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Systems biological assessment of immunity to severe and mild COVID-19 infections

GSE152418 Homo sapiens (human) RNA-seq (gene expression) 34 samples Submitted 2020/07/31 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 34 samples

What it is
RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
Organism
Homo sapiens (human)
Samples
34 samples
Data you can get
A processed table (series matrix) and supplementary files from NCBI; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.
Summary (written by the submitters)
The recent emergence of COVID-19 presents a major global crisis. Profound knowledge gaps remain about the interaction between the virus and the immune system. Here, we used a systems biology approach to analyze immune responses in 76 COVID-19 patients and 69 age and sex- matched controls, from Hong Kong and Atlanta. Mass cytometry revealed prolonged plasmablast and effector T cell responses, reduced myeloid expression of HLA-DR and inhibition of mTOR signaling in plasmacytoid DCs (pDCs) during infection.
Read the full summary ↓
Production of pro-inflammatory cytokines plasma levels of inflammatory mediators, including EN-RAGE, TNFSF14, and Oncostatin-M, which correlated with disease severity, and increased bacterial DNA and endotoxin in plasma in and reduced HLA-DR and CD86 but enhanced EN-RAGE expression in myeloid cells in severe transient expression of IFN stimulated genes in moderate infections, consistent with transcriptomic analysis of bulk PBMCs, that correlated with transient and low levels of plasma COVID-19.
This dataset
Open GSE152418 in finder → Find more human RNA-seq datasets →
Download · which file do I need?

Direct links to NCBI and ENA, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.

1 · Just have a look

Processed table

The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.

Series matrix ↓
2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE152418_RAW.tar (it can run to tens of gigabytes).

All supplementary files ↗ Whole study · RAW.tar ↓
3 · Start from the raw reads

Raw sequencing reads

The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.

Raw reads on ENA ↗

What the files usually look like: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.

Also filed as BioProject PRJNA639275 and SRA study SRP267176. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 32788292) ↗
Samples in this study

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+ 34 more — browse all 34 samples with per-sample file links →

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Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.