A Proteome-Wide Atlas of Drug Mechanism of Action
Ontology highlight
ABSTRACT:
INSTRUMENT(S): Orbitrap Eclipse, Orbitrap Fusion Lumos, Orbitrap Fusion
ORGANISM(S): Homo Sapiens (ncbitaxon:9606)
SUBMITTER: 
Steven Gygi
PROVIDER: MSV000089282 | MassIVE | Tue Apr 19 13:10:00 BST 2022
REPOSITORIES: MassIVE
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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
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2015-07-15 | E-PROT-3 | biostudies-arrayexpress
Project description:Background: A comprehensive transcriptome survey, or "gene atlas", provides information essential for a complete understanding of the genomic biology of an organism. We present an atlas of RNA abundance for 92 adult, juvenile and fetal cattle tissues and 3 cattle cell lines. Results: The Bovine Gene Atlas was generated from 7.2 million unique digital gene expression tag sequences (300.2 million total raw tag sequences), from which 1.59 million unique tag sequences were identified that mapped to the bovine genome accounting for 85% of the total raw tag abundance. Filtering these tags yielded 87,764 unique tag sequences that unambiguously mapped to 16,517 annotated protein-coding loci in the genome accounting for 45% of the total raw tag abundance. Clustering of tissues based on tag abundance profiles generally confirmed ontology classification based on anatomy. There were 5,429 constitutively expressed loci and 3,445 constitutively expressed unique tag sequences mapping outside annotated gene boundaries that represent a resource for enhancing current gene models. Physical measures such as inferred transcript length or antisense tag abundance identified tissues with atypical transcriptional tag profiles. We report for the first time the tissue specific variation in the proportion of mitochondrial transcriptional tag abundance. The Bovine Gene Atlas can be examined at http://www.agbase.msstate.edu/bovineatlas . Conclusions: The Bovine Gene Atlas is the deepest and broadest transcriptome survey of any livestock genome to date. Commonalities and variation in sense and antisense transcript tag profiles identified in different tissues facilitate the examination of the relationship between gene expression, tissue, and gene function. An atlas of mRNA abundance for 92 adult, juvenile and fetal cattle tissues and 3 cattle cell lines.
2010-09-28 | E-GEOD-21544 | biostudies-arrayexpress
Project description:In this study we used single cell multi-omics profiling to create an atlas of the human YS to gain insights into its haematopoietic, metabolic and nutritive functions during early embryonic development. This contains CITE-seq data (surface protein and cytosolic RNA content) data from two biological replicates. Pooled lanes were demultiplexed using SoupOrCell (for alignment and demultiplexing software and version numbers, please see accompanying manuscript and protocols within this accession). Raw count files provided are directly as output by alignment software, without any quality control applied. Quality control is described in accompanying manuscript methods. Metadata by barcode are provided as supplementary tables in accompanying manuscript.
2022-12-08 | E-MTAB-11549 | biostudies-arrayexpress
Project description:In this study we used single cell multi-omics profiling to create an atlas of the human YS to gain insights into its haematopoietic, metabolic and nutritive functions during early embryonic development. This contains fetal liver CITE-seq (surface protein and cytosolic RNA content) data from six biological replicates. Pooled lanes were demultiplexed using SoupOrCell (for alignment and demultiplexing software and version numbers, please see accompanying manuscript and protocols within this accession). Raw count files provided are directly as output by alignment software, without any quality control applied. Quality control is described in accompanying manuscript methods. Metadata by barcode are provided as supplementary tables in accompanying manuscript.
2022-12-08 | E-MTAB-11613 | biostudies-arrayexpress
Project description:In this study we used single cell multi-omics profiling to create an atlas of the human YS to gain insights into its haematopoietic, metabolic and nutritive functions during early embryonic development. This contains embryonic liver CITE-seq (surface protein and cytosolic RNA content) data from three biological replicates. Pooled lanes were demultiplexed using SoupOrCell (for alignment and demultiplexing software and version numbers, please see accompanying manuscript and protocols within this accession). Raw count files provided are directly as output by alignment software, without any quality control applied. Quality control is described in accompanying manuscript methods. Metadata by barcode are provided as supplementary tables in accompanying manuscript.
2022-12-08 | E-MTAB-11618 | biostudies-arrayexpress
Project description:Background: A comprehensive transcriptome survey, or "gene atlas", provides information essential for a complete understanding of the genomic biology of an organism. We present an atlas of RNA abundance for 92 adult, juvenile and fetal cattle tissues and 3 cattle cell lines. Results: The Bovine Gene Atlas was generated from 7.2 million unique digital gene expression tag sequences (300.2 million total raw tag sequences), from which 1.59 million unique tag sequences were identified that mapped to the bovine genome accounting for 85% of the total raw tag abundance. Filtering these tags yielded 87,764 unique tag sequences that unambiguously mapped to 16,517 annotated protein-coding loci in the genome accounting for 45% of the total raw tag abundance. Clustering of tissues based on tag abundance profiles generally confirmed ontology classification based on anatomy. There were 5,429 constitutively expressed loci and 3,445 constitutively expressed unique tag sequences mapping outside annotated gene boundaries that represent a resource for enhancing current gene models. Physical measures such as inferred transcript length or antisense tag abundance identified tissues with atypical transcriptional tag profiles. We report for the first time the tissue specific variation in the proportion of mitochondrial transcriptional tag abundance. The Bovine Gene Atlas can be examined at http://www.agbase.msstate.edu/bovineatlas . Conclusions: The Bovine Gene Atlas is the deepest and broadest transcriptome survey of any livestock genome to date. Commonalities and variation in sense and antisense transcript tag profiles identified in different tissues facilitate the examination of the relationship between gene expression, tissue, and gene function.
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Project description:During development, lymphatic vasculature forms as a second and distinct network that derives from embryonic blood vessels. Transdifferentiation of venous endothelial cells into specified lymphatic endothelial cells (LECs) is the first step in this process. Transdifferentiation and specification of LEC fate requires Prox1, but how Prox1 regulates transdifferentiation and differentiation is not fully understood. We present a single cell transcriptomic atlas of lymphangiogenesis spanning four key developmental stages that reveals new markers and functional regulators of lymphatic development. We extend this to comprehensively profile single cell transcriptomic and chromatin changes controlled by Prox1 using zygotic prox1a mutants, which form lymphatics that then dedifferentiate. Combining this with single cell analysis of Prox1-null, double prox1a/prox1b maternal zygotic mutants, we reveal in depth the role of Prox1 in control of LEC fate specification and differentiation. This resource reveals dual and progressive functions for Prox1, blocking blood vascular and hematopoietic fate while simultaneously up-regulating a small number of early acting genes that include tspan18a/b and lgals3a/b which are essential for lymphangiogenesis. This embryonic developmental resource will serve as a baseline to better understand both developmental and pathological lymphangiogenesis in the future. [Citations in sample metadata correspond to reference numbers in the associated publication.]
2023-04-27 | GSE188340 | GEO
Project description:The Ivy Glioblastoma Atlas Project (Ivy GAP) is a detailed anatomically based transcriptomic atlas of human glioblastoma tumors. As collaborators, the Ivy Foundation funded the Allen Institute and the Swedish Neuroscience Institute to design and create the atlas. The Paul G. Allen Family Foundation also supported the project. This resource consists of a viewer interface that resolves the manually- and machine-annotated histologic images (H&E and RNA in situ hybridization) at 0.5 µm/pixel, a transcriptome browser to view and mine the anatomically-based RNA-Seq samples, an application programming interface, help documentation that describes the methods and how to use the resource, as well as SNP array data and the supporting longitudinal clinical information and MRI time course data. The resource is made available to the public without charge as part of the Ivy GAP (http://glioblastoma.alleninstitute.org/) via the Allen Institute data portal (http://www.brain-map.org), the Ivy GAP Clinical and Genomic Database (http://ivygap.org/) via the Swedish Neuroscience Institute (http://www.swedish.org/services/neuroscience-institute), and The Cancer Imaging Archive (https://wiki.cancerimagingarchive.net/display/Public/Ivy+GAP). The Ivy GAP processed data at GEO includes normalized RNA-Seq FPKM files used for analysis in "An anatomic transcriptional atlas of glioblastoma,” which is under review. Other processed data files as well as sample and donor meta-data and QC metrics are available at http://glioblastoma.alleninstitute.org/static/download.html. The raw RNA-Seq and SNP array data will be submitted to dbGaP.
2017-12-01 | GSE107558 | GEO