Single nucleus transcriptomics data integration recapitulates the major cell types in human liver
Journal article, 2021

Hepatology Research published by John Wiley & Sons Australia, Ltd on behalf of Japan Society of Hepatology Aim: The aim of this study was to explore the benefits of data integration from different platforms for single nucleus transcriptomics profiling to characterize cell populations in human liver. Methods: We generated single-nucleus RNA sequencing data from Chromium 10X Genomics and Drop-seq for a human liver sample. We utilized state of the art bioinformatics tools to undertake a rigorous quality control and to integrate the data into a common space summarizing the gene expression variation from the respective platforms, while accounting for known and unknown confounding factors. Results: Analysis of single nuclei transcriptomes from both 10X and Drop-seq allowed identification of the major liver cell types, while the integrated set obtained enough statistical power to separate a small population of inactive hepatic stellate cells that was not characterized in either of the platforms. Conclusions: Integration of droplet-based single nucleus transcriptomics data enabled identification of a small cluster of inactive hepatic stellate cells that highlights the potential of our approach. We suggest single-nucleus RNA sequencing integrative approaches could be utilized to design larger and cost-effective studies.


data integration





Klev Diamanti

Uppsala University

Juan Salvador Inda Diaz

Chalmers, Mathematical Sciences, Applied Mathematics and Statistics

Amanda Raine

Uppsala University

Gang Pan

Uppsala University

Claes Wadelius

Uppsala University

Marco Cavalli

Uppsala University

Hepatology Research

1386-6346 (ISSN)

Vol. 51 2 233-238

Subject Categories

Biomedical Laboratory Science/Technology

Bioinformatics (Computational Biology)

Bioinformatics and Systems Biology





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