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Transcriptomics

Single-cell and bulk RNA-seq analysis agents

lobster-transcriptomics
FreeBeginner

Single-cell and bulk RNA-seq: QC, clustering, differential expression, and pathway analysis

Input
10X GenomicsH5ADCSVGEO
Output
QC ReportClustersUMAPDE GenesPathways
Agents (3)
└── transcriptomics_expertWorkflow orchestration and delegation
├── annotation_expertCell type annotation and QC
└── de_analysis_expertDifferential expression analysis
pip install lobster-transcriptomics

Agents

transcriptomics_expert

The main orchestrator for transcriptomics workflows, coordinating between specialized sub-agents.

Capabilities:

  • Workflow planning for scRNA-seq and bulk RNA-seq
  • Delegation to specialized sub-agents
  • Result synthesis and interpretation

annotation_expert

Specialized agent for single-cell RNA-seq quality control.

Capabilities:

  • Cell quality filtering (min genes, min counts)
  • Doublet detection (Scrublet integration)
  • Mitochondrial content analysis
  • Quality metrics visualization

Example workflow:

"Run quality control on my scRNA-seq data with default parameters"

de_analysis_expert

Specialized agent for bulk RNA-seq differential expression analysis.

Capabilities:

  • Differential expression (DESeq2, pyDESeq2)
  • Contrast definition and execution
  • Volcano plots and MA plots
  • Pathway enrichment integration

Example Workflows

Single-Cell Analysis

User: Load the data from GSE164378 and run a complete single-cell analysis

[transcriptomics_expert delegates to annotation_expert]
- Quality control filtering
- Normalization
- Variable gene selection
- Dimensionality reduction (PCA)
- Clustering (Leiden)
- UMAP visualization

Bulk RNA-seq

User: I have bulk RNA-seq data from treated vs control samples.
      Run differential expression analysis.

[transcriptomics_expert delegates to de_analysis_expert]
- Sample group assignment
- DESeq2 differential expression
- Volcano plot generation
- Top differentially expressed genes table

Dependencies

lobster-transcriptomics requires domain-specific libraries:

LibraryPurpose
scanpySingle-cell analysis framework
pydeseq2DESeq2 Python implementation
scrubletDoublet detection
leidenalgCommunity detection for clustering

These are installed automatically with the package.

Services

lobster-transcriptomics includes domain-specific services bundled with the package:

ServicePurpose
EnhancedSingleCellServiceComplete scRNA-seq analysis pipeline (QC, normalization, clustering)
QualityServiceCell and gene quality metrics
PreprocessingServiceData filtering and normalization
DifferentialFormulaServiceFormula-based differential expression (DESeq2-style)
PseudobulkServiceAggregate single-cell data to pseudobulk
BulkVisualizationServiceVolcano plots, MA plots, heatmaps for bulk RNA-seq
ManualAnnotationServiceManual cell type annotation workflow
AnnotationTemplateServicePre-defined marker gene templates

Services are installed automatically with the agent package and accessed internally by the agents.

Configuration

Enable transcriptomics agents in your workspace config:

# .lobster_workspace/config.toml
enabled = ["transcriptomics_expert", "annotation_expert", "de_analysis_expert"]

Or use a preset:

preset = "scrna-full"

Sub-Agent Architecture

transcriptomics_expert (supervisor)
|-- annotation_expert (sub-agent, not directly accessible)
|-- de_analysis_expert (sub-agent, not directly accessible)

Sub-agents are accessed through transcriptomics_expert delegation, not directly from the supervisor. This architecture allows the orchestrator to:

  1. Plan workflows - Determine which sub-agent is needed
  2. Manage state - Track analysis progress across steps
  3. Synthesize results - Combine outputs from multiple sub-agents

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