Skip to main content
bioRxiv
  • Home
  • About
  • Submit
  • ALERTS / RSS
Advanced Search
New Results

QuickRNASeq: Guide for Pipeline Implementation and for Interactive Results Visualization

Wen He, Shanrong Zhao, Chi Zhang, Michael S. Vincent, Baohong Zhang
doi: https://doi.org/10.1101/125856
Wen He
1Early Clinical Development, Pfizer Worldwide R&D, Cambridge, MA 02139
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Shanrong Zhao
1Early Clinical Development, Pfizer Worldwide R&D, Cambridge, MA 02139
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Chi Zhang
1Early Clinical Development, Pfizer Worldwide R&D, Cambridge, MA 02139
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Michael S. Vincent
2Inflammation & Immunology Research Unit, Pfizer WRD, Cambridge, MA 02139
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Baohong Zhang
1Early Clinical Development, Pfizer Worldwide R&D, Cambridge, MA 02139
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Preview PDF
Loading

i. Summary/Abstract

Sequencing of transcribed RNA molecules (RNA-seq) has been used wildly for studying cell transcriptomes in bulk or at the single-cell level (1, 2, 3) and is becoming the de facto technology for investigating gene expression level changes in various biological conditions, on the time course, and under drug treatments. Furthermore, RNA-Seq data helped identify fusion genes that are related to certain cancers (4). Differential gene expression before and after drug treatments provides insights to mechanism of action, pharmacodynamics of the drugs, and safety concerns (5). Because each RNA-seq run generates tens to hundreds of millions of short reads with size ranging from 50bp-200bp, a tool that deciphers these short reads to an integrated and digestible analysis report is in high demand. QuickRNASeq (6) is an application for large-scale RNA-seq data analysis and real-time interactive visualization of complex data sets. This application automates the use of several of the best open-source tools to efficiently generate user friendly, easy to share, and ready to publish report. Figure 1 illustrates some of the interactive plots produced by QuickRNASeq. The visualization features of the application have been further improved since its first publication in early 2016. The original QuickRNASeq publication (6) provided details of background, software selection, and implementation. Here, we outline the steps required to implement QuickRNASeq in user’s own environment, as well as demonstrate some basic yet powerful utilities of the advanced interactive visualization modules in the report.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC 4.0 International license.
Back to top
PreviousNext
Posted April 10, 2017.
Download PDF
Email

Thank you for your interest in spreading the word about bioRxiv.

NOTE: Your email address is requested solely to identify you as the sender of this article.

Enter multiple addresses on separate lines or separate them with commas.
QuickRNASeq: Guide for Pipeline Implementation and for Interactive Results Visualization
(Your Name) has forwarded a page to you from bioRxiv
(Your Name) thought you would like to see this page from the bioRxiv website.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Share
QuickRNASeq: Guide for Pipeline Implementation and for Interactive Results Visualization
Wen He, Shanrong Zhao, Chi Zhang, Michael S. Vincent, Baohong Zhang
bioRxiv 125856; doi: https://doi.org/10.1101/125856
Reddit logo Twitter logo Facebook logo LinkedIn logo Mendeley logo
Citation Tools
QuickRNASeq: Guide for Pipeline Implementation and for Interactive Results Visualization
Wen He, Shanrong Zhao, Chi Zhang, Michael S. Vincent, Baohong Zhang
bioRxiv 125856; doi: https://doi.org/10.1101/125856

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Subject Area

  • Bioinformatics
Subject Areas
All Articles
  • Animal Behavior and Cognition (4369)
  • Biochemistry (9550)
  • Bioengineering (7071)
  • Bioinformatics (24776)
  • Biophysics (12567)
  • Cancer Biology (9925)
  • Cell Biology (14299)
  • Clinical Trials (138)
  • Developmental Biology (7931)
  • Ecology (12078)
  • Epidemiology (2067)
  • Evolutionary Biology (15957)
  • Genetics (10904)
  • Genomics (14708)
  • Immunology (9848)
  • Microbiology (23585)
  • Molecular Biology (9456)
  • Neuroscience (50699)
  • Paleontology (369)
  • Pathology (1535)
  • Pharmacology and Toxicology (2674)
  • Physiology (4001)
  • Plant Biology (8643)
  • Scientific Communication and Education (1505)
  • Synthetic Biology (2388)
  • Systems Biology (6415)
  • Zoology (1345)