clean_annotation

Clean annotation text by removing prefixes and extra whitespace

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

clean_annotation function

<dl><dt>annotation</dt>
<dd>The annotation text to clean</dd></dl>

Arguments

Clean annotation text by removing prefixes and extra whitespace — clean_annotation

<dl>

<dt>annotation</dt>
<dd>The annotation text to clean</dd>

</dl>

clean_annotation: Clean annotation text by removing prefixes and extra whitespace

Description

Usage

Value

Arguments