GEO DataSets

(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) The goal of this study is to discover fibroblast subpopulations relevant to recessive dystrophic epidermolysis bullosa

Organism:

Homo sapiens

Type:

Expression profiling by high throughput sequencing

Platform:

GPL15520

543 Samples

Download data: TXT

(Submitter supplied) A key limitation in single cell genomics is generating a high-quality single cell suspension that contains rare or difficult to dissociate cell types and is free of RNA degradation or transcriptional stress responses. Samples with unpredictable availability or that must be collected at several timepoints present additional challenges. Using adult mouse kidney, we compared single-cell RNA sequencing (scRNA-seq) data generated using DropSeq with snRNA-seq data generated from nuclei using sNuc-DropSeq, DroNc-seq and 10X Chromium. more...

Organism:

Mus musculus

Type:

Expression profiling by high throughput sequencing

Platform:

GPL17021

5 Samples

Download data: TXT

(Submitter supplied) Single-cell whole-transcriptome analysis is a powerful tool for quantifying gene expression heterogeneity in populations of cells. Many techniques have, thus, been recently developed to perform transcriptome sequencing (RNA-Seq) on individual cells. To probe subtle biological variation between samples with limiting amounts of RNA, more precise and sensitive methods are still required. We adapted a previously developed strategy for single-cell RNA-Seq that has shown promise for superior sensitivity and implemented the chemistry in a microfluidic platform for single-cell whole transcriptome analysis. more...

Organism:

Mus musculus

Type:

Expression profiling by high throughput sequencing

Platform:

GPL17021

102 Samples

Download data: TXT

(Submitter supplied) Abstract: The recently developed droplet-based single cell transcriptome sequencing (scRNA-seq) technology makes it feasible to perform a population-scale scRNA-seq study, in which the transcriptome is measured for tens of thousands of single cells from multiple individuals. Despite the advances of many clustering methods, there are few tailored methods for population-scale scRNA-seq studies. Here, we develop a BAyesian Mixture Model for Single Cell sequencing (BAMM-SC) method to cluster scRNA-seq data from multiple individuals simultaneously. more...

Organism:

Homo sapiens; Mus musculus

Type:

Expression profiling by high throughput sequencing

Platforms:

GPL18573 GPL19057

11 Samples

Download data: MTX, TSV

(Submitter supplied) The development of high-throughput single-cell RNA-sequencing (scRNA-Seq) methodologies has empowered the characterization of complex biological samples by dramatically increasing the number of constituent cells that can be examined concurrently. Nevertheless, these approaches typically recover substantially less information per-cell as compared to lower-throughput microtiter plate-based strategies. more...

Organism:

Homo sapiens; Mus musculus

Type:

Expression profiling by high throughput sequencing

Platforms:

GPL19415 GPL18573

438 Samples

Download data: CSV, TXT

(Submitter supplied) We employed an experimental design where PBMCs from a single donor was sequenced with or without mixing with PBMCs from other healthy unrelated donors in order to determine whether PBMCs engage in an allogeneic response under standard scRNA-seq sample preparation conditions (e.g., 30 minute co-incubation at 4C)

Organism:

Homo sapiens

Type:

Expression profiling by high throughput sequencing

Platforms:

GPL24676 GPL15520

10 Samples

Download data: CSV, MTX, TSV

(Submitter supplied) To investigate novel markers for snRNA seq and graft in-vivo snRNA seq.

Organism:

Homo sapiens

Type:

Expression profiling by high throughput sequencing

Platform:

GPL24676

10 Samples

Download data: CSV

(Submitter supplied) Computational single-cell RNA-seq (scRNA-seq) methods have been successfully applied to experiments representing a single condition, technology, or species to discover and define cellular phenotypes. However, identifying subpopulations of cells that are present across multiple datasets remains challenging. Here, we introduce an analytical strategy for integrating scRNA-seq datasets based on common sources of variation, enabling the identification of shared populations across datasets and downstream comparative analysis. more...

Organism:

Homo sapiens

Type:

Expression profiling by high throughput sequencing

Platform:

GPL16791

13 Samples

Download data: CSV

(Submitter supplied) Massively parallel single cell RNA-seq (scRNA-seq) for diverse applications, from cell atlases to functional screens, is increasingly limited by sequencing costs, and large-scale low-cost sequencing can open many additional applications, including patient diagnostics and drug screens. Here, we adapted and systematically benchmarked a newly developed, mostly-natural sequencing by synthesis method for scRNA-seq. more...

Organism:

Homo sapiens

Type:

Expression profiling by high throughput sequencing; Other

4 related Platforms

16 Samples

Download data: CSV, H5, TXT

(Submitter supplied) We comparison the performance of three different library for transcriptome analysis.

Organism:

Homo sapiens

Type:

Expression profiling by high throughput sequencing

Platform:

GPL21697

6 Samples

Download data: TSV

(Submitter supplied) Transcriptomic profiling of complex tissues by single-nucleus RNA-sequencing (snRNA-seq) affords some advantages over single-cell RNA-sequencing (scRNA-seq). snRNA-seq provides less biased cellular coverage, does not appear to suffer cell isolation-based transcriptional artifacts, and can be applied to archived frozen specimens. We used well-matched snRNA-seq and scRNA-seq datasets from mouse visual cortex to compare cell type detection. more...

Organism:

Mus musculus

Type:

Expression profiling by high throughput sequencing

Platform:

GPL17021

956 Samples

Download data: CSV, XLS

(Submitter supplied) Single-cell RNA sequencing significantly deepened our insights into complex tissues and latest techniques are capable to analyze ten-thousands of cells simultaneously. With bigSCale, we provide an analytical framework being scalable to analyze millions of cells, addressing challenges of future large data sets. Unlike other methods, bigSCale does not constrain data to fit an a priori-defined distribution and instead uses an accurate numerical model of noise. more...

Organism:

Homo sapiens

Type:

Expression profiling by high throughput sequencing

Platform:

GPL16791

1847 Samples

Download data: CSV, H5, TXT, XLSX

(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) 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) Single-cell RNA-seq measurements of the normal mouse bone marrow cells using inDrop protocol

Organism:

Mus musculus

Type:

Expression profiling by high throughput sequencing

Platform:

GPL19057

1 Sample

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

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:

Homo sapiens; Mus musculus

Type:

Expression profiling by high throughput sequencing

Platform:

GPL24625

8 Samples

Download data: TXT