Single-cell transcriptomics revealed molecular vulnerability in a human midbrain-like organoid model of Parkinson's Disease [scRNA-Seq]
Single-cell RNA-seq · human · 15 samples
- What it is
- Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
- Organism
- Homo sapiens (human)
- Samples
- 15 samples: 5 × MLO_WT_batch1_manual vs 4 × MLO_WT_batch2_manual vs 4 × MLO_DJ1KO_batch2_manualGroups 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.
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 GSE271116_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 PRJNA1129998 and SRA study SRP517079. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 13 samples.
How we read this: 3 replicated groups read from 15 sample titles; they account for 13 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.
- GSM8370026 MLO_WT_batch1_manual_60 MLO_WT_batch1_manual
- GSM8370027 MLO_WT_manual_batch1_105
- GSM8370028 MLO_WT_batch1_manual_99 MLO_WT_batch1_manual
- GSM8370029 MLO_WT_batch1_manual_126 MLO_WT_batch1_manual
- GSM8370030 MLO_WT_batch1_manual_120 MLO_WT_batch1_manual
- GSM8370031 MLO_WT_batch1_robot_126
- GSM8370032 MLO_WT_batch1_manual_156 MLO_WT_batch1_manual
- GSM8370033 MLO_WT_batch2_manual_70 MLO_WT_batch2_manual
- GSM8370034 MLO_DJ1KO_batch2_manual_70 MLO_DJ1KO_batch2_manual
- GSM8370035 MLO_WT_batch2_manual_90 MLO_WT_batch2_manual
- GSM8370036 MLO_DJ1KO_batch2_manual_90 MLO_DJ1KO_batch2_manual
- GSM8370037 MLO_WT_batch2_manual_120 MLO_WT_batch2_manual
- GSM8370038 MLO_DJ1KO_batch2_manual_120 MLO_DJ1KO_batch2_manual
- GSM8370039 MLO_WT_batch2_manual_150 MLO_WT_batch2_manual
- GSM8370040 MLO_DJ1KO_batch2_manual_150 MLO_DJ1KO_batch2_manual
- GSE337246 Integrated single-cell profiling of RNA and DNA interactomes reveals targetable chromatin architectures in cancer [scRNA-Seq organoids] 35 samples shares single-cell, scrna-seq, organoid
- GSE294300 Single-cell gene expression profiles of cells from primary colorectal cancer and adjacent normal tissue [scRNA-Seq] 36 samples shares single-cell, scrna-seq
- GSE278688 Integrated Single-Cell and Spatial Transcriptomics Uncover Distinct Cellular Subtypes Involved in Neural Invasion in PDAC [scRNA-Seq] 29 samples shares single-cell, scrna-seq
- GSE294559 Single-cell multi-omics characterize colorectal tumors, adjacent healthy tissue and matched organoids identifying CRC-unique features 72 samples shares single-cell, organoid
- GSE282122 A longitudinal single-cell atlas of anti-tumour necrosis factor treatment in inflammatory bowel disease 216 samples shares single-cell
- GSE220774 Side- and disease-dependent changes in human aortic valve cell population and transcriptomic heterogeneity determined by single-cell RNA sequencing 15 samples shares single-cell
- GSE285196 Pathogenesis of Graves' Disease Using Single-Cell Sequencing with Thyroid Autoantigens Peptides Stimulation in B Cells 10 samples shares single-cell
- GSE228033 A single-cell atlas revealing cellular heterogeneity across healthy and diseased human thymus 10 samples shares single-cell
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.