visnormsc: A Graphical User Interface to Normalize Single-cell RNA Sequencing Data

  • Lijun Tang
  • Nan ZhouEmail author
Short Communication


Single-cell RNA sequencing (RNA-seq) allows the analysis of gene expression with high resolution. The intrinsic defects of this promising technology imports technical noise into the single-cell RNA-seq data, increasing the difficulty of accurate downstream inference. Normalization is a crucial step in single-cell RNA-seq data pre-processing. SCnorm is an accurate and efficient method that can be used for this purpose. An R implementation of this method is currently available. On one hand, the R package possesses many excellent features from R. On the other hand, R programming ability is required, which prevents the biologists who lack the skills from learning to use it quickly. To make this method more user-friendly, we developed a graphical user interface, visnormsc, for normalization of single-cell RNA-seq data. It is implemented in Python and is freely available at Although visnormsc is based on the existing method, it contributes to this field by offering a user-friendly alternative. The out-of-the-box and cross-platform features make visnormsc easy to learn and to use. It is expected to serve biologists by simplifying single-cell RNA-seq normalization.


RNA Single-cell Normalization Quantile regression 



This work is financially supported by China Scholarship Council (201506240135), and International Macquarie University Research Excellence Scholarships (2015233).


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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2017

Authors and Affiliations

  1. 1.College of Biological Resources and Food EngineeringQujing Normal UniversityQujingChina
  2. 2.Faculty of Medicine and Health SciencesMacquarie UniversitySydneyAustralia

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