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Blood gene expression changes in response to exposure to dust containing silica

GSE165489 Homo sapiens (human) RNA-seq (gene expression) 86 samples Submitted 2024/12/31 Platform GPL16791
At a glance

RNA-seq (gene expression) · human · 86 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
86 samples: 63 × TESC vs 23 × CTIGroups 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)
Occupational exposure to dust containing crystalline silica may result in serious adverse health effects including silicosis and cancer. Previous studies which employed animal models for inhalation exposure to crystalline silica revealed changes in blood gene expression profiles in association with the silica-induced lung toxicity. Currently, global gene expression profiles were determined in the whole blood samples obtained from control (not exposed to dust) and dust containing silica exposed individuals with or without clinically identified silicosis.
Read the full summary ↓
Differences in the blood gene expression profiles were detected in the blood samples obtained from the control and the silica-containing dust exposed individuals. Between the two groups of the silica-containing dust exposed individuals, the number of significantly differentially expressed genes was more in the blood samples obtained from those with silicosis.
This dataset
Open GSE165489 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 GSE165489_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 PRJNA694679 and SRA study SRP303197. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
63 × TESC vs 23 × CTI

Supports a between-group comparison across 86 samples.

How we read this: 2 replicated groups read from 86 sample titles; they account for 86 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

+ 46 more — browse all 86 samples with per-sample file links →

Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

Share this dataset

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.