tximeta

tximeta automates the annotation and metadata integration during import of transcript quantification files to link RNA-seq quantifications to their reference transcriptomes and support reproducible genomic analyses.


Key Features:

  • R/Bioconductor package: Implemented within the R/Bioconductor ecosystem for integration with Bioconductor workflows.
  • Automatic annotation metadata integration: Adds essential annotation metadata during import of transcript quantification files to ensure accurate metadata linkage.
  • Reference transcriptome identification: Identifies the correct reference transcriptome by using a hashed checksum stored in the quantification output.
  • Database download and caching: Automatically downloads matching transcript databases and caches them locally for reuse.
  • Facilitation of genomic workflows: Automates metadata addition based on reference sequence checksums to reduce annotation errors and support reproducibility in genomic analyses.

Scientific Applications:

  • Transcriptomics and gene expression analysis: Ensures transcript quantifications are correctly linked to reference annotations for reliable gene expression studies.
  • Preprocessing and data import: Streamlines import steps by integrating annotation metadata into transcript quantification imports.
  • Reproducible research: Provides a consistent method to link quantification files to their sources, supporting reproducible analyses.

Methodology:

Uses reference sequence checksums (hashed checksums embedded in quantification output) to identify reference transcriptomes, automatically downloads and locally caches matching transcript databases, and integrates annotation metadata during import of transcript quantification files.

Topics

Details

License:
GPL-2.0
Programming Languages:
R
Added:
11/14/2019
Last Updated:
12/31/2020

Operations

Publications

Love MI, Soneson C, Hickey PF, Johnson LK, Pierce NT, Shepherd L, Morgan M, Patro R. Tximeta: reference sequence checksums for provenance identification in RNA-seq. Unknown Journal. 2019. doi:10.1101/777888.

Links