用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
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npx skills add https://github.com/bioMate-AI/biomate-bioconductor-kb --skill bioconductor-bsgenome命令会保持在同一行。复制前请横向滚动并检查完整内容。
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In recent years a wealth of biological data has become available in public data repositories. Easy access to these valuable data resources and firm integration with data analysis is needed for comprehensive bioinformatics data analysis. bio
KEGGGraph is an interface between KEGG pathway and graph object as well as a collection of tools to analyze, dissect and visualize these graphs. It parses the regularly updated KGML (KEGG XML) files into graph models maintaining all essenti
The 'enrichplot' package implements several visualization methods for interpreting functional enrichment results obtained from ORA or GSEA analysis. It is mainly designed to work with the 'clusterProfiler' package suite. All the visualizati
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| name | bioconductor-bsgenome |
| description | Infrastructure shared by all the Biostrings-based genome data packages. |
| when_to_use | Use when: Chromosome Pattern Matching: Finding or counting the occurrences of an arbitrary nucleotide pattern in a specific chromosome using matchPattern() or countPattern().; Genome-Wide Dictionary Searches: Finding all occurrences of a constant-width dictionary of patterns across an entire genome using PDict() and matchPDict().; Sequence Masking: Applying or toggling masks (e.g., assembly gaps, repeats) o. Not for: For querying remote sequence databases on-the-fly without local storage, use biomaRt instead, as BSgenome relies on locally installed data packages.; For extracting transcript or exon sequences, use GenomicFeatures instead, because BSgenome provides |
| user-invocable | false |
Package-intrinsic requirements from the Bioconductor landing page — reproduce in any R environment.
BiocManager::install("BSgenome")matchPattern() or countPattern().PDict() and matchPDict().masks() and active() before performing sequence analysis.BSgenome relies on locally installed data packages.BSgenome provides raw chromosome sequences rather than gene models.BSgenome data package (e.g., BSgenome.Celegans.UCSC.ce2).DNAStringSet using readDNAStringSet().matchPattern().countPattern().seqinfo() and seqnames() to verify chromosome naming conventions and lengths before starting an analysis.subject <- genome[[seqname]]) to avoid memory allocation problems on large genomes.reverseComplement() of the short query pattern rather than the entire chromosome subject.for loop and seqnames().reverseComplement() to an entire chromosome sequence. Fix: Apply reverseComplement() to the short query pattern instead.active(masks(chrY)) <- FALSE.This skill is the knowledge layer — when, why, and how to use bsgenome. To run this analysis on your own data with managed compute, automated QC, and reproducible outputs, use BioMate — free to start.