Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Multiplexing droplet-based single cell RNA-sequencing using genetic barcodes

ABSTRACT: Here, we introduce an in-silico algorithm demuxlet that harnesses naturally occurring genetic variation in a pool of cells from unrelated individuals to discover the sample identity of each cell and identify droplets containing cells from two different individuals (doublets). These two capabilities enable a simple multiplexing design that increases single cell library construction throughput by experimental design where cells from genetically diverse samples are multiplexed and captured at 2-10x over standard workflows. We further demonstrate the utility of sample multiplexing by characterizing the interindividual variability in cell type-specific responses of ~15k PBMCs to interferon-beta, a potent cytokine. Our computational tool enables sample multiplexing of droplet-based single cell RNA-seq for large-scale studies of population variation and could be extended to other single cell datasets that incorporate natural or synthetic DNA barcodes.

ORGANISM(S): Homo sapiens

PROVIDER: GSE96583 | GEO | 2017/06/13

SECONDARY ACCESSION(S): PRJNA381100

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

CellTag Indexing: genetic barcode-based sample multiplexing for single-cell genomics

Project description:High-throughput single-cell assays increasingly require special consideration in experimental design, sample multiplexing, batch effect removal, and data interpretation. Here, we describe a lentiviral barcode-based multiplexing approach, CellTag Indexing, which uses predefined genetic barcodes that are also heritable, enabling cell populations to be tagged, pooled, and tracked over time in the same experimental replicate. We demonstrate the utility of CellTag Indexing by sequencing transcriptomes using a variety of cell types, including long-term tracking of cell engraftment and differentiation in vivo. Together, this presents CellTag Indexing as a broadly applicable genetic multiplexing tool that is complementary with existing single-cell technologies.

2019-04-20 | GSE130065 | GEO

Comparative analysis of single-cell RNA sequencing methods with and without sample multiplexing

Project description:Single-cell RNA sequencing (scRNA-seq) has emerged as a powerful technique for investigating biological heterogeneity at the single-cell level in human systems and model organisms. Recent advances in scRNA-seq have enabled the pooling of cells from multiple samples into single libraries, thereby increasing sample throughput while reducing technical batch effects, library preparation time, and the overall cost. However, a comparative analysis of scRNA-seq methods with and without sample multiplexing is lacking. In this study, we benchmarked methods from two representative platforms: Parse Biosciences (Parse; with sample multiplexing) and 10X Genomics (10x; without sample multiplexing). By using peripheral blood mononuclear cells (PBMCs) obtained from two healthy individuals, we demonstrate that demultiplexed scRNA-seq data obtained from Parse showed similar cell type frequencies compared to 10X data where samples are not multiplexed. Despite a relatively lower library and cell capture efficiencies, Parse can detect rare cell types (e.g., plasmablasts and dendritic cells) which is likely due to its relatively higher sensitivity in gene detection. Moreover, comparative analysis of transcript quantification between the two platforms revealed platform-specific distributions of gene length and GC content. These results offer guidance for researchers in designing high-throughput scRNA-seq studies.

2024-03-24 | GSE246624 | GEO

Sample multiplexing for retinal single-cell RNA-sequencing

Project description:Sample multiplexing for retinal single-cell RNA-sequencing

| PRJNA1071096 | ENA

Sample multiplexing for retinal single-cell RNA-sequencing

Project description:Single cell RNA sequencing (ScRNA-seq) often requires sample pooling, but sample variance is rarely addressed. We perform scRNA-seq on retinal ganglion cells with retina-multiplexing to assess the whether this enables comparisons between retinas of an experiment.

2024-06-12 | GSE254587 | GEO

CellTag Indexing: genetic barcode-based sample multiplexing for single-cell genomics

Project description:CellTag Indexing: genetic barcode-based sample multiplexing for single-cell genomics

| PRJNA533780 | ENA

Label-free single-cell RNA Multiplexing leveraging genetic variability [scRNA-seq]

Project description:Single cell RNA sequencing has enabled unprecedented insights into the molecular cues and cellular heterogeneity underlying human disease. However, the high costs and complexity of single cell methods remain a major obstacle for generating large scale human cohorts. Here we compare current state-of-the-art single cell multiplexing technologies, and provide a new widely applicable demultiplexing method, SNP-Fishing, that enables simple, robust high-throughput multiplexing leveraging genetic variability of patients.

2024-09-06 | GSE247707 | GEO

Label-free single-cell RNA Multiplexing leveraging genetic variability [bulk RNA-seq]

2024-09-06 | GSE247706 | GEO

An optimized approach for multiplexing single-cell ATAC-seq using oligonucleotide conjugated antibodies

Project description:An optimized approach for multiplexing single-cell ATAC-seq using oligonucleotide conjugated antibodies

2023-04-28 | GSE227522 | GEO

Probability of stealth multiplets in sample-multiplexing for droplet-based single-cell analysis

Project description:These datasets are test datasets of sample-multiplexed scRNA-seq, consisting of cDNA (transcriptome) and sample barcode read files: Three-sample multiplexing experiment (JS009) is a MULTI-seq dataset containing mesenchyme embryonic hind limb bud cells, embryonic stem (ES) cells, and NIH3T3 cells. Each cell sample was labelled with a distinct MULTI-seq barcode. The barcode sequences were, CATAGAGC, TCCTCGAA, and GTGTACCT for the limb bud mesenchyme cells, the ES cells, and the NIH3T3 cells, respectively. Two-sample multiplexing experiment (JS010) is a CellPlex detaset, containing ES cells and NIH3T3 cells. Each cell sample was labelled with the 3'CellPlex Kit (10X Genomics). NIH3T3 cells and ES cells were labelled with CMO301 and CMO302, respectively.

2024-01-09 | E-MTAB-13181 | biostudies-arrayexpress

Comparative analysis of single-cell RNA sequencing methods with and without sample multiplexing

Project description:Comparative analysis of single-cell RNA sequencing methods with and without sample multiplexing

| PRJNA1033995 | ENA