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JAX Study 3- RNA-seq of male KOLF2.2J hiPSC-derived cortical brain organoids homozygous null for six different transcription factors

GSE287558 Homo sapiens (human) RNA-seq (gene expression) 174 samples Submitted 2025/02/03 Platform GPL34281
At a glance

RNA-seq (gene expression) · human · 174 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
174 samples: 174 samples, each with a distinct title — no replicated groupsGroups 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)
This study aims to phenotype iPSC-derived cortical brain organoids that contain homozygous null alleles for transcription factors expressed in the early neuroectoderm. Null alleles were generated using three distinct genetic engineering approaches: full coding region deletion (KO), critical exon deletion (CE), and insertion of a premature termination codon with frameshift (PTC+1).
Read the full summary ↓
RNA-seq data was generated at the indicated day post initiation of differentiation from hiPSCs. The study included the homozygous null alleles for the following transcription factors: LHX9, RFX4, PAX6, OTX1, LHX5, and FEZF2. This analysis provided insight into the differences between the various CRISPR-Cas9-based approaches and the impact of loss of function for these transcription factors in cortical brain organoid differentiation.
This dataset
Open GSE287558 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 GSE287558_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 PRJEB82799 and SRA study ERP166466. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
174 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 174 sample titles: 174 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

+ 134 more — browse all 174 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.