Single cell RNA-sequencing of Spike-ins and mESC using Smart-Seq2 on 96-well plates
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ABSTRACT: 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: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 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 SMARTer method on Fluidigm C1 system and generate single-cell libraries using Nextera XT kit
Project description:In this study, we perform comparative analysis of Illumina HiSeq and BGISEQ-500 sequencing platforms for single-cell transcriptomics data. We performed scRNA-seq on a homogenous population of mouse embryonic stem cells along with two kinds of control spike-in molecules and sequenced across both sequencing platforms. The matched Illumina platform datasets can be found with accession numbers (E-MTAB-5483, E-MTAB-5484, E-MTAB-5485). The additional data comparison performed in the study can be found (BioProject# PRJNA430491, SRA# SRP132313 and CNBG# CNP0000075).
Project description:In this study, we develop computational tools for assignment of cell-cycle stages from single cell and bulk transcriptome data. We perform bulk RNA-Sequencing for mouse embryonic stem cells with known cell cycle stage.
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:BCL11A is upregulated in lung squamous cell carcinoma (LUSC) but not in lung adenocarcinoma (LUAD). BCL11A interacts with SOX2 at protein level. ChIP-Seq experiment was performed for BCL11A and SOX2 in LUSC LK-2 control or BCL11A-KD cell line in order to identify their role in LUSC pathology.
Project description:The purpose of this experiment was to compared the transcriptome of hepatocyte-like cells (HLCs) generated in vitro and adult primary human hepatocytes (PHHs). HLCs were differentiated from either hESCs or hIPSCs using previously established protocols (Hannah et al 2013; Segeritz et al 2018). Undifferentiated hIPSCs were used as control to confirm differentiation status. PHHs were commercially sourced as well as freshly isolated from donors.
Project description:Total RNA was extracted from wild type and mutant zebrafish embryos. Double stranded cDNA representing the 3' ends of transcripts was made by a variety of methods, including polyT priming and 3' pull down on magentic beads. Some samples included indexing test experiments where a sequence barcode was placed within one of the sequence reads. More information describing the mutant phenotype can be found at the Wellcome Trust Sanger Institute Zebrafish Mutation Project website http://www.sanger.ac.uk/cgi-bin/Projects/D_rerio/zmp/search.pl?q=zmp_phD This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/
Project description:In this study, we aimed to study the gene expression patterns at single cell level across the different cell cycle stages in mESC. We performed single cell RNA-Seq experiment on mESC that were stained with Hoechst 33342 and Flow cytometry sorted for G1, S and G2M stages of cell cycle. Single cell RNA-Seq was performed using Fluidigm C1 system and libraries were generated using Nextera XT (Illumina) kit.