Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Ena-DATASET-KI-10-01-2021-10:28:44:984-430 - samples

ABSTRACT: Smart-seq2 single cell RNA sequencing reads from kidney glomerular single cells of healthy human individuals. The dataset contains single-end fastq files of 766 single cells.

PROVIDER: EGAD00001006861 | EGA |

REPOSITORIES: EGA

ACCESS DATA

Json Xml

Similar Datasets

Single-cell RNA sequencing reveals the mesangial identity and species diversity of glomerular cell transcriptomes

Project description:Molecular characterization of the individual cell types in human kidney as well as model organisms are critical in defining organ function and understanding translational aspects of biomedical research. Previous studies have uncovered gene expression profiles of several kidney glomerular cell types, however, important cells, including mesangial (MCs) and glomerular parietal epithelial cells (PECs), were missing or incompletely described, and a systematic comparison between mouse and human kidney is lacking. To this end, we used Smart-seq2 to profile 4332 individual glomerulus-associated cells isolated from human living donor renal biopsies and mouse kidney. The analysis revealed genetic programs for all four glomerular cell types (podocytes, glomerular endothelial cells, MCs and PECs) as well as rare glomerulus-associated macula densa cells (MDCs). Importantly, we detected heterogeneity in glomerulus-associated Pdgfrb-expressing cells, including bona fide intraglomerular MCs with the functionally active phagocytic molecular machinery, as well as a unique mural cell type located in the central stalk region of the glomerulus tuft. Furthermore, we observed remarkable species differences in the individual gene expression profiles of defined glomerular cell types that highlight translational challenges in the field and provide a guide to design translational studies.

2020-11-21 | GSE160048 | GEO

Smart-seq2 analysis of P17 FACS sorted retinal cells from the Kcng4-cre;stop-YFP X Thy1-stop-YFP Line#1 mice

Project description:Four Kcng4-cre;stop-YFP mouse retinas from two mice were dissected, dissociated and FACS sorted, and single cell RNA-seq libraries were generated for 384 single cells using Smart-seq2. Aligned bam files are generated for 383 samples as one failed to align. Four mouse retinas (labeled 1la, 1Ra, and 2la, 2Ra respective from the two mice) were used, and 96 single cells from each were processed using Smart-seq2. Total 384 cells Smart-seq2 analysis of P17 FACS sorted retinal cells from the Kcng4-cre;stop-YFP mice (Kcng4tm1.1(cre)Jrs mice [Duan et al., Cell 158, 793-807, 2015] crossed to the cre-dependent reporter Thy1-stop-YFP Line#1 [Buffelli et al., Nature 424, 430-434, 2003])

2016-08-25 | E-GEOD-81903 | biostudies-arrayexpress

In situ transcriptome characteristics are lost following culture adaptation of adult cardiac stem cells (Smart-Seq2 scRNA-seq)

Project description:Single-cell RNA-seq (Smart-Seq2) to profile of cardiac progenitor cells

2018-09-12 | GSE114279 | GEO

Improved Smart-Seq for sensitive full-length transcriptome profiling in single cells

Project description:Improved Smart-Seq for sensitive full-length transcriptome profiling in single cells. Cells of four different origins were profiled using commercial SMARTer and compared to five variants of an improved protocol (Smart-Seq2).

2013-09-01 | E-GEOD-49321 | biostudies-arrayexpress

Single-cell RNAseq (SMART-seq2) of wild-type (TLAB) and MZoep (tz57) zebrafish embryos at 50% epiboly stage

Project description:SMART-seq2 was performed on single cells isolated from visually staged zebrafish embryos.

2018-04-27 | GSE106466 | GEO

Comparative analysis of single-cell RNA sequencing methods

Project description:Single-cell RNA sequencing (scRNA-seq) offers new possibilities to address biological and medical questions. However, systematic comparisons of the performance of diverse scRNA-seq protocols are lacking. We generated data from 583 mouse embryonic stem cells to evaluate six prominent scRNA-seq methods: CEL-seq2, Drop-seq, MARS-seq, SCRB-seq, Smart-seq and Smart-seq2. While Smart-seq2 detected the most genes per cell and across cells, CEL-seq2, Drop-seq, MARS-seq and SCRB-seq quantified mRNA levels with less amplification noise due to the use of unique molecular identifiers (UMIs). Power simulations at different sequencing depths showed that Drop-seq is more cost-efficient for transcriptome quantification of large numbers of cells, while MARS-seq, SCRB-seq and Smart-seq2 are more efficient when analyzing fewer cells. Our quantitative comparison offers the basis for an informed choice among six prominent scRNA-seq methods and provides a framework for benchmarking further improvements of scRNA-seq protocols.

2016-09-09 | GSE75790 | GEO

Single-cell RNA sequencing reveals the mesangial identity and species diversity of glomerular cell transcriptomes

| EGAS00001004943 | EGA

Smart-seq2 analysis of P17 FACS sorted retinal cells from the Tg(Chx10-EGFP/cre,-ALPP)2Clc or Vsx2-GFP transgenic line

Project description:Three Vsx2-GFP mouse retinas were dissected, dissociated and FACS sorted, and single cell RNA-seq libraries were generated for 288 single cells and 3 bulk libraries using Smart-seq2 (~10,000 cells each)

2016-08-25 | GSE80232 | GEO

Single-cell RNAseq of mouse ear dermal endothelial cells

Project description:Single blood vascular endothelial cells were isolated from the ear dermis of adult C57Bl/6 mice and subject to whole transcriptome RNA sequencing by SMART-seq2.

2022-08-16 | GSE202290 | GEO

Single-cell analysis of Toxoplasma gondii infected mouse dendritic cells

Project description:Mouse dendritic cells were infected in vitro with two strains of T.gondii (PTG, LDM). Controls stimulated with T.gondii lysate as well as LPS were included. Single-cell RNA-seq using Smart-seq2 was performed.

2020-12-01 | E-MTAB-9105 | biostudies-arrayexpress

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data