single nucleous RNAseq data from brain tissue provided from patients undergoing neurosurgery
Single-nucleus RNA-seq · human · 18 samples
- What it is
- Single-nucleus RNA-seqGene activity measured in individual nuclei (used when whole cells are hard to isolate, for example from frozen tissue). Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
- Organism
- Homo sapiens (human)
- Samples
- 18 samples: 9 × non-POD vs 9 × PODGroups 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.
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 GSE291019_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.
Also filed as BioProject PRJNA1231406 and SRA study SRP567822. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 18 samples.
How we read this: 2 replicated groups read from 18 sample titles; they account for 18 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.
- GSM8827637 non-POD1 non-POD
- GSM8827638 non-POD2 non-POD
- GSM8827639 non-POD3 non-POD
- GSM8827640 non-POD4 non-POD
- GSM8827641 non-POD5 non-POD
- GSM8827642 non-POD6 non-POD
- GSM8827643 non-POD7 non-POD
- GSM8827644 non-POD8 non-POD
- GSM8827645 non-POD9 non-POD
- GSM8827646 POD1 POD
- GSM8827647 POD2 POD
- GSM8827648 POD3 POD
- GSM8827649 POD4 POD
- GSM8827650 POD5 POD
- GSM8827651 POD6 POD
- GSM8827652 POD7 POD
- GSM8827653 POD8 POD
- GSM8827654 POD9 POD
- GSE328351 Bulk RNA-seq of dorsolateral prefrontal cortex tissue collected during deep brain stimulation neurosurgery in obsessive-compulsive disorder and neurological controls 10 samples shares neurosurgery, brain
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- GSE253173 Coupling of response biomarkers between tumour and peripheral blood in patients undergoing chemoimmunotherapy II 100 samples shares undergoing
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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.