Bioinformatics Pipeline
AvanzadadataContexto mínimo: 128K
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.
Casos de uso
- 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
Prompt de ejemplo
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
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Modalidades
Entrada: text, code, file
→Salida: text, code
Skills relacionadas
Autor
OpenModels Community