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High-throughput transcriptomics of water extracts detects reductions in biological activity with water treatment processes

GSE252117 Homo sapiens (human) RNA-seq (gene expression) 510 samples Submitted 2024/03/05 Platform GPL16791
At a glance

RNA-seq (gene expression) · human · 510 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)
Topic
Breast cancerThis series is part of our curated briefing on it.
Samples
510 samples: 397 distinct titles, 3 of them repeatedGroups 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.
Paper
High-Throughput Transcriptomics of Water Extracts Detects Reductions in Biological Activity with Water Treatment ProcessesEnvironmental science & technology · 2024
Summary (written by the submitters)
The presence of numerous chemical contaminants from industrial, agricultural, and pharmaceutical sources in water supplies poses a potential risk to human and ecological health. Current chemical analyses suffer from limitations including chemical coverage and high cost, and broad-coverage in vitro assays such as transcriptomics may further improve water quality monitoring by assessing a large range of possible effects. Here, we used high-throughput transcriptomics to assess the activity induced by field-derived water extracts in MCF7 breast carcinoma cells.
Published in
High-Throughput Transcriptomics of Water Extracts Detects Reductions in Biological Activity with Water Treatment Processes
Rogers JD, Leusch FDL, Chambers B et al. · Environmental science & technology 2024 · PMID 38235672 · doi:10.1021/acs.est.3c07525
This dataset
Open GSE252117 in finder → Find more human RNA-seq datasets → Breast cancer landscape →
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 GSE252117_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 PRJNA1057823 and SRA study SRP480322. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 38235672) ↗
Study design
397 distinct titles, 3 of them repeated
SIRO_TC00284663_G ×2 TSA_TC00284663_N ×2 SIRO_TC00284699_E ×2

How we read this: Read from the first 400 of 510 sample titles: 397 distinct titles with little repetition. 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

+ 470 more — browse all 510 samples with per-sample file links →

More Breast cancer datasets

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.