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Related Concept Videos

RNA-seq03:21

RNA-seq

RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases. 
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while microarray-based...

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Related Experiment Video

Updated: May 8, 2026

Analyzing Multifactorial RNA-Seq Experiments with DiCoExpress
05:22

Analyzing Multifactorial RNA-Seq Experiments with DiCoExpress

Published on: July 29, 2022

DoReMiTra: an R/Bioconductor data package for orchestrating the analysis of radiation transcriptomic studies.

Ahmed Salah1,2, Sebastian Zahnreich1, Federico Marini2,3

  • 1Department of Radiation Oncology and Radiation Therapy, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, 55131, Germany.

Bioinformatics Advances
|May 7, 2026
PubMed
Summary
This summary is machine-generated.

A new R/Bioconductor data package, DoReMiTra, offers a unified collection of radiation transcriptomics datasets. This resource aids researchers in analyzing cellular responses to radiation exposure and discovering biomarkers.

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Related Experiment Videos

Last Updated: May 8, 2026

Analyzing Multifactorial RNA-Seq Experiments with DiCoExpress
05:22

Analyzing Multifactorial RNA-Seq Experiments with DiCoExpress

Published on: July 29, 2022

High-Throughput Transcriptome Analysis for Investigating Host-Pathogen Interactions
14:58

High-Throughput Transcriptome Analysis for Investigating Host-Pathogen Interactions

Published on: March 5, 2022

Area of Science:

  • Molecular Biology
  • Bioinformatics
  • Radiation Biology

Background:

  • Understanding cellular responses to ionizing radiation is crucial for biomedical research and public health.
  • Transcriptomics assays, including microarrays and RNA sequencing, are key tools for studying radiation's molecular impact.
  • A unified, well-curated collection of radiation transcriptomic datasets has been lacking.

Purpose of the Study:

  • To introduce DoReMiTra, the first R/Bioconductor data package consolidating radiation transcriptomics datasets.
  • To provide standardized, harmonized metadata and pre-processed data for comparative analyses.
  • To facilitate radiation research through a centralized resource and interactive exploration tool.

Main Methods:

  • Development of an R/Bioconductor data package named DoReMiTra.
  • Integration with Bioconductor's ExperimentHub for data distribution.
  • Standardization and harmonization of sample-level metadata.
  • Provision of pre-processed SummarizedExperiment objects.
  • Development of a Shiny app for interactive visualization.

Main Results:

  • DoReMiTra offers a unified collection of radiation transcriptomic datasets.
  • The package provides standardized metadata and pre-processed data objects.
  • An accompanying Shiny app allows for interactive data exploration.
  • The resource is available under the MIT license.

Conclusions:

  • DoReMiTra serves as a valuable resource for radiation research.
  • It facilitates benchmarking, integrative analyses, and biomarker discovery.
  • The package promotes efficient distribution and utilization of radiation transcriptomic data.