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

A NMF-based approach to discover overlooked differentially expressed gene regions from single-cell RNA-seq data

View ORCID ProfileHirotaka Matsumoto, Tetsutaro Hayashi, Haruka Ozaki, Koki Tsuyuzaki, Mana Umeda, Tsuyoshi Iida, Masaya Nakamura, Hideyuki Okano, Itoshi Nikaido
doi: https://doi.org/10.1101/543447
Hirotaka Matsumoto
Laboratory for Bioinformatics Research RIKEN Center for Biosystems Dynamics Research;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Hirotaka Matsumoto
  • For correspondence: hirotaka.matsumoto@riken.jp
Tetsutaro Hayashi
Laboratory for Bioinformatics Research RIKEN Center for Biosystems Dynamics Research;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Haruka Ozaki
Center for Artificial Intelligence Research, University of Tsukuba;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Koki Tsuyuzaki
Laboratory for Bioinformatics Research RIKEN Center for Biosystems Dynamics Research;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Mana Umeda
Laboratory for Bioinformatics Research RIKEN Center for Biosystems Dynamics Research;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Tsuyoshi Iida
Department of Orthopaedic Surgery, Keio University School of Medicine;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Masaya Nakamura
Department of Orthopaedic Surgery, Keio University School of Medicine;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Hideyuki Okano
Department of Physiology, Keio University School of Medicine
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Itoshi Nikaido
Laboratory for Bioinformatics Research RIKEN Center for Biosystems Dynamics Research;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • Abstract
  • Info/History
  • Metrics
  • Supplementary material
  • Preview PDF
Loading

Abstract

Single-cell RNA sequencing has enabled researchers to quantify the transcriptomes of individual cells, infer cell types, and investigate differential expression among cell types, which will lead to a better understanding of the regulatory mechanisms of cell states. Transcript diversity caused by phenomena such as aberrant splicing events have been revealed, and differential expression of previously unannotated transcripts might be overlooked by annotation-based analyses. Accordingly, we have developed an approach to discover overlooked differentially expressed (DE) gene regions that complements annotation-based methods. We applied our algorithm to two datasets and discovered several intriguing DE transcripts, including a transcript related to the modulation of neural stem/progenitor cell differentiation.

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 4.0 International license.
Back to top
PreviousNext
Posted February 08, 2019.
Download PDF

Supplementary Material

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.
A NMF-based approach to discover overlooked differentially expressed gene regions from single-cell RNA-seq data
(Your Name) has forwarded a page to you from bioRxiv
(Your Name) thought you would like to see this page from the bioRxiv website.
Share
A NMF-based approach to discover overlooked differentially expressed gene regions from single-cell RNA-seq data
Hirotaka Matsumoto, Tetsutaro Hayashi, Haruka Ozaki, Koki Tsuyuzaki, Mana Umeda, Tsuyoshi Iida, Masaya Nakamura, Hideyuki Okano, Itoshi Nikaido
bioRxiv 543447; doi: https://doi.org/10.1101/543447
Digg logo Reddit logo Twitter logo CiteULike logo Facebook logo Google logo Mendeley logo
Citation Tools
A NMF-based approach to discover overlooked differentially expressed gene regions from single-cell RNA-seq data
Hirotaka Matsumoto, Tetsutaro Hayashi, Haruka Ozaki, Koki Tsuyuzaki, Mana Umeda, Tsuyoshi Iida, Masaya Nakamura, Hideyuki Okano, Itoshi Nikaido
bioRxiv 543447; doi: https://doi.org/10.1101/543447

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 (998)
  • Biochemistry (1489)
  • Bioengineering (943)
  • Bioinformatics (6823)
  • Biophysics (2419)
  • Cancer Biology (1784)
  • Cell Biology (2528)
  • Clinical Trials (106)
  • Developmental Biology (1693)
  • Ecology (2566)
  • Epidemiology (1493)
  • Evolutionary Biology (5018)
  • Genetics (3613)
  • Genomics (4625)
  • Immunology (1165)
  • Microbiology (4244)
  • Molecular Biology (1623)
  • Neuroscience (10781)
  • Paleontology (82)
  • Pathology (236)
  • Pharmacology and Toxicology (409)
  • Physiology (555)
  • Plant Biology (1456)
  • Scientific Communication and Education (412)
  • Synthetic Biology (542)
  • Systems Biology (1871)
  • Zoology (259)