Skip to content
cccskills
FreePublished on GitHub

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

The English summary is being prepared. Showing the original description.

See how to install

Files included (1)

  • SKILL.md5.0 KB

SKILL.md (original)

Review the instructions the agent will receive before you install.

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 →

Reviews

No reviews yet. Tell others what you thought.

Comments

No login needed. Share how it worked for you, ask a question, or note where it did not run.

No comments yet. Be the first to write one.

Comments are published right away. Do not include personal information such as email addresses or phone numbers. Up to 2 URLs.

0 / 1,000 characters

This form is protected by reCAPTCHA, and the Google Privacy Policy and Terms of Service apply.

More skills from this repository

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

The English summary is being prepared. Showing the original description.

bioMate-AI/biomate-bioconductor-kb793Updated Jun 21, 2026

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

The English summary is being prepared. Showing the original description.

bioMate-AI/biomate-bioconductor-kb793Updated Jun 21, 2026

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

The English summary is being prepared. Showing the original description.

bioMate-AI/biomate-bioconductor-kb793Updated Jun 21, 2026

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

The English summary is being prepared. Showing the original description.

bioMate-AI/biomate-bioconductor-kb793Updated Jun 21, 2026

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).

The English summary is being prepared. Showing the original description.

bioMate-AI/biomate-bioconductor-kb793Updated Jun 21, 2026

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

The English summary is being prepared. Showing the original description.

bioMate-AI/biomate-bioconductor-kb793Updated Jun 21, 2026

See all skills by bioMate-AI

Report a problem with this skill