Omics · dataset · 2023
Data and R Scripts for: "Transcriptome network analysis implicates CX3CR1-positive type 3 dendritic cells in non-infectious uveitis"
Listed in IISH Dataverse
Description
This dataset contains the processed RNA sequencing data of purified CD1c-positive conventional type 2 dendritic cells (CD1c+ cDC2s), functional enrichment analysis, manual and automatic gating data of (i.e., flowSOM) flow cytometry, and multiplex cytokine analyses as outlined in Hiddingh et al. 2022 "Transcriptome network analysis implicates CX3CR1-positive type 3 dendritic cells in non-infectious uveitis see preprint on BioRxiv Data are from two cohorts (cohort I, n=36, and cohort II, n=42) of in total 51 patients with non-infectious uveitis (HLA-B27-positive acute anterior uveitis, idiopathic intermediate uveitis, HLA-A29-positive Birdshot Uveitis (Birdshot chorioretinopathy), and 27 sex/age-matched healthy controls without ocular inflammatory disease).
All raw sequencing data are available at NCBI SRA under the accession number: GSE195501 (FACS-sorted cohort I). GSE194060 (MACS-sorted cohort II). This dataverseNL dataset contains additional raw, processed, and metadata (see readme file and reproducible R notebooks (R script and Image) used for the analysis in the manuscript: R scripts (markdown + R image) with step-by-step analyses Figure_1.rmd (see "Figure_1.html") Figure_2.rmd (see "Figure_2.html") Figure_3.rmd (see "Figure_3.html") Figure_4.rmd (see "Figure_4.html") Figure_5.rmd(see "Figure_5.html") Processed RNA seq data (including WGCNA) (see folder Uveitis_mDC in files) Experimental data Manual gating data of MACS-sorted fractions cohort I (see here) Manual gating data for CD1c+ cDC2 subsets in PBMCs (see here) Manual gating CD14+ and CD14- CD1c+ cDC2 fractions from Buffy (see here) qPCR data for CX3CR1,CCR5,CCR2,IRF8,TLR7,RUNX3 and CD36 in sorted CD14+ and CD14- CD1c+ DCs (see here) qPCR data (fold change compared to medium) for RUNX3 and CD36 in overnight stimulated cDC2 cultures (see here) Cell phenotypes identified by flowSOM (7x7 grid) using the cDC2-subset flow cytometry panel (see here) IL-23 ELISA concentration in supernatant of overnight LTA-stimulated cDC2 subset cultures (see here) Luminex Multiplex Cytokine analysis of supernatant of overnight LTA-stimulated cDC2 subset cultures (see here) Other transcriptomic data used in the R scripts (above) WT Untreated cDC2 versus cDC2 from Runx3-11cKO miceGSE48590 generated by Dicken et al., PLoS One 2013 WT Untreated cDC2 versus cDC2 from Notch2-11cKO miceGSE119242 generated by Briseño et al., Proc Natl Acad Sci U S A 2018 Sorted CD14+CD5-CD163+ and CD14-CD5-CD163+ cDC2s from SLE and Scleroderma patients GSE136731 generated by Dutertre et al., Immunity 2019 Single-cell RNA-seq of aqueous humor from 4 HLA-B27-positive uveitis patients and control GSE178833 generated by Kasper et al., Elife 2021 Inflammatory [inf-]cDC2sGSE149619 generated by Bosteels et al., Immunity 2020 RNA-seq data from cDC2s generated from murine bone marrow cells in co-culture with stromal OP-9 cell line transduced with or without expression of the Notch ligand Delta-like 1GSE110577 generated by Kirkling et al., Cell Rep 2018
Links
Where it is published
- Dataverse dataset page dataverse.nl/dataset.xhtml?persistentId=doi%3A10.34894%2F9Q0FVO ↗
landing page · from datasets iisg amsterdam
- DOI doi.org/10.34894/9q0fvo ↗
DOI / persistent id · from datasets iisg amsterdam
Catalogue records · 1
- Dataverse API dataverse.nl/api/datasets/:persistentId/?persistentId=doi%3A10.34894%2F9Q0F… ↗
metadata API · from datasets iisg amsterdam
Topics
- Stated by source
- Medicine, Health and Life Sciences
- From keywords
- Life Sciences · Medicine & Health · RNA sequencing
- Inferred from text
- Disease 75% · Image 75% · Immunology 71% · Sequencing 75% · Single-cell RNA sequencing 65%
Provenance · 1 source records, 15 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| IISH Dataverse | doi:10.34894/9Q0FVO | 13 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| concepts[disease].local:disease:disease | enrichment · datasets iisg amsterdam | keyword-concept-rules@1.0.0 | title+description (75%) |
| concepts[field].anzsrc:group:3204 | enrichment · datasets iisg amsterdam | taxonomy-embedding@1.1.0 | title+keywords+description (71%) |
| concepts[field].dataverse_subject:medicine-health-and-life-sciences | source · datasets iisg amsterdam | connector:datasets_iisg_amsterdam@1.0.0 | /subjects |
| concepts[field].local:field:life-sciences | mapping · datasets iisg amsterdam | connector:datasets_iisg_amsterdam@1.0.0 | /subjects |
| concepts[field].local:field:medicine-health | mapping · datasets iisg amsterdam | connector:datasets_iisg_amsterdam@1.0.0 | /subjects |
| concepts[modality].local:modality:image | enrichment · datasets iisg amsterdam | keyword-concept-rules@1.0.0 | title+description (75%) |
| concepts[modality].local:modality:rna-seq | mapping · datasets iisg amsterdam | vocabulary-mapper@1.0.0 | keywords['RNA-sequencing'] |
| concepts[modality].local:modality:sequencing | enrichment · datasets iisg amsterdam | keyword-concept-rules@1.0.0 | title+description (75%) |
| concepts[modality].local:modality:single-cell-rna-seq | enrichment · datasets iisg amsterdam | keyword-concept-rules@1.0.0 | title+description (65%) |
| created_date | source · datasets iisg amsterdam | connector:datasets_iisg_amsterdam@1.0.0 | |
| description | source · datasets iisg amsterdam | connector:datasets_iisg_amsterdam@1.0.0 | /description |
| publication_date | source · datasets iisg amsterdam | connector:datasets_iisg_amsterdam@1.0.0 | |
| title | source · datasets iisg amsterdam | connector:datasets_iisg_amsterdam@1.0.0 | /name |
| updated_date | source · datasets iisg amsterdam | connector:datasets_iisg_amsterdam@1.0.0 | |
| version_label | source · datasets iisg amsterdam | connector:datasets_iisg_amsterdam@1.0.0 |