Phenotypic complexities of rare heterozygous neurexin-1 deletions
RNA-seq (gene expression) · human · 10 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
- 10 samples: 10 samples, each with a distinct title — no replicated groupsGroups 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
- Phenotypic complexities of rare heterozygous neurexin-1 deletionsNature · 2025
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 GSE288964_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 PRJNA1220127 and SRA study SRP562084. Searching any of these in the dataset finder brings you back here.
Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.
How we read this: Read from 10 sample titles: 10 distinct titles with little repetition. 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.
- GSM8779930 2607-hCS-6mo
- GSM8779931 2607-hSS-6mo
- GSM8779932 581-hCS-6mo
- GSM8779933 581-hSS-6mo
- GSM8779934 641-hCS-6mo
- GSM8779935 641-hSS-6mo
- GSM8779936 972-hCS-6mo
- GSM8779937 972-hSS-6mo
- GSM8779938 973-hCS-6mo
- GSM8779939 973-hSS-6mo
- GSE288881 Phenotypic complexities of rare heterozygous neurexin-1 deletions [shNEG_ASO_rnaseq] 54 samples shares neurexin-1, complexities, heterozygous, phenotypic, deletions, rare
- GSE288880 Phenotypic complexities of rare heterozygous neurexin-1 deletions [nrxn1_bulk_rnaseq] 53 samples shares neurexin-1, complexities, heterozygous, phenotypic, deletions, rare
- GSE291060 Dynamic modelling of EWS::FLI1 fluctuations reveals molecular determinants of phenotypic tumor plasticity and prognosis in Ewing sarcoma [RNA-seq] 164 samples shares phenotypic
- GSE273114 Phenotypic and transcriptomic characterisation of the human B cell response to a novel Ebola vaccine regimen (Ad26.ZEBOV, MVA-BN-Filo) 126 samples shares phenotypic
- GSE289466 Intraindividual epigenetic heterogeneity underlying phenotypic subtypes of advanced prostate cancer [RNA-seq] 98 samples shares phenotypic
- GSE297342 Assessing the Effects of Silver Nanoparticles on ARPE-19 Cells via High-Throughput Phenotypic Profiling with the Cell Painting Assay. 88 samples shares phenotypic
- GSE233236 Pan-Cancer Single-Cell Dissection Reveals Phenotypically Distinct B Cell Subtypes 78 samples shares phenotypic
- GSE267243 Scalable, compressed phenotypic screening using pooled perturbations (PDAC screens) 54 samples shares phenotypic
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.