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Kabuki syndrome type I fibroblast multi-omics dataset: bulk RNA-seq profiles from primary skin fibroblasts

GSE330762 Homo sapiens (human) RNA-seq (gene expression) 19 samples Submitted 2026/07/12 Platform GPL21697
At a glance

RNA-seq (gene expression) · human · 19 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
19 samples: 16 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.
Summary (written by the submitters)
Kabuki syndrome type 1 (KS1) is a rare congenital disorder caused by heterozygous loss-of-function mutations in KMT2D – an H3K4 histone methyltransferase. While KMT2D function during early development is increasingly understood, the transcriptional and chromatin accessibility consequences of its loss in differentiated somatic tissues remain poorly characterized.
Read the full summary ↓
We present a multi-omic dataset from primary dermal fibroblasts of seven individuals with KS type I and nine unaffected donors. The dataset comprises bulk RNA-seq from sixteen donors (nineteen libraries across two sequencing batches, including three donors sequenced in both batches to assess technical replicability) and ATAC-seq from ten donors (six KS, four controls). All libraries were processed through standardized nf-core pipelines, with differential analyses performed using DESeq2 with RUVSeq batch correction. This resource is intended to facilitate research on Kabuki syndrome type 1 and by expanding the available models for studying the group of mendelian disorders known as chromatinopathies.
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 GSE330762_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 PRJNA1465389 and SRA study SRP699809. Searching any of these in the dataset finder brings you back here.

Study design
16 distinct titles, 3 of them repeated
GDB339 control female ×2 GDB380 Kabuki syndrome male ×2 GDB447 Kabuki syndrome male ×2

How we read this: Read from 19 sample titles: 16 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
Datasets on a similar topic

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