Tiledbvcf
Skill Verifiziert AktivEfficient storage and retrieval of genomic variant data using TileDB. Scalable VCF/BCF ingestion, incremental sample addition, compressed storage, parallel queries, and export capabilities for population genomics.
To enable researchers and bioinformaticians to efficiently manage and query large genomic variant datasets using the TileDB-VCF framework, streamlining population genomics analyses.
Funktionen
- Scalable VCF/BCF ingestion
- Incremental sample addition
- Compressed storage
- Parallel querying of genomic regions and samples
- Data export to VCF and TSV formats
- Cloud storage integration (S3, Azure, GCS)
Anwendungsfälle
- Building population genomics databases
- Performing genome-wide association studies (GWAS)
- Efficiently querying specific genomic regions across many samples
- Integrating new samples into existing variant datasets incrementally
- Exporting subsets of large VCF datasets for downstream analysis
Nicht-Ziele
- Direct execution of arbitrary C++ TileDB-VCF library functions not exposed through the Python or CLI interfaces
- Replacing comprehensive genome browsers or visualization tools
- Performing complex statistical modeling or machine learning directly on variant data (requires export to other tools)
Errors
- info:Actionable error messagesWhile the documentation mentions common pitfalls, it does not explicitly detail actionable error messages for every failure path, only general recovery steps.
Installation
npx skills add K-Dense-AI/claude-scientific-skillsFührt das Vercel skills CLI (skills.sh) via npx aus — benötigt Node.js lokal und mindestens einen installierten skills-kompatiblen Agent (Claude Code, Cursor, Codex, …). Setzt voraus, dass das Repo dem agentskills.io-Format folgt.
Qualitätspunktzahl
VerifiziertVertrauenssignale
Ähnliche Erweiterungen
Alterlab Tiledbvcf
96Efficient storage and retrieval of genomic variant data using TileDB. Scalable VCF/BCF ingestion, incremental sample addition, compressed storage, parallel queries, and export capabilities for population genomics. Part of the AlterLab Academic Skills suite.
PyDESeq2
100Differential gene expression analysis (Python DESeq2). Identify DE genes from bulk RNA-seq counts, Wald tests, FDR correction, volcano/MA plots, for RNA-seq analysis.
Scanpy
99Standard single-cell RNA-seq analysis pipeline. Use for QC, normalization, dimensionality reduction (PCA/UMAP/t-SNE), clustering, differential expression, and visualization. Best for exploratory scRNA-seq analysis with established workflows. For deep learning models use scvi-tools; for data format questions use anndata.
Pysam
99Genomic file toolkit. Read/write SAM/BAM/CRAM alignments, VCF/BCF variants, FASTA/FASTQ sequences, extract regions, calculate coverage, for NGS data processing pipelines.
Polars Bio
99High-performance genomic interval operations and bioinformatics file I/O on Polars DataFrames. Overlap, nearest, merge, coverage, complement, subtract for BED/VCF/BAM/GFF intervals. Streaming, cloud-native, faster bioframe alternative.
Gtars
99High-performance toolkit for genomic interval analysis in Rust with Python bindings. Use when working with genomic regions, BED files, coverage tracks, overlap detection, tokenization for ML models, or fragment analysis in computational genomics and machine learning applications.