Similar Datasets
Project description:We performed single-cell RNA-seq on CD14+ cells isolated from the tonsils of one healthy donor. We used the 10x chromium technology.
2019-04-25 | GSE119506 | GEO
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
Project description:Single-cell RNAseq (10x Genomics) analysis of human CD4+ T cells in IPEX patients, healthy donors and heterozygous mothers (blood). Human CD4+T cells from IPEX, HD and mothers were isolated from frozen peripheral blood mononuclear cells by flow cytometry as DAPI–CD3+CD4+ cells. In cohort 1, cells from separate donor were encapsulated in separate channel following 10x Genomics Single Cell 3′ Reagent Kit (V2 chemistry). In cohort 2, samples were tagged using a different Hashtags, pooled and encapsulared following 10x Genomics Single Cell 3′ Reagent Kit (V3 chemistry).
2021-03-02 | GSE167976 | GEO
Project description:We performed single-cell RNA-seq on CD14+ monocytes isolated from the blood of healthy donors. Using the 10x chromium technology, we analyzed 425 and 431 cells from 2 individual donors.
2017-09-15 | GSE103544 | GEO
Project description:This repository contains all the FASTQ files for the five data modalities (scRNA-seq, scATAC-seq, Multiome, CITE-seq+scVDJ-seq, and spatial transcriptomics) used in the article \\"An Atlas of Cells in The Human Tonsil,\\" published in Immunity in 2024. Inspired by the TCGA barcodes, we have named each fastq file with the following convention: [TECHNOLOGY].[DONOR_ID].[SUBPROJECT].[GEM_ID].[LIBRARY_ID].[LIBRARY_TYPE].[LANE].[READ].fastq.gz which allows to retrieve all metadata from the name itself. Here is a full description of each field: - TECHNOLOGY: scRNA-seq, scATAC-seq, Multiome, CITE-seq+scVDJ-seq, and spatial transcriptomics (Visium). We also include the fastq files associated with the multiome experiments performed on two mantle cell lymphoma patients (MCL). - DONOR_ID: identifier for each of the 17 patients included in the cohort. We provide the donor-level metadata in the file \\"tonsil_atlas_donor_metadata.csv\\", including the hospital, sex, age, age group, cause for tonsillectomy and cohort type for every donor. - SUBPROJECT: each subproject corresponds to one run of the 10x Genomics Chromium™ Chip. - GEM_ID: each run of the 10x Genomics Chromium™ Chip consists of up to 8 \\"GEM wells\\" (see https://www.10xgenomics.com/support/software/cell-ranger/getting-started/cr-glossary): a set of partitioned cells (Gel Beads-in-emulsion) from a single 10x Genomics Chromium™ Chip channel. We give a unique identifier to each of these channels. - LIBRARY_ID: one or more sequencing libraries can be derived from a GEM well. For instance, multiome yields two libraries (ATAC and RNA) and CITE-seq+scVDJ yields 4 libraries (RNA, ADT, BCR, TCR). - LIBRARY_TYPE: the type of library for each library_id. Note that we used cell hashing () for a subset of the scRNA-seq libraries, and thus the library_type can be \\"not_hashed\\", \\"hashed_cdna\\" (RNA expression) or \\"hashed_hto\\" (the hashtag oligonucleotides). - LANE: to increase sequencing depth, each library was sequenced in more than one lane. Important: all lanes corresponding to the same sequencing library need to be inputed together to cellranger, because they come from the same set of cells. - READ: for scATAC-seq we have three reads (R1, R2 or R3), see cellranger-atac's documentation. While we find these names to be the most useful, they need to be changed to follow cellranger's conventions. We provide a code snippet in the README file of the GitHub repository associated with the tonsil atlas to convert between both formats (https://github.com/Single-Cell-Genomics-Group-CNAG-CRG/TonsilAtlas/). Besides the fastq files, cellranger (and other mappers) require additional files, which we also provide in this repository: - cell_hashing_metadata.csv: as mentioned above, we ran cell hashing (10.1186/s13059-018-1603-1) to detect doublets and reduce cost per cell. This file provides the sequence of the hashtag oligonucleotides in cellranger convention to allow demultiplexing. - cite_seq_feature_reference.csv: similar to the previous file, this one links each protein surface marker to the hashtag oligonucleotide that identified it in the CITE-seq experiment. - V10M16-059.gpr and V19S23-039.gpr: these correspond to the two slides of the two Visium experiments performed in the tonsil atlas. They are needed to run spaceranger. - [GEM_ID]_[SLIDE]_[CAPTURE_AREA].jpg: 8 images associated with the Visium experiments. Here, GEM_ID refers to each of the 4 capture areas in each slide. - [TECHNOLOGY]_sequencing_metadata.csv: the GEM-level metadata for each technology. It includes the relationship between subproject, gem_id, library_id, library_type and donor_id. These are the other repositories associated with the tonsil atlas: - Expression and accessibility matrices: https://zenodo.org/records/10373041 - Seurat objects: https://zenodo.org/records/8373756 - HCATonsilData package: https://bioconductor.org/packages/release/data/experiment/html/HCATonsilData.html - Azimuth: https://azimuth.hubmapconsortium.org/ - Github: https://github.com/Single-Cell-Genomics-Group-CNAG-CRG/TonsilAtlas
2024-05-02 | E-MTAB-13687 | biostudies-arrayexpress
Project description:To further know features of CD4+CD8+ Double positive (DP)-Tfh cells in respective lymphoid tissues, we subsequently investigated transcriptomes of DP-Tfh cells in submandibular gland lesions of IgG4-RD in comparison to those of DP-Tfh cells in tonsils. Results showed that DP-Tfh cells of IgG4-RD lesions were more apt to present CTL-related genes such as Eomes and granzymes than DP-Tfh cells in tonsils. It was also noted that the level of CD70 in DP-Tfh cells of IgG4-RD lesions was higher than that of tonsillar DP-Tfh cells. Genes related to Tfh cell function were seemed to be presented in DP-Tfh cells of tonsils compared to DP-Tfh cells of IgG4-RD lesions.
2022-08-10 | GSE202617 | GEO
Project description:CD4+ T cells play a fundamental role in host defenses against viruses by orchestrating B cell development and/or by directly targeting pathogens. This dataset aimed at understanding the molecular profile of CD4+ T cells in the context of an acute and severe SARS-CoV-2 infection. The analyzed patient was recruited at Henri Mondor University Hospital (AP-HP, Paris France) in March 2020, and required oxygen as treatment. Peripheral (CD14-CD56-CD123-CD19-CD3+CD4+CD45RA-PD-1high) T cells were FACS-sorted using a Sony MA900 in PBS/0.08% FCS. 1.105 cells were obtained and 20000 were loaded in the 10x Chromium Controller to generate single-cell gel-beads in emulsion. The scRNA-seq libraries were generated using the Chromium Next GEM Single Cell V(D)J Reagent Kit v.1.1 with Feature Barcoding (10x Genomics) according to the manufacturer’s protocol. PBMCs were initially isolated from venous blood samples via standard density gradient centrifugation and used after cryopreservation at -150°C. Cells were thawed using RPMI-1640 (Gibco) 10% FBS, washed twice and incubated with fluorochrome-conjugated antibody cocktail and viable cells were identified using a LIVE/DEAD Fixable Aqua Dead Cell Stain Kit (Thermo Fisher Scientific) incubated with conjugated antibodies used for cell sorting (CD3/CD4/CD14/CD19/CD45/CD56/CD123/PD-1) as well as a panel of barcoded TotalSeqC® antibodies (CD11c/CD21/CD27/CD38/CD49d/CD69/CD71/CD73/CD95/CD103/CD138/CD305/CD307d/CD307e/CXCR3/CXCR4/CXCR5/HLA-DR/ICOS/ITB7/LAG-3/NKG2D/TIM3). A single sort was performed for this patient and 5’-transcriptomic, VDJ and ADT libraries were sequenced .
2023-09-30 | E-MTAB-13321 | biostudies-arrayexpress
Project description:We report a series of single-cell transcriptomic datasets of the mouse regenerating muscle tissue produced using the Chromium 10X technology.
2020-01-11 | GSE143437 | GEO
Project description:We report the application of single-molecule-based sequencing technology for high-throughput profiling of 5 Ewing Sarcoma PDX (PDX-184, 352, 856, 861 and 1058) with the 10X Genomics Chromium technology.
2020-02-14 | GSE130024 | GEO
Project description:We report a series of single-cell transcriptomic datasets of FACS-sorted mouse muscle tissue cells from injured muscle produced using the Chromium 10X technology.
2020-01-11 | GSE143435 | GEO