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

Correcting batch effects in single-cell RNA sequencing data by matching mutual nearest neighbours

Laleh Haghverdi, View ORCID ProfileAaron T. L. Lun, View ORCID ProfileMichael D. Morgan, View ORCID ProfileJohn C. Marioni
doi: https://doi.org/10.1101/165118
Laleh Haghverdi
1European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom
2Institute of Computational Biology, Helmholtz Zentrum München, 85764 Neuherberg, Germany
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Aaron T. L. Lun
3Cancer Research UK Cambridge Institute, University of Cambridge, Robinson Way, Li Ka Shing Centre, Cambridge CB2 0RE, United Kingdom
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Aaron T. L. Lun
Michael D. Morgan
4Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, United Kingdom
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Michael D. Morgan
John C. Marioni
1European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom
3Cancer Research UK Cambridge Institute, University of Cambridge, Robinson Way, Li Ka Shing Centre, Cambridge CB2 0RE, United Kingdom
4Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, United Kingdom
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for John C. Marioni
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Supplementary material
  • Preview PDF
Loading

Abstract

The presence of batch effects is a well-known problem in experimental data analysis, and single- cell RNA sequencing (scRNA-seq) is no exception. Large-scale scRNA-seq projects that generate data from different laboratories and at different times are rife with batch effects that can fatally compromise integration and interpretation of the data. In such cases, computational batch correction is critical for eliminating uninteresting technical factors and obtaining valid biological conclusions. However, existing methods assume that the composition of cell populations are either known or the same across batches. Here, we present a new strategy for batch correction based on the detection of mutual nearest neighbours in the high-dimensional expression space. Our approach does not rely on pre-defined or equal population compositions across batches, only requiring that a subset of the population be shared between batches. We demonstrate the superiority of our approach over existing methods on a range of simulated and real scRNA-seq data sets. We also show how our method can be applied to integrate scRNA-seq data from two separate studies of early embryonic development.

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 July 18, 2017.
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.
Correcting batch effects in single-cell RNA sequencing data by matching mutual nearest neighbours
(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
Correcting batch effects in single-cell RNA sequencing data by matching mutual nearest neighbours
Laleh Haghverdi, Aaron T. L. Lun, Michael D. Morgan, John C. Marioni
bioRxiv 165118; doi: https://doi.org/10.1101/165118
Digg logo Reddit logo Twitter logo Facebook logo Google logo LinkedIn logo Mendeley logo
Citation Tools
Correcting batch effects in single-cell RNA sequencing data by matching mutual nearest neighbours
Laleh Haghverdi, Aaron T. L. Lun, Michael D. Morgan, John C. Marioni
bioRxiv 165118; doi: https://doi.org/10.1101/165118

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 (3686)
  • Biochemistry (7767)
  • Bioengineering (5666)
  • Bioinformatics (21237)
  • Biophysics (10553)
  • Cancer Biology (8159)
  • Cell Biology (11905)
  • Clinical Trials (138)
  • Developmental Biology (6737)
  • Ecology (10388)
  • Epidemiology (2065)
  • Evolutionary Biology (13838)
  • Genetics (9694)
  • Genomics (13054)
  • Immunology (8121)
  • Microbiology (19936)
  • Molecular Biology (7825)
  • Neuroscience (42959)
  • Paleontology (318)
  • Pathology (1276)
  • Pharmacology and Toxicology (2256)
  • Physiology (3350)
  • Plant Biology (7207)
  • Scientific Communication and Education (1309)
  • Synthetic Biology (1998)
  • Systems Biology (5528)
  • Zoology (1126)