본문으로 건너뛰기
cccskills
무료GitHub에 공개

bioconductor-txdbmaker

A set of tools for making TxDb objects from genomic annotations from various sources (e.g. UCSC, Ensembl, and GFF files). These tools allow the user to download the genomic locations of transcripts, exons, and CDS, for a given assembly, and

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

설치 방법 보기

포함된 파일(1)

  • SKILL.md5.0 KB

SKILL.md(원문)

설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.

txdbmaker

Dependencies & Environment

Package-intrinsic requirements from the Bioconductor landing page — reproduce in any R environment.

  • Version: 1.8.0 · Bioconductor: 3.23 · R: ≥ 4.6
  • Depends: BiocGenerics, S4Vectors, Seqinfo, GenomicRanges, GenomicFeatures
  • Imports: httr, rjson, DBI, RSQLite, IRanges, UCSC.utils, GenomeInfoDb, AnnotationDbi, Biobase, BiocIO, rtracklayer, biomaRt
  • Install: BiocManager::install("txdbmaker")

When to Use

  • Creating TxDb objects from UCSC Genome Browser transcript tables using makeTxDbFromUCSC.
  • Retrieving and assembling transcript annotations from BioMart datasets using makeTxDbFromBiomart.
  • Extracting transcript information directly from GFF3 or GTF files using makeTxDbFromGFF.
  • Saving and loading created TxDb objects to/from SQLite database files using saveDb and loadDb to avoid repeated download times.
  • Wrapping a generated database directly into an installable annotation package using makeTxDbPackageFromUCSC or makeTxDbPackageFromBiomart.

When NOT to Use

  • For extracting features (like transcripts, exons, and CDS) from an already created TxDb object, use GenomicFeatures instead, which implements the flexible extraction methods.
  • For creating TxDb objects from unsupported BioMart datasets (not all BioMart datasets are currently supported by makeTxDbFromBiomart).

Data Requirements

  • UCSC: A valid genome build (e.g., "mm9", "hg19") and a supported transcript table (e.g., "knownGene", "refGene").
  • BioMart: A supported BioMart dataset name (e.g., "mmusculus_gene_ensembl").
  • Files: Local GFF3 or GTF files containing transcript annotations.

Key Parameters

  • genome (default): Specifies the genome build (e.g., "mm9") when downloading tables from UCSC.
  • tablename (default): Specifies the specific UCSC transcript table to download (e.g., "knownGene").
  • dataset (default): Specifies the BioMart dataset to retrieve (e.g., "mmusculus_gene_ensembl").
  • circ_seqs (default): A vector specifying which sequences are circular; defaults to the contents of DEFAULT_CIRC_SEQS.
  • file (default): The file path used to save or load the SQLite database in saveDb and loadDb.

Best Practices

  • Use the supportedUCSCtables utility function to get a list of tables known to work with makeTxDbFromUCSC for your specific genome build.
  • Save your annotation objects using saveDb and label them with an appropriate time stamp to facilitate reproducible research and avoid bandwidth costs.
  • Use the helper function getChromInfoFromBiomart to check what the different chromosomes are called for a given BioMart source before building the TxDb.

Common Pitfalls

  • Re-downloading and assembling databases from UCSC or BioMart every time a script is run. Fix: Use saveDb to save the object locally and loadDb to initialize it from the .sqlite file in future sessions.
  • Attempting to serialize a TxDb object using R's base save function. Fix: Use saveDb instead, because TxDb objects are backed by a SQLite database and cannot be serialized normally.

Alternatives

  • GenomicFeatures: The companion package where TxDb objects are actually implemented and which provides the methods to extract features from them.
  • AnnotationDbi: For querying standard Bioconductor annotation packages (e.g., OrgDb) rather than building transcript-centric databases.

Citations

  • Marc Carlson, Patrick Aboyoun, Hervé Pagès, Seth Falcon and Martin Morgan. Making TxDb Objects. Package txdbmaker.

References

  • Homepage: bioconductor.org/packages/txdbmaker
  • Vignette: vignette_0_4310e349.txt
<!-- biomate-cta -->

Run this on BioMate

This skill is the knowledge layer — when, why, and how to use txdbmaker. To run this analysis on your own data with managed compute, automated QC, and reproducible outputs, use BioMate — free to start.

▶ Open txdbmaker on BioMate →

리뷰

아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.

댓글

로그인 없이 쓸 수 있습니다. 사용 후기, 질문, 작동하지 않은 환경 등을 편하게 남겨 주세요.

아직 댓글이 없습니다. 첫 댓글을 남겨 보세요.

보내면 바로 공개됩니다. 이메일 주소나 전화번호 같은 개인 정보는 쓰지 마세요. URL은 2개까지입니다.

0 / 1,000자

이 양식은 reCAPTCHA로 보호되며 Google 개인정보처리방침 및 서비스 약관이 적용됩니다.

같은 저장소의 스킬

The package contains functions for exploratory oligonucleotide array analysis. The dependence on tkWidgets only concerns few convenience functions. 'affy' is fully functional without it.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

bioMate-AI/biomate-bioconductor-kb7972026년 6월 21일 업데이트

This tool uses the label-tree function from HyPhy to annotate a phylogenetic tree. It allows users to select a subset of leaves using either a regular expression or a list of sequence names, and then apply a specified label to these selecte

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

bioMate-AI/biomate-bioconductor-kb7972026년 6월 21일 업데이트

This package provides a client for the Bioconductor AnnotationHub web resource. The AnnotationHub web resource provides a central location where genomic files (e.g., VCF, bed, wig) and other resources from standard locations (e.g., UCSC, En

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

bioMate-AI/biomate-bioconductor-kb7972026년 6월 21일 업데이트

apeglm provides Bayesian shrinkage estimators for effect sizes for a variety of GLM models, using approximation of the posterior for individual coefficients.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

bioMate-AI/biomate-bioconductor-kb7972026년 6월 21일 업데이트

ASURAT is a software for single-cell data analysis. Using ASURAT, one can simultaneously perform unsupervised clustering and biological interpretation in terms of cell type, disease, biological process, and signaling pathway activity. Inputting a single-cell RNA-seq data and knowledge-based databases, such as Cell Ontology, Gene Ontology, KEGG, etc., ASURAT transforms gene expression tables into original multivariate tables, termed sign-by-sample matrices (SSMs).

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

bioMate-AI/biomate-bioconductor-kb7972026년 6월 21일 업데이트

AUCell allows to identify cells with active gene sets (e.g. signatures, gene modules...) in single-cell RNA-seq data. AUCell uses the "Area Under the Curve" (AUC) to calculate whether a critical subset of the input gene set is enriched with

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

bioMate-AI/biomate-bioconductor-kb7972026년 6월 21일 업데이트

bioMate-AI의 스킬 모두 보기

이 스킬의 문제 신고