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 STRT-seq method on Fluidigm C1 system and generate single-cell libraries using Nextera XT kit. Please note the sample-data relationship format (SDRF) file for this submission contains only a high-level representation of all sample, library and run information, and not per cell. For meta-data at the level of individual cells, please refer to the supplementary file called single_cells_list.txt, which is included as part of this ArrayExpress submission.
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 SMARTer 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 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