Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Single-cell RNA-seq analysis of human tumor ascites dendritic cells and macrophages

ABSTRACT: We performed single-cell RNA-seq on dendritic cells and macrophages isolated from the tumor ascites of one cancer patient. We used the 10x chromium technology. The expression matrix provided in supplementary is the result Cellranger aggregate method on : GSE115007, GSE115006 and GSE103544.

ORGANISM(S): Homo sapiens

PROVIDER: GSE115007 | GEO | 2018/05/30

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Single-cell RNA-seq analysis of human tonsil dendritic cells

Project description:We performed single-cell RNA-seq on dendritic cells isolated from the tonsils of one healthy donor. We used the 10x chromium technology.The expression matrix provided in supplementary is the result of Cellranger aggregate method on : GSE115007, GSE115006 and GSE103544.

2018-05-30 | GSE115006 | GEO

single cell RNA-seq analysis of ovarian cancer ascites

Project description:To understand the cellular diversity within malignant ascites, we profiled ~11,000 single cells from 22 samples by Smartseq2 and by 10x.

2020-05-01 | GSE146026 | GEO

Human fetal yolk sac scRNA-seq data (sample ID: F158 for Haniffa Lab; 16099 for HDBR)

Project description:Investigating the blood, immune and stromal cells present in a human fetal embryo in a world first single cell transcriptomic atlas. The embryo was dissected into 12 coronal sections, yolk sac, and yolk sac stalk. Live single cells sorted, with cell suspension then undergoing 10x chromium 5 prime scRNA-seq. This accession contains the yolk sac and yolk sac stalk data from this embryo. A matched accession contains the coronal section data. Lane "WS_wEMB12142156" (from yolk sac) was excluded from downstream analysis due to low fraction reads in cells post-CellRanger QC. Termination procedure for this embryo was medical. The F158_[features...barcodes...matrix].[tsv...mtx].gz files attached to this accession represent raw count data from all the 10x lanes in this accession combined, and as output from CellRanger filtered matrices (CellRanger version 6.0.1 using human reference genome GRCh38-2020-A). One set of count matrices relates to the yolk sac data, and one set of count matrices relates to the yolk sac stalk data.

2022-12-07 | E-MTAB-11673 | biostudies-arrayexpress

Single cell profiling of 3 Human Lung Adenocarcinoma cell lines.

Project description:An equal mixture of cells from the 3 Human Lung Adenocarcinoma cell lines (H2228, NCI-H1975 and HCC827) were processed on the Chromium 3' single cell platform (10X Genomics) and sequenced on an Illumina NextSeq 500. FASTQ data were preprocessed using both scPipe and CellRanger.

2018-02-28 | GSE111108 | GEO

Quantitative proteomic analysis of human malignant ascites

Project description:Ascites is a valuable source of cancer biomarkers, because it contains a variety of secreted and shed proteins from cancerous cells. Conversely, most proteomic studies on ascites have focused on ovarian cancer and provided insufficient depth for biomarker discovery. Further, no proteomic analysis of ascites from gastric cancer has been reported. To this end, we profiled the human ascites proteome to obtain a pool of biomarker candidates using comprehensive proteomic strategies. Subsequently, label-free quantitation was performed to compare the abundance of proteins between benign disease and gastric cancer patients.

2018-04-16 | PXD004501 | Pride

Ascites-derived circulating microRNAs as potential diagnostic biomarkers of gastric cancer-associated malignant ascites

Project description:Peritoneal carcinomatosis with malignant ascites is associated with dismal prognosis in gastric cancer. Malignant ascites is the most relevant body fluid in which to seek diagnostic biomarkers for peritoneal carcinomatosis. We aimed to identify and validate ascites-derived circulating microRNAs (miRNAs) that are differentially expressed between liver cirrhosis-associated benign ascites (LC-ascites) and gastric cancer-associated malignant ascites (GC-ascites). MiRNA expression levels were investigated in three independent cohorts. Overall, 165 ascites samples (73 LC-ascites and 92 GC-ascites) were obtained from the National Biobank of Korea. Initially, microarrays were used to screen the expression levels of 2,006 miRNAs in the discovery cohort (n = 22). Subsequently, quantitative reverse transcriptase-polymerase chain reaction (qRT-PCR) analyses were used to validate the expression levels of selected miRNAs in the training (n = 70) and validation (n= 73) cohorts. In addition, the levels of carcinoembryonic antigen (CEA), a commonly used tumor marker, were determined in the ascites samples. Expression levels of miR-574-3p, miR-181b-5p, miR-4481, and miR-181d were significantly lower in the GC-ascites samples than in the LC-ascites samples, and miR-181b-5p showed the best diagnostic performance for GC-ascites (area under the curve [AUC] = 0.798 and 0.846 for the training and validation cohorts, respectively). The diagnostic performance of CEA for GC-ascites was improved if CEA and miR-181b-5p were analyzed together (AUC = 0.981 and 0.946 for the training and validation cohorts, respectively). Overall, we identified ascites-derived circulating miRNAs capable of differentiating non-malignant ascites and GC-ascites, and demonstrated that the combined use of miR-181b-5p and CEA produces the optimal diagnostic yield.

2019-02-12 | GSE126399 | GEO

Single-cell RNA-seq analysis of human tumor ascites dendritic cells and macrophages

Project description:Single-cell RNA-seq analysis of human tumor ascites dendritic cells and macrophages

| PRJNA473508 | ENA

snATAC-seq of the developing mouse cerebellum across eleven stages

Project description:This study used droplet-based snATAC-seq to profile the chromatin accessibility landscape of 91,922 nuclei in the mouse cerebellum across eleven developmental stages, from the beginning of neurogenesis (e10.5) till adulthood (P63). The study included two biological replicates per stage, one from each sex. Cerebelli were dissected as whole or in two halves, nuclei were extracted and profiled using 10x single-cell ATAC reagent kit (v1.0) and a Chromium controller. Libraries were sequenced using paired-reads on Illumina NextSeq 550 and initial data processing was performed using Cellranger ATAC (1.1).

2021-09-07 | E-MTAB-9765 | biostudies-arrayexpress

Single cell analysis of Monolayer and Organoid Primary Prostate Human Epithelial Cells Derived from the same patient

Project description:Single human primary prostate epithelial cells grown as a monolayer (2D) or as organoids (3D) were separated, collected and prepped for RNA-seq using the 10x Genomics Chromium Genome Reagent kit v2 Chemistry. 3,500-5,000 cells were collected from each sample and sequenced at a depth of ~45,000 genes per cells on a 2x150nt lane in a HiSeq 4000. CellRanger alignment was performed to produce the RAW data files.

2019-07-11 | GSE130318 | GEO

Single Cell RNA sequencing of the Dendritic Cells from controls and pulmonary arterial hypertension (PAH) patients

Project description:We report the application of single cell RNA sequencing on human dendritic cells. By using the negative selecting kit, we enriched theconventional DC from human PBMCs. The seven samples are sequenced as biological replications (4 control and 3 patients), and pooled at the analysis stage. The library was prepared using the Chromium Single Cell 3' v2 Reagent Kit, and sample processing was under bcl2fastq2/2.20.0 and cellranger/2.2.0. We report a increased cDC1 to cDC2 ratio, and an increased inflammatory DC in PAH patient, with the major changes of CXCR4 expression which are experimentally confirmed. This study provide a reference for studying the DC related abonormalties in PAH and other inflammatory diseases.

2022-06-01 | GSE164493 | GEO

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data