Project description:Previous study (Segerstolpe Å et.al., Cell Metab . 2016) has revealed the single-cell landscape of human pancreatic islets from 10 human individuals. Here, we have performed Smart-seq2 scRNA-seq of additional 4 healthy and 6 T2D individuals.
Project description:In this study, we assess technical differences between commonly used single-cell RNA-Sequencing (scRNA-Seq) methods. We perform scRNA-seq on a homogenous population of mouse embryonic stem cells along with two kinds of control spike-in molecules to assess sensitivity and accuracy of these specific methods. In this dataset, we perform Smart-Seq2 method on Fluidigm C1 system and generate single-cell libraries using Nextera XT kit
Project description:In this study, we assess technical differences between commonly used single-cell RNA-Sequencing (scRNA-Seq) methods. We perform scRNA-seq on a homogenous population of mouse embryonic stem cells along with two kinds of control spike-in molecules to assess sensitivity and accuracy of these specific methods. In this dataset, we perform a replicate of Smart-Seq2 method on Fluidigm C1 system and generate single-cell libraries using Nextera XT kit
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])
Project description:In this study, we assess technical differences between commonly used single-cell RNA-Sequencing (scRNA-Seq) methods. We perform scRNA-seq on a homogenous population of mouse embryonic stem cells along with two kinds of control spike-in molecules to assess sensitivity and accuracy of these specific methods. In this dataset, we assess the RNA-degradation and decay rates by subjecting both spike-in molecules to range of repeated freezing and thawing (freeze-thaw) cycles. We manually add spike-in molecules across a 96-well plate (containing cells and reagents), perform Smart-Seq2 method manually and generate single-cell libraries using Nextera XT kit
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).