identify_controversial_clusters

Identify controversial clusters based on consensus analysis

internal

Automated cell type annotation for single-cell RNA sequencing data
using consensus predictions from multiple large language models (LLMs). LLMs are
artificial intelligence models trained on vast text corpora to understand and
generate human-like text. This package integrates with 'Seurat' objects and
provides uncertainty quantification for annotations. Supports various LLM
providers including 'OpenAI', 'Anthropic', and 'Google'. The package leverages
these models through their respective APIs (Application Programming Interfaces)
<https://platform.openai.com/docs>, <https://docs.anthropic.com/>, and
<https://ai.google.dev/gemini-api/docs>.
For details see Yang et al. (2025) <doi:10.1101/2025.04.10.647852>.

Chen Yang

mLLMCelltype

Cell Type Annotation Using Large Language Models

identify_controversial_clusters function

<dl><dt>input</dt>
<dd>Either the differential gene table or a list of genes</dd>
<dt>individual_predictions</dt>
<dd>List of predictions from each model</dd>
<dt>controversy_threshold</dt>
<dd>Threshold for marking clusters as controversial</dd>
<dt>entropy_threshold</dt>
<dd>Entropy threshold for identifying controversial clusters</dd></dl>

Arguments

Identify controversial clusters based on consensus analysis — identify_controversial_clusters

<dl>

<dt>input</dt>
<dd>Either the differential gene table or a list of genes</dd>


<dt>individual_predictions</dt>
<dd>List of predictions from each model</dd>


<dt>controversy_threshold</dt>
<dd>Threshold for marking clusters as controversial</dd>


<dt>entropy_threshold</dt>
<dd>Entropy threshold for identifying controversial clusters</dd>

</dl>

identify_controversial_clusters: Identify controversial clusters based on consensus analysis

Description

Usage

Value

Arguments