Bioinformatics Pipeline

advanceddataMin 128K context

Builds and executes bioinformatics analysis pipelines for genomics, transcriptomics, and proteomics data. Supports single-cell RNA-seq analysis with Scanpy, differential expression with PyDESeq2, sequence alignment, variant calling, gene ontology enrichment, and pathway analysis using KEGG and Reactome databases.

bioinformatics genomics rna-seq single-cell scanpy variant-calling pathway-analysis gene-expression

Use Cases

Single-cell RNA-seq analysis from raw counts to cell type annotation
Differential gene expression analysis between conditions
Gene ontology and pathway enrichment analysis
Building reproducible Snakemake or Nextflow pipelines
Variant annotation and clinical interpretation
Multi-omics data integration workflows

Example Prompt

Build a single-cell RNA-seq analysis pipeline using Scanpy for a 10X Genomics dataset.

The pipeline should include:
1. Data loading (from 10X .h5 or .mtx format)
2. Quality control (filter cells by gene count, mito %, doublet detection)
3. Normalization and log-transformation
4. Highly variable gene selection
5. PCA and batch correction (if multiple samples)
6. Neighborhood graph and UMAP embedding
7. Leiden clustering
8. Marker gene identification per cluster
9. Cell type annotation using known markers
10. Differential expression between conditions

Output:
- Complete Python script with Scanpy
- QC thresholds and rationale
- Expected output files and visualizations
- Tips for parameter tuning

Recommended Models

claude-opus-4-6 gpt-5 gemini-2-5-pro

Compatible Tools

claude-codecursorkiroany

Modalities

Input: text, code, file

→

Output: text, code

Related Skills

data-analysis scientific-visualization

Author

OpenModels Community

@openmodelsrun