GEO DataSets

(Submitter supplied) We systematically benchmarked seven high-throughput single-cell RNA-seq methods. We prepared 21 libraries under identical conditions of a defined mixture of two human and two murine lymphocyte cell lines, simulating heterogeneity across immune-cell types and cell sizes. We evaluate methods by their cell recovery rate, library efficiency, sensitivity, and ability to recover expression signatures for each cell type. more...

Organism:

Mus musculus; Homo sapiens

Type:

Expression profiling by high throughput sequencing

Platforms:

GPL25526 GPL24625 GPL25431

8 Samples

Download data: MTX, TSV

(Submitter supplied) We systematically benchmarked seven high-throughput single-cell RNA-seq methods. We prepared 21 libraries under identical conditions of a defined mixture of two human and two murine lymphocyte cell lines, simulating heterogeneity across immune-cell types and cell sizes. We evaluate methods by their cell recovery rate, library efficiency, sensitivity, and ability to recover expression signatures for each cell type. more...

Organism:

Homo sapiens

Type:

Expression profiling by high throughput sequencing

Platform:

GPL24676

2 Samples

Download data: MTX, TSV

(Submitter supplied) This SuperSeries is composed of the SubSeries listed below.

Organism:

Homo sapiens; Mus musculus

Type:

Expression profiling by high throughput sequencing

6 related Platforms

27 Samples

Download data: CSV, MTX, TSV, TXT

(Submitter supplied) We systematically benchmarked seven high-throughput single-cell RNA-seq methods. We prepared 21 libraries under identical conditions of a defined mixture of two human and two murine lymphocyte cell lines, simulating heterogeneity across immune-cell types and cell sizes. We evaluate methods by their cell recovery rate, library efficiency, sensitivity, and ability to recover expression signatures for each cell type. more...

Organism:

Homo sapiens; Mus musculus

Type:

Expression profiling by high throughput sequencing

Platform:

GPL24625

3 Samples

Download data: CSV, TXT

(Submitter supplied) We systematically benchmarked seven high-throughput single-cell RNA-seq methods. We prepared 21 libraries under identical conditions of a defined mixture of two human and two murine lymphocyte cell lines, simulating heterogeneity across immune-cell types and cell sizes. We evaluate methods by their cell recovery rate, library efficiency, sensitivity, and ability to recover expression signatures for each cell type. more...

Organism:

Mus musculus; Homo sapiens

Type:

Expression profiling by high throughput sequencing

Platform:

GPL24625

8 Samples

Download data: TXT

(Submitter supplied) We systematically benchmarked seven high-throughput single-cell RNA-seq methods. We prepared 21 libraries under identical conditions of a defined mixture of two human and two murine lymphocyte cell lines, simulating heterogeneity across immune-cell types and cell sizes. We evaluate methods by their cell recovery rate, library efficiency, sensitivity, and ability to recover expression signatures for each cell type. more...

Organism:

Homo sapiens; Mus musculus

Type:

Expression profiling by high throughput sequencing

Platforms:

GPL21103 GPL20301

4 Samples

Download data: CSV

(Submitter supplied) We systematically benchmarked seven high-throughput single-cell RNA-seq methods. We prepared 21 libraries under identical conditions of a defined mixture of two human and two murine lymphocyte cell lines, simulating heterogeneity across immune-cell types and cell sizes. We evaluate methods by their cell recovery rate, library efficiency, sensitivity, and ability to recover expression signatures for each cell type. more...

Organism:

Homo sapiens; Mus musculus

Type:

Expression profiling by high throughput sequencing

Platform:

GPL24625

2 Samples

Download data: TXT

(Submitter supplied) Single-cell RNA sequencing (scRNA-seq) methods generate sparse gene expression profiles for thousands of single cells in a single experiment. The information in these profiles is sufficient to classify cell types by distinct expression patterns but the high complexity of scRNA-seq libraries prevents full characterization of transcriptomes from individual cells. To generate more focused gene expression information from scRNA-seq libraries, we developed a strategy to physically recover the DNA molecules comprising transcriptome subsets, enabling deeper interrogation of the isolated molecules by another round of DNA sequencing. more...

Organism:

Homo sapiens; Mus musculus

Type:

Expression profiling by high throughput sequencing

5 related Platforms

13 Samples

Download data: JSON, TSV, TXT

(Submitter supplied) Here we compare the performance of these three approaches (inDrop, Drop-seq and 10x) using the same kind of sample with a unified data processing pipeline. We generated 2-3 replicates for each method using lymphoblastoid cell line GM12891. The average sequencing depth was around 50-60k reads per cell barcode. We also developed a versatile and rapid data processing workflow and applied it for all datasets. more...

Organism:

Homo sapiens

Type:

Expression profiling by high throughput sequencing

Platform:

GPL20301

7 Samples

Download data: TXT

(Submitter supplied) Purpose:To systematically assess the differences between high-throughput single-cell and single-nuclei RNA-seq approaches, we compared Drop-seq and DroNc-seq, two microfluidic-based 3’ RNA capture technologies that profile total cellular and nuclear RNA, respectively, during a time course experiment of human induced pluripotent stem cells (iPSCs) differentiating into cardiomyocytes Conclusions: Clustering of time-series transcriptomes from Drop-seq and DroNc-seq revealed six distinct cell types, five of which were found in both techniques. more...

Organism:

Homo sapiens

Type:

Expression profiling by high throughput sequencing

Platform:

GPL18573

25 Samples

Download data: TSV

(Submitter supplied) We report here a new single-cell RNA-seq assay, Multiple Annealing and dC-Tailing based Quantitative single-cell RNA-seq (MATQ-seq), which provides the accuracy and sensitivity that enable the detection of transcriptional variations existing in single cells of the same type. We performed a systematic characterization of the technical noise using pool-and-split averaged single-cell samples and showed that the biological variations in single cells were observed with statistical significance.

Organism:

Homo sapiens

Type:

Expression profiling by high throughput sequencing

Platform:

GPL18573

91 Samples

Download data: DAT, TXT

(Submitter supplied) Gene expression profiling via RNA-sequencing has become standard for measuring and analyzing the gene activity in bulk and at single cell level. Increasing sample sizes and cell counts provides substantial information about transcriptional architecture of samples. In addition to quantification of expression at cellular level, RNA-seq can be used for detecting of variants, including single nucleotide variants and small insertions/deletions and also large variants such as copy number variants. more...

Organism:

Homo sapiens

Type:

Expression profiling by high throughput sequencing

Platform:

GPL18573

2 Samples

Download data: MTX, TSV

(Submitter supplied) Background: Rare cell subtypes can profoundly impact the course of human health and disease, yet their presence within a sample is often missed with bulk molecular analysis. Single-cell analysis tools such as FACS, FISH-FC and single-cell barcode-based sequencing can investigate cellular heterogeneity; however, they have significant limitations that impede their ability to identify and transcriptionally characterize many rare cell subpopulations. more...

Organism:

Homo sapiens

Type:

Expression profiling by high throughput sequencing

Platform:

GPL16791

8 Samples

Download data: TXT

(Submitter supplied) We used microfluidic single cell RNA-seq on mixed e16.5 mouse lung cells in order to determine the potential cell types present based on differential transcriptional profiles of the entire population using minimal cell selection bias.

Organism:

Mus musculus

Type:

Expression profiling by high throughput sequencing

Platform:

GPL13112

148 Samples

Download data: TXT

(Submitter supplied) Purpose: Next-generation sequencing (NGS) has revolutionized systems-based analysis of cellular pathways. The goals of this study are to compare NGS-derived retinal transcriptome profiling (RNA-seq) to microarray and quantitative reverse transcription polymerase chain reaction (qRT–PCR) methods and to evaluate protocols for optimal high-throughput data analysis. Methods: Retinal mRNA profiles of 21-day-old wild-type (WT) and neural retina leucine zipper knockout (Nrl−/−) mice were generated by deep sequencing, in triplicate, using Illumina GAIIx. more...

Organism:

Mus musculus

Type:

Expression profiling by high throughput sequencing

Platform:

GPL11002

6 Samples

Download data: BAM, TXT, XLS

(Submitter supplied) RNA profiling technologies at single-cell resolutions, including single-cell and single-nuclei RNA sequencing (scRNA-Seq and snRNA-Seq, scnRNA-Seq for short), can help characterize the composition of tissues and reveal cells that influence key healthy and disease functions. However, the use of these technologies is challenging because of their relatively high costs and exacting sample collection requirements. more...

Organism:

Homo sapiens

Type:

Expression profiling by high throughput sequencing

Platform:

GPL24676

4 Samples

Download data: CSV, JSON, RDS, XLSX

(Submitter supplied) This SuperSeries is composed of the SubSeries listed below.

Organism:

Homo sapiens

Type:

Expression profiling by high throughput sequencing

Platform:

GPL24676

58 Samples

Download data: MTX, TSV

(Submitter supplied) RNA profiling technologies at single-cell resolutions, including single-cell and single-nuclei RNA sequencing (scRNA-Seq and snRNA-Seq, scnRNA-Seq for short), can help characterize the composition of tissues and reveal cells that influence key healthy and disease functions. However, the use of these technologies is challenging because of their relatively high costs and exacting sample collection requirements. more...

Organism:

Homo sapiens

Type:

Expression profiling by high throughput sequencing

Platform:

GPL24676

36 Samples

Download data: CSV

(Submitter supplied) Single cell expression data used for training the deconvolution algorithm

Organism:

Homo sapiens

Type:

Expression profiling by high throughput sequencing

Platform:

GPL18573

16 Samples

Download data: TSV

(Submitter supplied) We report the development of a simplified Cap Analysis of Gene Expression (CAGE) protocol adapted for single molecule sequencers which avoids second strand synthesis, ligation, digestion and PCR. HeliScopeCAGE directly sequences the 3’ end of cap trapped first strand cDNAs. As with previous versions of CAGE, we better define transcription start sites (TSS) than known models, identify novel regions of transcription and alternative promoters, and find two major classes of TSS signal, sharp peaks and broad regions. more...

Organism:

Homo sapiens

Type:

Expression profiling by array; Expression profiling by high throughput sequencing

Platforms:

GPL6884 GPL14761

19 Samples

Download data: TXT