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Predicting sepsis severity at first clinical presentation: the role of endotypes and mechanistic signatures

GSE185263 Homo sapiens (human) RNA-seq (gene expression) 392 samples Submitted 2022/01/10 Platform GPL16791
At a glance

RNA-seq (gene expression) · human · 392 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
392 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)
Identifying at first clinical presentation gene expression signatures that predict subsequent severity will allow clinicians to identify the most at risk groups of patients, and also enable appropriate antibiotic use. Accordingly, we characterized the blood immune profiles of patients with early/pre-sepsis to identify signatures reflecting disease severity, organ dysfunction, mortality, and specific endotypes/mechanisms.
This dataset
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.

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 GSE185263_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA768419 and SRA study SRP339949. Searching any of these in the dataset finder brings you back here.

Samples in this study

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