Transcriptomics agents for Lobster AI - single-cell and bulk RNA-seq analysis

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  • License Expression: AGPL-3.0-or-later
    SPDX License Expression
  • Author: Omics-OS
  • Tags bioinformatics , single-cell , RNA-seq , transcriptomics , scRNA-seq , bulk-rnaseq , differential-expression , cell-type-annotation
  • Requires: Python <3.14, >=3.12
  • Provides-Extra: seurat-v3 , doublet-detection , batch-integration
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Project description

lobster-transcriptomics

Single-cell and bulk RNA-seq analysis agents for the Lobster AI platform.

Installation

pip install lobster-transcriptomics

Agents

Agent Description
transcriptomics_expert Parent orchestrator for single-cell and bulk RNA-seq workflows. Handles QC, clustering, and coordinates sub-agents.
annotation_expert Cell type annotation specialist. Automated and manual annotation, debris detection, annotation templates.
de_analysis_expert Differential expression specialist. Pseudobulk aggregation, pyDESeq2, pathway enrichment.

Services

Service Purpose
EnhancedSingleCellService Single-cell clustering and analysis workflows
PseudobulkService Aggregate single-cell data to pseudobulk for DE analysis
DifferentialFormulaService Formula-based differential expression with pyDESeq2
QualityService Comprehensive QC metrics calculation and filtering
PreprocessingService Normalization, log transformation, and preprocessing
ManualAnnotationService Manual cluster annotation with template support
AnnotationTemplates Tissue-specific marker gene templates (PBMC, brain, lung)
BulkVisualizationService Publication-quality plots for bulk RNA-seq results

Features

  • Auto-detection of single-cell vs bulk RNA-seq data types
  • Comprehensive QC metrics including gene counts, mitochondrial %, and ribosomal %
  • Flexible filtering with data-type-appropriate default thresholds
  • Leiden clustering with multi-resolution support and quality metrics
  • UMAP visualization with automatic point size scaling
  • Deviance-based highly variable gene selection
  • Batch correction for multi-sample experimental designs
  • Sub-clustering for heterogeneous cell populations
  • Tissue-specific annotation templates for rapid cell type identification
  • Pseudobulk aggregation from single-cell to bulk format
  • Formula-based DE analysis supporting complex experimental designs
  • GO and KEGG pathway enrichment for biological interpretation

Requirements

  • Python 3.12+
  • lobster-ai >= 1.0.0

Documentation

Full documentation: docs.omics-os.com/docs/agents/transcriptomics

License

MIT

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  • License Expression: AGPL-3.0-or-later
    SPDX License Expression
  • Author: Omics-OS
  • Tags bioinformatics , single-cell , RNA-seq , transcriptomics , scRNA-seq , bulk-rnaseq , differential-expression , cell-type-annotation
  • Requires: Python <3.14, >=3.12
  • Provides-Extra: seurat-v3 , doublet-detection , batch-integration
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