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Gene expression analysis of hESCs undergoing neuronal differentiation exposed to citalopram

GSE260888 Homo sapiens (human) RNA-seq (gene expression) 89 samples Submitted 2024/07/01 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 89 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
89 samples: 16 conditions, mostly with about 6 replicates eachGroups 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
Citalopram exposure of hESCs during neuronal differentiation identifies dysregulated genes involved in neurodevelopment and depressionFrontiers in cell and developmental biology · 2024
Summary (written by the submitters)
Genome-wide gene expression profiling of human embryonic stem cells (hESCs) undergoing neuronal differentiation at four distinct time-points. hESCs are differentiated towards neuronal cells for 13 days, and sampled for downstream analysis at day 0, 6, 10 and 13 . Cells exposed to 50, 100, 200 and 400 nM citalopram from Day 1 were charachterised at Day 6, 10 and 13.
Published in
Citalopram exposure of hESCs during neuronal differentiation identifies dysregulated genes involved in neurodevelopment and depression
Spildrejorde M, Leithaug M, Samara A et al. · Frontiers in cell and developmental biology 2024 · PMID 39055655 · doi:10.3389/fcell.2024.1428538
This dataset
Open GSE260888 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 GSE260888_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 PRJNA1083921. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39055655) ↗
Study design
16 conditions, mostly with about 6 replicates each
HS360-Day10-RNA-seq ×6 HS360-Day10-CIT50-RNA-seq ×6 HS360-Day10-CIT400-RNA-seq ×6 HS360-Day13-RNA-seq ×6 HS360-Day13-CIT50-RNA-seq ×6 HS360-Day13-CIT400-RNA-seq ×6 HS360-Day6-RNA-seq ×6 HS360-Day6-CIT50-RNA-seq ×6 +8 more

Supports a between-group comparison across 89 samples.

How we read this: 16 replicated groups read from 89 sample titles; they account for 89 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

+ 49 more — browse all 89 samples with per-sample file links →

Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

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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.