Tonsil Atlas FASTQ files
Ontology highlight
ABSTRACT:
PROVIDER: PRJEB75429 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| Other | ||||
| ERR13027100_1.fastq.gz | Fastqsanger.gz | |||
| ERR13027100_2.fastq.gz | Fastqsanger.gz | |||
| ERR13027200_1.fastq.gz | Fastqsanger.gz | |||
| ERR13027200_2.fastq.gz | Fastqsanger.gz |
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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 investigate miRNA expression in human tonsil squamous cell carcinoma (SCC) compared to normal tonsil tissue. Two colour LNA Exiqon array. MicroRNAs were labeled at 3'-end with a P-CU-C3-Cy3 RNA linker. A mixture of 371 synthetic DNA reference oligonucleotides containing complementary sequences to all LNA probes was randomly labeled using the ULYSIS labeling kit.
2015-12-23 | GSE75630 | GEO
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Project description:Tonsil cancer compared with normal tonsil tissue
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Project description:Here we report a comprehensive atlas of candidate cis-regulatory DNA elements (cCREs) in the adult mouse brain, generated through examination of the chromatin accessibility in 2.3 million individual brain cells from 117 anatomical dissections. The atlas includes approximately 1 million cCREs and their chromatin accessibility across 1482 distinct brain cell populations, adding over 446,000 new cCREs to the most recent such annotation in the mouse genome. Raw fastq files are demultiplexed. Out of 234 samples, fastq files for 6 samples are available in NCBI under the accession number GSE126724 (CEMBA180308_3B, CEMBA180312_3B, CEMBA180226_1A, CEMBA180227_1A, CEMBA180305_2B, CEMBA180306_2B). Processed data are SnapATAC2 (<= 2.4.0) h5ad files per sample, with raw fragments and 500-bp bmat. NOTE: due to the break changes in SnapATAC2 >= 2.5.0, the data can not be handled rightly in SnapATAC2 >= 2.5.0.
2023-11-02 | GSE246791 | GEO
Project description:We used ATLAS-seq to comprehensively map the genomic location of LINE-1 elements belonging to the youngest and potentially polymorphic subfamily (L1HS-Ta). This was performed in a panel of 12 human primary or transformed cell lines (BJ, IMR90, MRC5, H1, K562, HCT116, HeLa S3, HepG2, MCF7, HEK-293, HEK-293T, 2102Ep). In brief, ATLAS-seq relies on the random mechanical fragmentation of the genomic DNA to ensure high-coverage, ligation of adapter sequences, suppression PCR-amplification of L1HS-Ta element junctions, and Ion Torrent sequencing using single-end 400 bp read chemistry. A notable aspect of ATLAS-seq is that we can obtain both L1 downstream and upstream junctions (3'- and 5'-ATLAS-seq libraries, respectively), for full-length L1 elements. Note that a 10-nt sample-specific barcode has been removed at the 5' end of the reads in the .fastq files upon demultiplexing. This was achieved using cutadapt v1.9.2.dev0 (with the following parameters: -e 0.1 -q 10 -m 25 -g <barcode_name>=^<barcode_sequence>)
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