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Comparative gene expression in healthy African American and White Non-Hispanic skin

GSE267066 Homo sapiens (human) RNA-seq (gene expression) 11 samples Submitted 2024/12/31 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 11 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
11 samples: 6 × Skin biopsy from WNH female vs 5 × Skin biopsy from AA femaleGroups are read from the sample names, not from the paper. Check the list below.
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 risk of atopic dermatitis, hidradenitis suppurativa, lupus erythematosus is significantly higher in African Americans (AA), while White Non-Hispanic (WNH) subjects have a greater risk of psoriasis. The mechanisms underlying disparity in inflammatory skin diseases risks are poorly understood, and the molecular landscape of skin of color including transcriptome and proteome are not well known.
Read the full summary ↓
To assess whether and how gene expression pattern in normal skin may affect predisposition to specific skin inflammatory diseases, we performed analkysis of gene expression in full thickness skin biopsies obtained from healthy African American and White Non-Hispanic volunteers (all females, aged 22-46).
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 GSE267066_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 PRJNA1109430 and SRA study SRP506610. Searching any of these in the dataset finder brings you back here.

Study design
6 × Skin biopsy from WNH female vs 5 × Skin biopsy from AA female

Supports a between-group comparison across 11 samples.

How we read this: 2 replicated groups read from 11 sample titles; they account for 11 of them. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.

Samples in this study
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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.