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Multiomic Profile Integration Reveals Early Signatures of Amyotrophic Lateral Sclerosis and Suggests the MAPK Pathway as a Therapeutic Target [RNA-Seq]

GSE234245 Mus musculus (mouse) RNA-seq (gene expression) 79 samples Submitted 2024/04/22 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 79 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
Mus musculus (mouse)
Samples
79 samples: 19 conditions, mostly with about 5 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
A dataset profiling the multiomic landscape of the prefrontal cortex in amyotrophic lateral sclerosisGigaScience · 2024
Summary (written by the submitters)
The study conducted a multiomic analysis of the prefrontal cortex from 51 sporadic ALS patients and 50 control subjects, as well as four transgenic mouse models ( C9orf72, SOD1, TDP-43 and FUS) of ALS with each 5 males/females and 5 case/control samples. The analysis identified sex-specific differences in early disease mechanisms.
Published in
A dataset profiling the multiomic landscape of the prefrontal cortex in amyotrophic lateral sclerosis
Hausmann F, Caldi Gomes L, Hänzelmann S et al. · GigaScience 2024 · PMID 39693632 · doi:10.1093/gigascience/giae100
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 GSE234245_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 PRJNA980618 and SRA study SRP441344. Searching any of these in the dataset finder brings you back here.

Study design
19 conditions, mostly with about 5 replicates each
SOD1,ctrl,male,S ×6 FUS,mut,female,S ×5 FUS,mut,male,S ×5 FUS,ctrl,female,S ×5 TDP43,ctrl,male,S ×5 TDP43,ctrl,female,S ×5 TDP43,mut,female,S ×5 TDP43,mut,male,S ×5 +17 more

Supports a between-group comparison across 73 samples.

How we read this: 19 replicated groups read from 79 sample titles; they account for 73 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

+ 39 more — browse all 79 samples with per-sample file links →

Datasets on a similar topic

Search all mouse 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.