Project description:Observational, Multicenter, Post-market, Minimal risk, Prospective data collection of PillCam SB3 videos (including PillCam reports) and raw data files and optional collection of Eneteroscopy reports
Project description:Single-cell RNA-seq libraries were generated from human PBMCs that were incubated with anti-HER2/CD3 TDB in the presence of KPL-4 cells. This dataset only contains the metadata and processed data. Raw data can be accessed via the EGA accession EGAS00001003734
Project description:A novel one-dimensional on-line pH gradient-eluted strong cation exchange (SCX)-nano-ESI-MS/MS method was developed for protein identification and tested with mixture of six standard proteins, total lysate of HuH7 and N2a cells, as well as membrane fraction of N2a cells. This method utilized an on-line nano-flow SCX column in a nano-LC system coupled with a nano-electrospray high-resolution mass spectrometer. Protein digests were separated on a nano-flow SCX column with a pH gradient and directly introduced into a mass spectrometer through nano-electrospray ionization. SCXLC-MS/MS showed identification capability for higher proportion of basic peptides compared to RPLC-MS/MS method, especially for histidine-containing peptides. Our SCXLC-MS/MS method is an excellent alternative method to the RPLC-MS/MS method for analysis of standard proteins, total cell and membrane proteomes.
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
Project description:RAW-Rv3722c and RAW-Vector cells were collected for RNA extraction and subject to transcriptome sequencing. Expression levels of all genes in the two cell lines were determined by Next Generation Sequencing (NGS)
Project description:Single D11 cells were identified in 16-cell embryos of Xenopus laevis. Metabolites were extracted, and the extracts were analyzed using a custom-built capillary electrophoresis electrospray ionization platform coupled to a quadrupole time-of-flight mass spectrometer. The resulting metadata was analyzed by Trace, a custom-design software, designed to extract molecular feautres from trace-sensitive metabolomics experiments. The results were validated against molecular features that were extracted by manual curation of the same raw mass spectrometer files.
Project description:Raw data for Metabolomics Studies of Cell-Cell Interactions using Single Cell Mass Spectrometry Combined with Fluorescence Microscopy
Project description:RawTools is a software that provides parsing and quantification of raw Thermo Orbitrap mass spectrometer data. RawTools software was used to process a subset of injections (n = 10) from a prepared HeLa digest that were analyzed on an Orbitrap Velos to get instrument performance metrics.
Project description:RawTools is a software that provides parsing and quantification of raw Thermo Orbitrap mass spectrometer data. RawTools software was used to process a set of injections (n = 140) from a prepared HeLa digest that were analyzed on an Orbitrap Velos to get summarized instrument performance metrics for quality control.