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Related Experiment Video

Updated: May 30, 2026

Optimization for Sequencing and Analysis of Degraded FFPE-RNA Samples
07:30

Optimization for Sequencing and Analysis of Degraded FFPE-RNA Samples

Published on: June 8, 2020

RseqFlow: workflows for RNA-Seq data analysis.

Ying Wang1, Gaurang Mehta, Rajiv Mayani

  • 1Department of Biological Sciences, USC, Los Angeles, CA 90089, USA. wangying@xmu.edu.cn

Bioinformatics (Oxford, England)
|July 29, 2011
PubMed
Summary
This summary is machine-generated.

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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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We created RseqFlow, an RNA-Seq analysis workflow for single-ended Illumina reads. This automated system simplifies data analysis, including quality control, expression analysis, and variant calling, with easy deployment via a virtual machine.

Area of Science:

  • Genomics
  • Bioinformatics

Background:

  • RNA sequencing (RNA-Seq) is crucial for transcriptome analysis.
  • Analyzing single-ended Illumina reads presents specific computational challenges.

Purpose of the Study:

  • To develop an automated and user-friendly RNA-Seq analysis workflow.
  • To integrate essential analytical functions for RNA-Seq data.

Main Methods:

  • Developed RseqFlow, a workflow for single-ended Illumina reads.
  • Utilized the Pegasus Workflow Management System for automation and resource management.
  • Provided RseqFlow as a pre-configured Virtual Machine.

Main Results:

  • RseqFlow includes quality control, read mapping, expression level calculation, differential gene expression analysis, and coding SNP calling.

Related Experiment Videos

Last Updated: May 30, 2026

Optimization for Sequencing and Analysis of Degraded FFPE-RNA Samples
07:30

Optimization for Sequencing and Analysis of Degraded FFPE-RNA Samples

Published on: June 8, 2020

  • The workflow automates the execution of analysis modules in the correct order.
  • The Virtual Machine eliminates complex software configuration and installation.

    • Conclusions:

    • RseqFlow offers a comprehensive and streamlined solution for RNA-Seq data analysis.
    • The workflow simplifies complex bioinformatics pipelines, making them accessible.
    • Automated management and easy deployment enhance the usability of RNA-Seq analysis.