ScRNA-seq and bulk RNA-seq of NGP cells
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA605359 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR11040458_1.fastq.gz | Fastqsanger.gz | |||
| SRR11040458_2.fastq.gz | Fastqsanger.gz | |||
| SRR11040459_1.fastq.gz | Fastqsanger.gz | |||
| SRR11040459_2.fastq.gz | Fastqsanger.gz | |||
| SRR11040460_1.fastq.gz | Fastqsanger.gz |
Items per page: 5 1 - 5 of 32 |
Similar Datasets
Project description:Technological advances in transcriptome sequencing of single cells provided an unprecedented view on tissue composition and cellular heterogeneity. While several studies have compared different single cell RNA-seq methods with respect to data quality and their ability to distinguish cellular subpopulations, none of these comparative studies investigated the heterogeneity of the cellular transcriptional response upon a chemical perturbation. In this study, we evaluated the transcriptional response of NGP neuroblastoma cells upon nutlin-3 treatment using the C1, ddSeq and Chromium single cell systems. These systems and library preparation methods are representative for the wide variety of platforms, ranging from microfluids chips to droplet-based systems and from full transcript sequencing to 3’ end sequencing. In parallel, we used bulk RNA-seq for molecular characterization of the transcriptional response. Two complementary metrics to evaluate performance were applied: the first is the number and identification of differentially expressed genes as robustly assessed by two statistical models, and the second is enrichment analysis of biological signals, which is independent of sample size or number of cells evaluated. Where relevant, we downsampled sequencing library size, selected cell subpopulations based on specific RNA abundance features, or created pseudobulk samples to make the data more comparable. While the C1 detects the highest number of genes per cell and better resembles bulk RNA-seq, the Chromium identifies most differentially expressed genes, albeit still substantially fewer than bulk RNA-seq. Gene set enrichment analyses reveals that detection of the most abundant genes in single cell RNA-seq experiments is sufficient for molecular phenotyping. Finally, single cell RNA-seq reveals a heterogeneous response of NGP cells upon nutlin-3 treatment, pinpointing putative late-responders or resistant cells, hidden in bulk RNA-seq experiments.
2021-12-31 | GSE144930 | GEO
Project description:Technological advances in transcriptome sequencing of single cells provided an unprecedented view on tissue composition and cellular heterogeneity. While several studies have compared different single cell RNA-seq methods with respect to data quality and their ability to distinguish cellular subpopulations, none of these comparative studies investigated the heterogeneity of the cellular transcriptional response upon a chemical perturbation. In this study, we evaluated the transcriptional response of NGP neuroblastoma cells upon nutlin-3 treatment using the C1, ddSeq and Chromium single cell systems. These systems and library preparation methods are representative for the wide variety of platforms, ranging from microfluids chips to droplet-based systems and from full transcript sequencing to 3’ end sequencing. In parallel, we used bulk RNA-seq for molecular characterization of the transcriptional response. Two complementary metrics to evaluate performance were applied: the first is the number and identification of differentially expressed genes as robustly assessed by two statistical models, and the second is enrichment analysis of biological signals, which is independent of sample size or number of cells evaluated. Where relevant, we downsampled sequencing library size, selected cell subpopulations based on specific RNA abundance features, or created pseudobulk samples to make the data more comparable. While the C1 detects the highest number of genes per cell and better resembles bulk RNA-seq, the Chromium identifies most differentially expressed genes, albeit still substantially fewer than bulk RNA-seq. Gene set enrichment analyses reveals that detection of the most abundant genes in single cell RNA-seq experiments is sufficient for molecular phenotyping. Finally, single cell RNA-seq reveals a heterogeneous response of NGP cells upon nutlin-3 treatment, pinpointing putative late-responders or resistant cells, hidden in bulk RNA-seq experiments.
2021-12-31 | GSE144929 | GEO
Project description:We performed gene expression profiling by Affymetrix primeview array in both NGP CRISPR control cells and NGP ALK(LF655del) cells.
2021-08-11 | GSE140025 | GEO
Project description:single cell polyA+ and total RNA-seq data was generated for NGP, SK-N-BE-2C and SHSY5Y-MYCN-TR cells
2019-01-01 | GSE119936 | GEO
Project description:scRNA-seq and bulk RNA-seq analysis of normoxic and hyperoxic lung in mice [bulk RNA-seq]
| PRJNA891758 | ENA
Project description:scRNA-seq and bulk RNA-seq analysis of normoxic and hyperoxic lung in mice [scRNA-seq]
| PRJNA899102 | ENA
Project description:This SuperSeries is composed of the SubSeries listed below.
2021-12-31 | GSE144931 | GEO
Project description:Human pluripotent stem cells (hPSCs) offer a unique cellular model to study lineage specifications of the primary germ layers during human development. We profiled single-cell RNA-seq (scRNA-seq) on four lineage-specific progenitor cells derived from hESCs. Our scRNA-seq analyses revealed each type of progenitors display various extend of heterogeneity. Specifically, definitive endoderm cells (DECs) not only show a greater degree of heterogeneity, but are also enriched in metabolic signatures. Followed by detailed temporal scRNA-seq profiling along DEC differentiation, we reconstructed a differentiation trajectory using a novel statistical pipeline named Wave-Crest. Wave-Crest further identifies candidate regulators during the transitioning phase from Brachyury (T)+ mesendoderm towards CXCR4+ DEC state. To functionally test identified novel regulators; we generated a live cell monitoring system, a T-2A-EGFP knock-in reporter cell line via CRISPR/CAS9. We demonstrated that, among the top candidate genes, KLF8 plays a pivotal role modulating mesendoderm to DEC differentiation. In this submission, 1810 raw fastq files are provided; 212 are re-analysis from GSE64016. Four expected count matrices are provided - 1) 1018 single cells from snapshot progenitors; 2) 758 single cells from time couse profiling; 3) 19 bulk RNA-seq sample from snapshot progenitors; 4) 15 bulk RNA-seq sample from time course profiling. Total 1018 single cells from snapshot progenitors and 758 single cells from time couse profiling. Matchd population bulk RNA-seq samples for both the progenitors snapshot (19 samples) and time course profiling (15 samples) also included in this submission. These data set are used to detect the transitioning phase from mesendoderm to definitive endoderm.
2016-07-21 | E-GEOD-75748 | biostudies-arrayexpress
Project description:Ovarian cancer (OC) was the fifth leading cause of cancer death and the deadliest gynecological cancer in women. This was largely attributed to its late diagnosis, high therapeutic resistance, and a dearth of effective treatments. Clinical and preclinical studies have revealed that tumor-infiltrating CD8+T cells often lost their effector function, the dysfunctional state of CD8+T cells was known as exhaustion. Our objective was to identify genes associated with exhausted CD8+T cells (CD8TEXGs) and their prognostic significance in OC. We downloaded the RNA-seq and clinical data from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. CD8TEXGs were initially identified from single-cell RNA-seq (scRNA-seq) datasets, then univariate Cox regression, the least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression were utilized to calculate risk score and to develop the CD8TEXGs risk signature. Kaplan-Meier analysis, univariate Cox regression, multivariate Cox regression, time-dependent receiver operating characteristics (ROC), nomogram, and calibration were conducted to verify and evaluate the risk signature. Gene set enrichment analyses (GSEA) in the risk groups were used to figure out the closely correlated pathways with the risk group. The role of risk score has been further explored in the homologous recombination repair deficiency (HRD), BRAC1/2 gene mutations and tumor mutation burden (TMB). A risk signature with 4 CD8TEXGs in OC was finally built in the TCGA database and further validated in large GEO cohorts. The signature also demonstrated broad applicability across various types of cancer in the pan-cancer analysis. The high-risk score was significantly associated with a worse prognosis and the risk score was proven to be an independent prognostic biomarker. The 1-, 3-, and 5-years ROC values, nomogram, calibration, and comparison with the previously published models confirmed the excellent prediction power of this model. The low-risk group patients tended to exhibit a higher HRD score, BRCA1/2 gene mutation ratio and TMB. The low-risk group patients were more sensitive to Poly-ADP-ribose polymerase inhibitors (PARPi). Our findings of the prognostic value of CD8TEXGs in prognosis and drug response provided valuable insights into the molecular mechanisms and clinical management of OC.
| S-EPMC11225302 | biostudies-literature