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Rup (RNA-seq Usability Assessment Pipeline) - Quality Control for Bulk RNA-seq Experiments in Eukaryotes
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RNA-seq: Basic Bioinformatics Analysis.

Fei Ji1,2, Ruslan I Sadreyev1,3

  • 1Department of Molecular Biology, Massachusetts General Hospital, Boston, Massachusetts.

Current Protocols in Molecular Biology
|September 18, 2018
PubMed
Summary
This summary is machine-generated.

This study introduces a bioinformatics workflow for analyzing RNA-sequencing (RNA-seq) data to quantify gene expression. It details tools for assessing RNA-seq data quality and identifying differentially expressed genes between conditions.

Keywords:
RNA-seqbioinformaticsdifferentially expressed genesquantitative analysis of gene expression

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Area of Science:

  • Genomics
  • Bioinformatics
  • Molecular Biology

Background:

  • Quantitative gene expression analysis is vital for understanding genome regulation.
  • RNA-sequencing (RNA-seq) offers a comprehensive approach to transcriptome investigation.

Purpose of the Study:

  • To present a general bioinformatics workflow for quantitative RNA-seq data analysis.
  • To highlight publicly available computational tools for each step of the workflow.

Main Methods:

  • The workflow begins with raw sequencing files.
  • It includes quality assessment and quantitation of RNA-seq data.
  • Focuses on identifying and analyzing differentially expressed genes.

Main Results:

  • A pipeline for RNA-seq data analysis is described.
  • The pipeline facilitates the identification of genes with altered expression between biological conditions.

Conclusions:

  • The presented workflow and tools enable robust quantitative analysis of RNA-seq data.
  • This facilitates the study of molecular mechanisms in genome regulation.