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Identification of skewed X chromosome inactivation using exome and transcriptome sequencing in patients with suspected rare genetic disease

GSE234607 Homo sapiens (human) RNA-seq (gene expression) 112 samples Submitted 2024/04/24 Platform GPL20301
At a glance

RNA-seq (gene expression) · human · 112 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
112 samples
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
Identification of skewed X chromosome inactivation using exome and transcriptome sequencing in patients with suspected rare genetic diseaseBMC genomics · 2024
Summary (written by the submitters)
Purpose: Evaluation of XCI status in a cohot of female patients with suspected rare genetic diseases using exome and RNA sequencing Results: We developed a method for estimating X inactivation status, using exome and transcriptome sequencing data from 112 female samples. We built a reference model for evaluation of XCI in 135 females from the GTEx consortium.
Read the full summary ↓
We tested and validated the model on 14 female individuals with different types of undiagnosed rare genetic disorders who were clinically tested for X-skew using the AR gene assay and compared results to our outlier-based analysis technique. In comparison to the AR clinical test for identification of X inactivation, our method was concordant with AR method in 9 samples, discordant in 3, and provided measures of X inactivation in 2 samples with uninformative clinical results. We applied this method on an additional 98 females presenting to the clinic with phenotypes consistent with different hereditary disorders without a known genetic diagnosis. Here we show the use of transcriptome sequencing data to provide an accurate and complete estimation of X-inactivation and skew status in female patients.
Published in
Identification of skewed X chromosome inactivation using exome and transcriptome sequencing in patients with suspected rare genetic disease
Fadra N, Schultz-Rogers LE, Chanana P et al. · BMC genomics 2024 · PMID 38627676 · doi:10.1186/s12864-024-10240-2
This dataset
Open GSE234607 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 GSE234607_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 PRJNA982123 and SRA study SRP442498. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 38627676) ↗
Study design
A cohort of 112 individual samples

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

How we read this: Sample titles run Sample_1 … Sample_112 and carry no group information.

Samples in this study

+ 72 more — browse all 112 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.