R-Cloud Workbench

R-Cloud Workbench enables remote R/Bioconductor-based processing, expression estimation, and quality assessment of high-throughput RNA-seq datasets using the ArrayExpressHTS pipeline on EBI's 64-bit Linux Cluster.


Key Features:

  • Remote R execution and scalability: Executes R/Bioconductor on EBI's 64-bit Linux Cluster to provide scalable compute and storage for high-throughput RNA-seq analyses.
  • ArrayExpressHTS pipeline integration: Integrates ArrayExpressHTS for pre-processing, expression estimation, and quality assessment of RNA-seq data.
  • Bioconductor object generation: Transforms raw sequence files into standard Bioconductor R objects suitable for downstream analysis.
  • Data quality assessment: Generates comprehensive reports to support thorough data quality assessment.
  • Data access and extensibility: Provides access to public RNA-seq datasets in the ArrayExpress Archive and supports analysis of user-provided datasets and installation of additional R/Bioconductor packages.

Scientific Applications:

  • Transcriptome profiling: Processing and expression estimation for RNA-seq-based transcriptome analyses.
  • Large-scale RNA-seq projects: Analysis of large datasets requiring distributed computation and extensive memory resources.
  • Comparative and integrative studies: Comparative analyses using public RNA-seq datasets from the ArrayExpress Archive.

Methodology:

Runs R/Bioconductor locally or remotely on EBI's distributed R-cloud farm, employs the ArrayExpressHTS pipeline for pre-processing, expression estimation, and quality assessment, converts raw sequence files into Bioconductor R objects, and produces quality assessment reports.

Topics

Details

Tool Type:
desktop application
Operating Systems:
Linux, Windows, Mac
Programming Languages:
Java
Added:
8/3/2017
Last Updated:
11/25/2024

Operations

Publications

Goncalves A, Tikhonov A, Brazma A, Kapushesky M. A pipeline for RNA-seq data processing and quality assessment. Bioinformatics. 2011;27(6):867-869. doi:10.1093/bioinformatics/btr012. PMID:21233166. PMCID:PMC3051320.

Documentation

Links