Dcc4e242-ffa2-4244-aa8b-89f604f524d2 - samples
Ontology highlight
ABSTRACT:
PROVIDER: EGAD00001010167 | EGA |
REPOSITORIES: EGA
Similar Datasets
Project description:Investigating the blood, immune and stromal cells present in a human fetal embryo in a world first single cell transcriptomic atlas. The embryo was dissected into 12 coronal sections, yolk sac, and yolk sac stalk. Live single cells sorted, with cell suspension then undergoing 10x chromium 5 prime scRNA-seq. This accession contains the yolk sac and yolk sac stalk data from this embryo. A matched accession contains the coronal section data. Lane "WS_wEMB12142156" (from yolk sac) was excluded from downstream analysis due to low fraction reads in cells post-CellRanger QC. Termination procedure for this embryo was medical. The F158_[features...barcodes...matrix].[tsv...mtx].gz files attached to this accession represent raw count data from all the 10x lanes in this accession combined, and as output from CellRanger filtered matrices (CellRanger version 6.0.1 using human reference genome GRCh38-2020-A). One set of count matrices relates to the yolk sac data, and one set of count matrices relates to the yolk sac stalk data.
2022-12-07 | E-MTAB-11673 | biostudies-arrayexpress
Project description:For single cell RNA sequencing analysis, whole cell population isolated from two breast cancer bone metastases and associated organoid models were analyzed by 10X genomic single cell RNA platform. Raw BCL files from Novaseq6000 was converted to FASTQ files with cellranger (Version: 3.1.0) mkfastq function. Cellranger count function was then applied for read alignment, barcode and UMI counting using GRCh38 as reference. scCB2 and DoubletFinder were used to predict and remove empty droplets and doublets of single cell data. Cells with number of features less 300 and more than 9000 were further filtered out based on the distribution of number of features. For bulk RNA sequencing, RNA were extracted from FFPE preserved primary tumor and bone metastasis. Library was prepared with TruSeq Stranded mRNA for FFPE kit, and sequenced by NextSeq 500 with high output 150 cycle kit.
2022-02-08 | GSE190772 | GEO
Project description:The adult healthy human pancreas has been poorly studied given lack of indication to obtain tissue from the pancreas in the absence of disease and rapid postmortem degradation. We obtained pancreata from brain dead donors thus avoiding any warm ischemia time. We found that neoplastic lesions occur frequently in healthy organs, in donors as young as in their 3rd decade of life. Using the 10X Genomics Platform, we performed single cell RNA sequencing on 6 donor pancreata, 5 of which we separately sequenced tissue from the pancreas head and tail, for a total of 11 sequencing runs. This is a robust single-cell dataset of healthy, nonpathologic pancreas tissue and includes acinar, ductal, and non-epithelial cells (myeloid cells, fibroblasts, endothelial cells, lymphocytes). We compared this dataset of normal pancreata to single cell sequencing of tumor samples previously published in Steele, et al, Nature Cancer 2020, (raw fastq in dbGap phs002071) realigned to GRCh38 reference genome (CellRanger 6.0). This GEO series contains the raw and filtered feature matrices for the donor pancreata as well as the realigned tumor samples. Supplementary files contain the aggregate feature matrices and the metadata of the donor pancreata samples and the tumor samples.
2023-05-01 | GSE229413 | GEO
Project description:We perform 10X Genomics scRNA-Seq on P2, P21, P2 + 7 days post wound, P21 + 7 days post wound, with 3 bioreplicates for each condition. Fastq files and output folders were generated from Cellranger pipeline. Loom files were generated using Velocyto.py for downstream analysis. Chemistry: V2
2020-07-01 | GSE153596 | GEO
Project description:Methods: Cells isolated from the whole brains of naive wild type, infected wild type, and infected CCR2-DTR mice were sort-purified on live CD45hi cells from five biological replicates and pooled. Sort-purified cells were then processed using the 10X Genomics Chromium Controller. Cell suspensions were loaded onto the Chromium Single Cell A Chip for cell lysis and barcoding. RNA from individual cells was reverse transcribed and sequencing libraries prepared using the Chromium Single Cell 3’ Library Kit v2 following the manufacturers protocol. Samples were sequenced using an Illumina NextSeq 550 with standard 10X Genomics Configuration (26 bp x 98 bp). After sequencing, raw bcl files were processed using the cellranger mkfastq command for sample demultiplexing and conversion to .fastq files, followed by cellranger count for cell barcode and UMI deconvolution as well as mapping to the respective reference genome. Processed digital gene expression matrices were imported into R studio for analysis using the Seurat package. Samples were aligned along common sources of variation and compared using canonical correlation analysis to identify unique clusters of cells within the samples. Marker genes for each sample and cluster were identified and used for generation of downstream plots within the Seurat package. All packages are maintained to be best in class and are regularly updated to their most recent release. Results: 10 distinct cell clusters were identified and we found that two populations were found at increased proportions post-infection but were substantially reduced in the monocyte-depleted animals (CCR2-DTR). We confirmed that these populations to be monocytes and monocyte-derived cells, and valicated their immunoregulatory molecules by RT-qPCR analysis.
2022-08-25 | GSE189957 | GEO
Project description:Raw RNAseq data (fastq) files that were analyzed for circadian changes in RNA ribosome binding. The numbers in the file names (00 - 44) represent circadian time (0 to 44 hours in constant dark and constant temperature). Two separate sets of samples (independent biological replicates) were collected over a 44-hour period of time.
2021-09-06 | GSE183282 | GEO
Project description:The goals of this study are to determine tissue composition of human lung organoids (hLOs) when maintained long-term (day 230). hLOs consist of alveolar epithelial cells, mesenchymal/endothelial cells, smooth muscle cells and immune cells. After dissociated hLOs, a target capture of 1x 104 cells was performed using the 10X Genomics Chromium Single Cell RNA sequencing. Briefly, single cell gel bead-in-emulsions(GEMs) are generated by passing cells with enzyme mix, partitioning oil, and barcoded gel beads by 10X Chromium chip. After GEM formation, the gel bead is dissolved and co-partitioned cell is lysed. Subsequently, reverse transcription (RT) occurs inside GEMs and barcoded full-length cDNA is generated. After RT, amplified cDNAs with barcode sequences (cell index and UMI) are pooled and single cell library is constructed using the Single Cell 3` Reagent Kit (v3 chemistry). The resulting library was sequenced on illumina HiseqX platform with 150bp paired end. Raw base calling files generated by illumine sequencing were demultiplexed based on the sample index read to generate FASTQ files using the 10X Genomics Cell Ranger (v3.0.2) pipeline. The raw reads were trimmed from the 3’ end to get the recommended number of cycle for read pairs (read1: 28bp; read2 : 91bp). The trimmed reads were mapped to the hg38 reference human genome with subsequent analysis, including filtering, barcode counting, and UMI counting. The resulting data were used to generate the multidimensional feature-barcode matrix using the CellRanger count with default parameters.
2020-01-03 | GSE142838 | GEO
Project description:This repository provides scRNA-seq data corresponding to the manuscript \\"Single-Cell RNA-Sequencing Reveals Placental Response under Environmental Stress\\" by Van Buren, Azzara, Rangel-Moreno, de la Luz Garcia-Hernandez, Murphy, Cohen, Lin, and Park. The repository includes both count by gene matrices output from CellRanger version 6.0.1 (file names *_filtered_feature_matrix.h5 for each of the eight samples Control_1_M, Control_1_F, Control_2_M, Control_2_F, As_1_M, As_1_F, As_2_M, As_2_F), and a finalized Seurat object including cell type assignments as used for analyses in the manuscript (file name final_Seurat_obj.RData). Accompanying code used in analysis can be found at https://github.com/edvanburen/placenta_code.
2024-07-13 | E-MTAB-14214 | 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 human primary prostate epithelial cells grown as a monolayer (2D) or as organoids (3D) were separated, collected and prepped for RNA-seq using the 10x Genomics Chromium Genome Reagent kit v2 Chemistry. 3,500-5,000 cells were collected from each sample and sequenced at a depth of ~45,000 genes per cells on a 2x150nt lane in a HiSeq 4000. CellRanger alignment was performed to produce the RAW data files.
2019-07-11 | GSE130318 | GEO