Multiome RNA+ATAC on human PBMCs (snATAC-seq data)
Ontology highlight
ABSTRACT:
INSTRUMENT(S): Illumina NovaSeq 6000
ORGANISM(S): Homo sapiens
SUBMITTER: Mirjana Efremova
PROVIDER: E-MTAB-11226 | biostudies-arrayexpress |
REPOSITORIES: biostudies-arrayexpress
Similar Datasets
Project description:We generated Multiome RNA+ATAC data from the same cell from human PBMC. This served as a gold benchmark for a novel integration method for multi-omics data that we developed.
2021-12-02 | E-MTAB-11225 | biostudies-arrayexpress
Project description:B cells from tonsils of human donors were extracted for combined RNAseq+ATACseq from the same cell. One sample was prepared separately ("old") and is of lower quality, but still included. It primarily holds ATACseq information.
2023-04-13 | E-MTAB-12632 | biostudies-arrayexpress
Project description:This study looks at the ATAC+RNA profiles of human CD4 T cells under bioreactor-like conditions as ACT. Cells were stimulated toward Th1,Th2,Treg and Th17 under anti-CD3/28 activation, and profiled on day 5.
2024-01-31 | E-MTAB-13711 | biostudies-arrayexpress
Project description:In order to understand the genomic and transcriptomic variability of the axolotl pallium, as well as reconstruct their intrinsic gene regulatory networks, we performed single-nucleus multiome sequencing (RNA and open chromatin) of whole axolotl pallium.
2022-07-20 | E-MTAB-11666 | biostudies-arrayexpress
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:Single cell ATAC sequencing of SIINFEKL-reactive immune cell from intracranial murine GL261-SIINFEKL tumors 20 days after inoculation. SIINFEKL-reactive T cells were sorted based on dextramer staining. We show that loss of major histocompatibility complex (MHC) class II (MHCII)-restricted antigen presentation on bbm drives dysfunctional intratumoral tumor-reactive CD8+ T cell states through increased chromatin accessibility and expression of Tox, a critical regulator of T cell exhaustion.
2023-01-11 | E-MTAB-12512 | biostudies-arrayexpress
Project description:We obtained human embryonic and fetal lungs from 5-22 pcw for scRNAseq and scATACseq analysis. To focus on epithelial differentiation and region specialization, we deeply sampled 15, 18, 20 and 22 pcw lungs and separated proximal and distal regions while leaving lungs at 5, 6, 9 and 11 pcw intact. These cell samples (except for one at 6pcw) were split and processed for both scRNAseq and scATACseq.
2022-01-27 | E-MTAB-11266 | biostudies-arrayexpress
Project description:The aim of the experiment was to investigate the clonal relationship between CD8+ T cell subsets of donor matched blood with epidermal CD8+ T cells. Abdominal skin (n=8) was separated into dermis and epidermis, followed by epidermal skin and PBMC isolation. Single CD8+ T cells (n=6) and CD3+ T cells (n=2) were FACS sorted, processed with the 5’ 10x Genomics workflow and sequenced at NGI Sweden.
2023-06-12 | E-MTAB-12839 | biostudies-arrayexpress
Project description:Using Multiome and previously published sc/snRNA-seq data, we studied eight anatomical regions of the human heart including left and right ventricular free walls (LV and RV), left and right atria (LA and RA), left ventricular apex (AX), interventricular septum (SP), sino-atrial node (SAN) and atrioventricular node (AVN). For the first time, we profile the cells of the human cardiac conduction system, revealing their distinctive repertoire of ion channels, G-protein coupled receptors and cell-cell interactions. We map the identified cells to spatial transcriptomic data to discover cellular niches within the eight regions of the heart.
2023-06-13 | E-MTAB-12919 | biostudies-arrayexpress
Project description:scGET-seq profiling of NIH3T3 cells in which Kdm5c was silenced with antisense shRNA or with a control scramble shRNA.
2021-08-17 | E-MTAB-9651 | biostudies-arrayexpress