A human neural crest model reveals the developmental impact of neuroblastoma-associated chromosomal aberrations [10x scRNA-seq]
Single-cell RNA-seq · human · 38 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
- 38 samples: 26 × GEX vs 12 × BCGroups 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 human neural crest model reveals the developmental impact of neuroblastoma-associated chromosomal aberrationsNature communications · 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 GSE221853_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 PRJNA916500 and SRA study SRP415300. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 38 samples.
How we read this: 2 replicated groups read from 38 sample titles; they account for 38 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.
- GSM6900802 GEX1 GEX
- GSM6900803 GEX3 GEX
- GSM6900804 GEX4 GEX
- GSM6900805 GEX5 GEX
- GSM6900806 GEX6 GEX
- GSM6900807 GEX7 GEX
- GSM6900808 GEX8 GEX
- GSM6900809 GEX9 GEX
- GSM6900810 GEX10 GEX
- GSM6900811 GEX11 GEX
- GSM6900812 GEX12 GEX
- GSM6900813 GEX13 GEX
- GSM6900814 BC1 BC
- GSM6900815 BC3 BC
- GSM6900816 BC4 BC
- GSM6900817 BC5 BC
- GSM6900818 BC6 BC
- GSM6900819 BC7 BC
- GSM6900820 BC8 BC
- GSM6900821 BC9 BC
- GSM6900822 BC10 BC
- GSM6900823 BC11 BC
- GSM6900824 BC12 BC
- GSM6900825 BC13 BC
- GSM8112107 GEX14 GEX
- GSM8112109 GEX15 GEX
- GSM8112111 GEX16 GEX
- GSM8112113 GEX17 GEX
- GSM8112115 GEX18 GEX
- GSM8112117 GEX19 GEX
- GSM8112119 GEX20 GEX
- GSM8112121 GEX21 GEX
- GSM8112122 GEX22 GEX
- GSM8112124 GEX23 GEX
- GSM8112126 GEX24 GEX
- GSM8112128 GEX25 GEX
- GSM8112130 GEX26 GEX
- GSM8112132 GEX27 GEX
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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.