Please Cite:


Developing mouse kidney scRNA-seq and snATAC-seq studies (Miao, Z. et al., Nature Communications, 2021):

Miao, Z. et al. Single cell regulatory landscape of the mouse kidney highlights cellular differentiation programs and disease targets. Nature Communications (2021).

Raw data:
https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE157079


Human kidney snATAC-seq, cell fraction eQTL and cell type interaction eQTL studies (Sheng, X. et al., bioRxiv, 2020):

Sheng, X. et al. Mapping the genetic architecture of human traits to cell types in the kidney identifies mechanisms of disease and potential treatments. bioRxiv (2020).


Disease mouse kidney scRNA-seq study (Dhillon, P. et al., Cell Metabolism, 2020):

Dhillon, P. et al. The Nuclear Receptor ESRRA Protects from Kidney Disease by Coupling Metabolism and Differentiation. Cell Metabolism (2020).

Raw data:
https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE156686
https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE152765


Human whole blood mQTL study (Sheng, X. et al., Proceedings of the National Academy of Sciences, 2020):

Sheng, X. et al. Systematic integrated analysis of genetic and epigenetic variation in diabetic kidney disease. Proceedings of the National Academy of Sciences (2020).

Summary Statistics data for mQTL and MWAS:
https://zenodo.org/record/4148467#.X5ohRy1VZR0

The clinical records for CRIC samples
https://clinicaltrials.gov/ct2/show/NCT00304148?term=CRIC+study

Genotype data
https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000524.v1.p1


Bulk eQTL study (Qiu, C. et al., Nature Medicine, 2018):

Qiu, C. et al. Renal compartment–specific genetic variation analyses identify new pathways in chronic kidney disease. Nature medicine 24, 1721 (2018).

Raw data:
https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE115098


Healthy mouse kidney single cell RNA-seq study (Park, J. et al., Science, 2018):

Park, J. et al. Single-cell transcriptomics of the mouse kidney reveals potential cellular targets of kidney disease. Science (2018).

Raw data:
https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE107585