Delineating biological and technical variance in single cell expression data

Ángeles Arzalluz-Luque, Guillaume Devailly, Anna Mantsoki, Anagha Joshi

Research output: Contribution to journalArticlepeer-review


Single cell transcriptomics is becoming a common technique to unravel new biological phenomena whose functional significance can only be understood in the light of differences in gene expression between single cells. The technology is still in its early days and therefore suffers from many technical challenges. This review discusses the continuous effort to identify and systematically characterise various sources of technical variability in single cell expression data and the need to further develop experimental and computational tools and resources to help deal with it.

Original languageEnglish
Pages (from-to)161-166
JournalInternational Journal of Biochemistry and Cell Biology
Early online date15 Jul 2017
Publication statusPublished - Sep 2017


  • single cell
  • RNA-seq
  • Noise
  • variability


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