The seeker R package: simplified fetching and processing of transcriptome data
Abstract
Transcriptome data have become invaluable for interrogating biological systems. Preparing a transcriptome dataset for analysis, particularly an RNA-seq dataset, entails multiple steps and software programs, each with its own command-line interface (CLI). Although these CLIs are powerful, they often require shell scripting for automation and parallelization, which can have a high learning curve, especially when the details of the CLIs vary from one tool to another. However, many individuals working with transcriptome data are already familiar with R due to the plethora and popularity of R-based tools for analyzing biological data. Thus, we developed an R package called seeker for simplified fetching and processing of RNA-seq and microarray data. Seeker is a wrapper around various existing tools, and provides a standard interface, simple parallelization, and detailed logging. Seekers primary output--sample metadata and gene expression values based on Entrez or Ensembl Gene IDs--can be directly plugged into a differential expression analysis. To maximize reproducibility, seeker is available as a standalone R package and in a Docker image that includes all dependencies, both of which are accessible at https://seeker.hugheylab.org.
02 /Specification & Classification
Click any tag to browse matching papers- Citations
- 4
- FWCI
- 0.33
- Field percentile
- 47th percentile
- Assay
- Research Focus
- Approach
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- FetchR: an intuitive end-to-end solution for local RNA-Seq analyses
Dustin R Fetch, Alexey A. Soshnev·bioRxiv·Aug 4, 2026
- ERSAtool: A User-Friendly R/Shiny Comprehensive Transcriptomic Analysis Interface Suitable for Education
Sujith Taridalu, Ayyappa Kumar Sista Kameshwar, Masako Suzuki·Genes to CellsPeer-reviewed·Aug 18, 2025
- RNASeqR: an R package for automated two-group RNA-Seq analysis workflow
Kuan-Hao Chao, Yi-Wen Hsiao, … Eric Yao-Yu Chuang·IEEE Transactions on Computational Biology and BioinformaticsPeer-reviewed·Dec 2, 2019
- The recount3 Python package for programmatic access to uniformly processed RNA-seq data
Alexander Alsalihi, Robert M Flight, Hunter Moseley·bioRxiv·Jun 20, 2026
- GEO2RNAseq: An easy-to-use R pipeline for complete pre-processing of RNA-seq data
Bastian Seelbinder, Thomas Wolf, … Jörg Linde·bioRxiv·Sep 16, 2019
- ideal: an R/Bioconductor package for Interactive Differential Expression Analysis
Fédérico Marini, Jan Linke, Harald Binder·BMC BioinformaticsPeer-reviewed·Dec 1, 2020