute(adata, species="human", groupby="cell_type", group_a="T", group_b="B") # -> {"omega": 0.87, "kn": 0.92, "kf": 0.85, ...} </code></pre>
title zhanglknt/CKI-cell-type-identification: CKI v0.2.0
url https://doi.org/10.5281/zenodo.20405459