B80d1540-ae13-44ae-b067-192084db4222 - samples
Ontology highlight
ABSTRACT:
PROVIDER: EGAD00001009174 | EGA |
REPOSITORIES: EGA
Similar Datasets
Project description:Purpose: To build an atlas of head and neck squamous cell carcinoma (HNSCC) using single-cell RNA-sequencing (scRNA-seq) data with surface protein expression using AbSeq oligo-tagged antibodies.
2021-12-02 | GSE140042 | GEO
Project description:Single-cell RNA-sequencing (scRNA-Seq) is widely used to characterize immune cell populations. However, mRNA levels correlate poorly with expression of surface proteins, which are well established to define immune cell types. CITE-Seq (cellular indexing of transcriptomes and epitopes by sequencing) utilizes oligonucleotide-tagged antibodies to simultaneously analyze surface phenotypes and transcriptomes. Considering the high costs of adding surface phenotyping to scRNA-Seq, we aimed to determine which of 188 tested CITE-Seq antibodies can detect their antigens on human peripheral blood mononuclear cells (PBMCs), a commonly interrogated cell population in immunology, and find the optimal concentration for staining. The recommended concentration was optimal for 76 antibodies, whereas staining quality of 7 antibodies improved when the concentration was doubled. 33 and 8 antibodies still worked well when the concentration was reduced to 1/5 or 1/25, respectively. 64 antigens were not detected at any antibody concentration. Optimizing the antibody panel by removing antibodies not able to detect their target antigens and adjusting concentrations of the remaining antibodies could enable a cost reduction of almost 50%. In conclusion, our data are a resource for building an informative and cost-effective panel of CITE-Seq antibodies and use them at their optimal concentrations in future CITE-seq experiments on human PBMCs.
2022-09-18 | GSE213282 | GEO
Project description:The recently developed transcription, epitopes, and chromatin accessibility by sequencing (TEA-seq) and similar DOGMA-seq single-cell trimodal omics assays provide unprecedented opportunities for understanding cell biology, but independent optimization, benchmarking and evaluation are lacking. We explored the utility, pros and cons of DOGMA-seq compared to the bimodal cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq) assay in activated and stimulated human peripheral blood T cells. We identified an optimal incubation time and concentration of digitonin (DIG) for cell permeabilization and found that single-cell trimodal omics measurements after DIG permeabilization were generally better than after an alternative “low-loss lysis” (LLL) permeabilization condition. Next, we found that DOGMA-seq with optimized DIG permeabilization and its ATAC library provides more information, even though its mRNA and cell surface protein antibody-derived tag (ADT) libraries have slightly inferior quality, compared to CITE-seq. Finally, we recognized the additional value of DOGMA-seq for studying lineage-specific T helper cells.
2022-06-13 | GSE200417 | GEO
Project description:The recent advance of single cell sequencing (scRNA-seq) technology such as Cellular Indexing of Transcriptomes and Epitopes by Sequencing (CITE-seq) allows researchers to quantify cell surface protein abundance and RNA expression simultaneously at single cell resolution. Although CITE-seq and other similar technologies have quickly gained enormous popularity, novel methods for analyzing this new type of single cell multi-omics data are still in urgent need. A limited number of available tools utilize data-driven approach, which may undermine the biological importance of surface protein data. In this study, we developed SECANT, a biology-guided SEmi-supervised method for Clustering, classification, and ANnoTation of single-cell multi-omics. SECANT can be used to analyze CITE-seq data, or jointly analyze CITE-seq and scRNA-seq data. The novelties of SECANT include 1) using confident cell type labels identified from surface protein data as guidance for cell clustering, 2) providing general annotation of confident cell types for each cell cluster, 3) fully utilizing cells with uncertain or missing cell type labels to increase performance, and 4) accurate prediction of confident cell types identified from surface protein data for scRNA-seq data. Besides, as a model-based approach, SECANT can quantify the uncertainty of the results, and our framework can be easily extended to handle other types of multi-omics data. We successfully demonstrated the validity and advantages of SECANT via simulation studies and analysis of public and in-house real datasets. We believe this new method will greatly help researchers characterize novel cell types and make new biological discoveries using single cell multi-omics data.
2022-09-03 | GSE168264 | GEO
Project description:In this study we used single cell multi-omics profiling to create an atlas of the human YS to gain insights into its haematopoietic, metabolic and nutritive functions during early embryonic development. This contains CITE-seq data (surface protein and cytosolic RNA content) data from two biological replicates. Pooled lanes were demultiplexed using SoupOrCell (for alignment and demultiplexing software and version numbers, please see accompanying manuscript and protocols within this accession). Raw count files provided are directly as output by alignment software, without any quality control applied. Quality control is described in accompanying manuscript methods. Metadata by barcode are provided as supplementary tables in accompanying manuscript.
2022-12-08 | E-MTAB-11549 | biostudies-arrayexpress
Project description:In this study we used single cell multi-omics profiling to create an atlas of the human YS to gain insights into its haematopoietic, metabolic and nutritive functions during early embryonic development. This contains fetal liver CITE-seq (surface protein and cytosolic RNA content) data from six biological replicates. Pooled lanes were demultiplexed using SoupOrCell (for alignment and demultiplexing software and version numbers, please see accompanying manuscript and protocols within this accession). Raw count files provided are directly as output by alignment software, without any quality control applied. Quality control is described in accompanying manuscript methods. Metadata by barcode are provided as supplementary tables in accompanying manuscript.
2022-12-08 | E-MTAB-11613 | biostudies-arrayexpress
Project description:In this study we used single cell multi-omics profiling to create an atlas of the human YS to gain insights into its haematopoietic, metabolic and nutritive functions during early embryonic development. This contains embryonic liver CITE-seq (surface protein and cytosolic RNA content) data from three biological replicates. Pooled lanes were demultiplexed using SoupOrCell (for alignment and demultiplexing software and version numbers, please see accompanying manuscript and protocols within this accession). Raw count files provided are directly as output by alignment software, without any quality control applied. Quality control is described in accompanying manuscript methods. Metadata by barcode are provided as supplementary tables in accompanying manuscript.
2022-12-08 | E-MTAB-11618 | biostudies-arrayexpress
Project description:Single cells from human colorectal cancer and normal adjacent colon of 16 patients were used for single-cell RNA-seq, TCR-seq, CITE-seq and Cell hashing. In brief, single cells were incubated for 3h with or without PMA/Ionomycin, and were treated with Cell hashing and CITE-seq antibodies to distinguish samples, stimulation/non-stimulation, and cell surface proteins. Sorted viable CD3+TCRαβ+ single cells were loaded into 10x genomics ChromiumTM controller to make nanoliter-scale droplets with uniquely barcoded 5’ gel beads called GEMs. After GEM-RT and the following some cDNA amplification steps, cDNAs derived from cellular mRNA were pooled for downstream processing and library preparation according to the manufacturer’s instructions. The 5’ transcript library was sequenced with Illumina Novaseq. The single cell TCR enriched library was sequenced with Illumina Miseq using 150 paired-end reads. HTO/ADTs from Cell hashing or CITE-seq were amplified using specific primers that append P5 and P7 sequences for illumina sequencing (Miseq or Nextseq). All fastq files were demultiplexed. Cell hashing and CITE-seq barcodes are available in attached text files. Fastq files from RNA-seq and TCR-seq can be processed through cellranger and vdjranger by 10xgenomics. The datasets include the data of independent experiments at May 29, June 16, June 23, and Aug 13, 2019. Details are available in Masuda et al., bioRxiv, 2020, The functional and phenotypic diversity of single T-cell infiltrates in human colorectal cancer as correlated with clinical outcome.
2022-03-02 | E-MTAB-9455 | biostudies-arrayexpress
Project description:We report here the analysis of young and aged hematopoietic stem and progenitor cells (HSPCs) by transcriptional profiling (bulk RNA-Seq, CITE-Seq) and chromatin profiling (ATAC-Seq, scATAC-Seq). We use here a Clca3a1 as a surface marker to further fractionate HSPCs. HSPCs were sorted by flow cytometry. During the staining procedure for flow cytometry, the antibody cocktail also included antibodies labelled with oligos (antibody-derived tags =ADTs) which can later be analyzed by the 10x Chromium controller.
2022-07-14 | GSE157458 | GEO
Project description:We developed a single cell application of the sequencing-based immunodetection method ID-seq which makes it possible to multiplex measurements of many different epitopes from proteins and phosphoproteins in a high throughput setting. A FACS sort step was implemented to allow sorting of single cells in 96 well plates. With these DNA-tagged antibodies and dedicated sample preparation protocol adapted for single cells, we studied the studied the changes of 70 (phospho-)proteins in primary human skin cells compared to a subpopulation with low ITGB1 protein expression. Given that ITGB1 is a skin stem cell marker, we indeed found that the ITGB1 low cells are differentiated and we found a role for BMP signaling in this process.
2018-11-28 | GSE115925 | GEO