NAFLD scRNA seq Database

Introduction about NAFLD scRNAseq Database



Introduction will be added



Please cite the NAFLD scRNAseq Database as:

Unveiling the pathogenesis of non-alcoholic fatty liver disease by decoding biomarkers through integrated single-cell and single-nucleus profiles Wenfeng Ma, Xin Zhong, Benqiang Cai, Mumin Shao, Xuewen Yu, Minling Lv, Shaomin Xu, Bolin Zhan, Qun Li, Mengqing Ma, Mikkel Breinholt Kjær, Jinrong Huang, Yonglun Luo, Henning Grønbæk, Lin Lin medRxiv 2023.10.05.23296635; doi: https://doi.org/10.1101/2023.10.05.23296635



Contact:

Wenfeng Ma, Ph.D., Associate Chief Physician, Shenzhen Traditional Chinese Medicine Hospital, China. Email: wenfeng@clin.au.dk



Lin Lin, Ph.D., Associate Professor

Group leader, Department of Biomedicine, Aarhus University

Email: lin.lin@biomed.au.dk

Address: Building 1116-152, Hoegh-Guldbergs Gade 10, 8000 Aarhus

Cell information vs gene expression on reduced dimensions

In this tab, users can visualise both cell information and gene expression side-by-side on low-dimensional representions.

Dimension Reduction

Cell information

Download PDF Download PNG

Cell numbers / statistics

Gene expression

Download PDF Download PNG

Cell information vs cell information on dimension reduction

In this tab, users can visualise two cell informations side-by-side on low-dimensional representions.

Dimension Reduction

Cell information 1

Download PDF Download PNG

Cell information 2

Download PDF Download PNG

Gene expression vs gene expression on dimension reduction

In this tab, users can visualise two gene expressions side-by-side on low-dimensional representions.

Dimension Reduction

Gene expression 1

Download PDF Download PNG

Gene expression 2

Download PDF Download PNG

Coexpression of two genes on reduced dimensions

In this tab, users can visualise the coexpression of two genes on low-dimensional representions.

Dimension Reduction

Gene Expression

Download PDF Download PNG

Cell information / gene expression violin plot / box plot

In this tab, users can visualise the gene expression or continuous cell information (e.g. Number of UMIs / module score) across groups of cells (e.g. libary / clusters).



Download PDF Download PNG

Proportion / cell numbers across different cell information

In this tab, users can visualise the composition of single cells based on one discrete cell information across another discrete cell information. Usage examples include the library or cellcycle composition across clusters.



Download PDF Download PNG

Gene expression bubbleplot / heatmap

In this tab, users can visualise the gene expression patterns of multiple genes grouped by categorical cell information (e.g. library / cluster).
The normalised expression are averaged, log-transformed and then plotted.




Download PDF Download PNG

This webpage was made using ShinyCell