Project description:Plasmodium-specific CD4+ T cells from mice infected with Plasmodium chabaudi chabaudi AS parasites were recovered at Days 0, 7, 10, 14, 17, 21, 28 to undergo processing and generate scRNA-seq dataset. From Day 10 onwards, mice were administered with either saline or artesunate (intermittent artesunate therapy - IAT). scRNA-seq dataset was analysed to investigate transcriptome dynamics of CD4+ T cells from effector to memory states.
Project description:Plasmodium-specific CD4+ T cells from mice infected with Plasmodium chabaudi chabaudi AS parasites were recovered at Days 0, 7, and 28 to undergo processing and generate scRNA-seq dataset. At Day 28, mice were administered with either saline or artesunate (intermittent artesunate therapy - IAT). scRNA-seq dataset was analysed to investigate transcriptome dynamics of CD4+ T cells from effector to memory states.
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: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: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])