Whole blood transcriptome profile identifies motor neurone disease (MND) RNA biomarker signatures
RNA-seq (gene expression) · human · 84 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
- 84 samples: 42 × ALS vs 42 × KTGroups 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
- Whole blood transcriptome profile identifies motor neurone disease RNA biomarker signaturesExperimental biology and medicine (Maywood, N.J.) · 2024
Read the full summary ↓
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.
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.
Supplementary files
The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE277709_RAW.tar (it can run to tens of gigabytes).
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 PRJNA1163403 and SRA study SRP533919. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 84 samples.
How we read this: 2 replicated groups read from 84 sample titles; they account for 84 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.
- GSM8528155 ALS-1 ALS
- GSM8528156 ALS-2 ALS
- GSM8528157 ALS-5 ALS
- GSM8528158 ALS-7 ALS
- GSM8528159 ALS-11 ALS
- GSM8528160 ALS-12 ALS
- GSM8528161 ALS-15 ALS
- GSM8528162 ALS-16 ALS
- GSM8528163 ALS-18 ALS
- GSM8528164 ALS-19 ALS
- GSM8528165 ALS-20 ALS
- GSM8528166 ALS-22 ALS
- GSM8528167 ALS-23 ALS
- GSM8528168 ALS-24 ALS
- GSM8528169 ALS-25 ALS
- GSM8528170 ALS-26 ALS
- GSM8528171 ALS-28 ALS
- GSM8528172 ALS-32 ALS
- GSM8528173 ALS-33 ALS
- GSM8528174 ALS-34 ALS
- GSM8528175 ALS-35 ALS
- GSM8528176 ALS-39 ALS
- GSM8528177 ALS-41 ALS
- GSM8528178 ALS-42 ALS
- GSM8528179 ALS-43 ALS
- GSM8528180 ALS-44 ALS
- GSM8528181 ALS-45 ALS
- GSM8528182 ALS-46 ALS
- GSM8528183 ALS-49 ALS
- GSM8528184 ALS-51 ALS
- GSM8528185 ALS-52 ALS
- GSM8528186 ALS-53 ALS
- GSM8528187 ALS-54 ALS
- GSM8528188 ALS-55 ALS
- GSM8528189 ALS-56 ALS
- GSM8528190 ALS-57 ALS
- GSM8528191 ALS-58 ALS
- GSM8528192 ALS-59 ALS
- GSM8528193 ALS-60 ALS
- GSM8528194 ALS-61 ALS
+ 44 more — browse all 84 samples with per-sample file links →
- GSE251778 Sex-specific and multiomic integration enhance accuracy of peripheral blood biomarkers of major depressive disorder [RNA-Seq] 169 samples shares biomarker, blood
- GSE318816 Blood-based Molecular Endotyping of Fibrotic Hypersensitivity Pneumonitis Identifies Two Immune Subtypes with Divergent Clinical Outcomes 126 samples shares identifies, blood
- GSE253173 Coupling of response biomarkers between tumour and peripheral blood in patients undergoing chemoimmunotherapy II 100 samples shares biomarker, blood
- GSE291471 Integrative blood profiling uncovers inflammatory network signatures in high-altitude pulmonary edema 83 samples shares signatures, blood
- GSE339456 Integrated bulk and spatial transcriptomic analysis identifies progression-associated molecular signatures in biopsy-proven hypertensive nephropathy [RNA-seq] 35 samples shares identifies, signatures
- GSE338165 Single-cell analysis identifies monocyte signatures of disease activity and clinical subtypes in Behçet’s disease 22 samples shares identifies, signatures
- GSE309430 Blood-Based Gene Signatures Associated with Therapeutic Response to Anti-TNF Therapy in Rheumatoid Arthritis: A Combined Meta-Analytical and Machine Learning Approach 8 samples shares signatures, blood
- GSE270387 Single cell profiling of peripheral blood mononuclear cells in diverse men with prostate cancer reveals lethal disease-associated immune signatures 165 samples shares signatures, blood
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.