Ontology highlight
ABSTRACT:
PROVIDER: PRJNA1007577 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR25874312_1.fastq.gz | Fastqsanger.gz | |||
| SRR25874312_2.fastq.gz | Fastqsanger.gz | |||
| SRR25874313_1.fastq.gz | Fastqsanger.gz | |||
| SRR25874313_2.fastq.gz | Fastqsanger.gz | |||
| SRR25874314_1.fastq.gz | Fastqsanger.gz |
Items per page: 5 1 - 5 of 36 |
Similar Datasets
Project description:Atlas of lymphangiogenesis [scATAC-Seq]
| PRJNA778402 | ENA
Project description:We present a joint scRNA-seq and scATAC-seq atlas of adult human retinal pigment epithelium (RPE) and choroid. We integrate this atlas with a HiChIP enhancer connectome to predict noncoding variants with causal roles in age-related macular degeneration (AMD).
2025-03-25 | GSE262151 | GEO
Project description:Single cell ATAC-seq (scATAC-seq) was performed on macaque embryonic stem cell-derived cerebral organoids. scATAC-seq was performed on day 60 (2 months old cerebral organoid).
2019-10-16 | E-MTAB-8087 | biostudies-arrayexpress
Project description:Aging is a universal biological phenomenon linked to many diseases, such as cancer or neurodegeneration. However, the molecular mechanisms underlying aging, or how lifestyle interventions such as cognitive stimulation can ameliorate this process, are yet to be clarified. Here, we performed a multi-omic profiling, including RNA-seq, ATAC-seq, ChIP-seq, EM-seq, SWATH-MS and single cell Multiome scRNA and scATAC-seq, in the dorsal hippocampus of young and old mouse subjects which were subject to cognitive stimulation using the paradigm of environmental enrichment. In this study we were able to describe the epigenomic landscape of aging and cognitive stimulation.
2023-09-29 | PXD045567 | Pride
Project description:Single cell ATAC-seq (scATAC-seq) was performed on bonobo induced pluripotent stem cells (iPSC) derived cerebral organoids. scATAC-seq was performed on day 60 (2 months old cerebral organoid) and day 120 (4 months old cerebral organoid).
2019-10-16 | E-MTAB-8083 | biostudies-arrayexpress
Project description:Estrogen-triggered Monkey Multi-Organ Cell Atlas [scATAC-seq]
| PRJNA1019783 | ENA
Project description:In order to provide multi-omic resolution to human retinal organoid developmental dynamics, we performed scRNA-seq and scATAC-seq from the same cell suspension across a time course (6-46 weeks) of human retinal organoid development. This data set covers all the retinal organoid scATAC-seq data generated from IMR90 and 409B2-iCas9 cell lines.
2023-03-12 | E-MTAB-12714 | biostudies-arrayexpress
Project description:Here, we apply tRNA-seq and YAMAT-seq to profile the expressions of tRFs and tRNAs in plants. We provide a high-quality expression atlas of tRFs and tRNAs in Arabidopsis and rice, and uncover complex tRF population and the dynamic expressions of tRNA genes in plants.
2021-01-01 | GSE154165 | 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:Here, we adopt a method that combines tRNA-seq and cp-RNA-seq to identify and quantify tRFs and tRNAs in plants. We provide a high-quality expression atlas of tRFs and tRNAs in Arabidopsis and rice, and uncovers complex tRFs repertoire and the dynamic expressions of tRNA genes in plants.
2021-01-01 | GSE124608 | GEO