Neurodevelopmental disorder genes
RNA-seq (gene expression) · human · 60 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
- 60 samples: 17 conditions, mostly in triplicateGroups 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 GSE327685_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 PRJNA1451859 and SRA study SRP676299. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 59 samples.
How we read this: 17 replicated groups read from 60 sample titles; they account for 59 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.
- GSM9510606 NPC__3182_mRNA_R1 NPC__3182_mRNA
- GSM9510607 NPC__3182_mRNA_R2 NPC__3182_mRNA
- GSM9510608 NPC__3182_mRNA_R3 NPC__3182_mRNA
- GSM9510609 NPC__3182_mRNA_R4 NPC__3182_mRNA
- GSM9510610 iGLUTs_D7_3182_mRNA_R1 iGLUTs_D7_3182_mRNA
- GSM9510611 iGLUTs_D7_3182_mRNA_R2 iGLUTs_D7_3182_mRNA
- GSM9510612 iGLUTs_D7_3182_mRNA_R3 iGLUTs_D7_3182_mRNA
- GSM9510613 iGLUTs_D7_3182_mRNA_R4 iGLUTs_D7_3182_mRNA
- GSM9510614 iGABAs_D36_553_mRNA_R1 iGABAs_D36_553_mRNA
- GSM9510615 iGABAs_D36_553_mRNA_R2 iGABAs_D36_553_mRNA
- GSM9510616 iGABAs_D36_553_mRNA_R3 iGABAs_D36_553_mRNA
- GSM9510617 iGABAs_D36_553_mRNA_R4 iGABAs_D36_553_mRNA
- GSM9510618 iGLUTs_D21_3182_mRNA_R1 iGLUTs_D21_3182_mRNA
- GSM9510619 iGLUTs_D21_3182_mRNA_R2 iGLUTs_D21_3182_mRNA
- GSM9510620 iGLUTs_D21_3182_mRNA_R3 iGLUTs_D21_3182_mRNA
- GSM9510621 iGLUTs_D21_3182_mRNA_R4 iGLUTs_D21_3182_mRNA
- GSM9510622 NPC__3182_gRNA_R1 NPC__3182_gRNA
- GSM9510623 NPC__3182_gRNA_R2 NPC__3182_gRNA
- GSM9510624 NPC__3182_gRNA_R3 NPC__3182_gRNA
- GSM9510625 NPC__3182_gRNA_R4 NPC__3182_gRNA
- GSM9510626 iGLUTs_D7_3182_gRNA_R1 iGLUTs_D7_3182_gRNA
- GSM9510627 iGLUTs_D7_3182_gRNA_R2 iGLUTs_D7_3182_gRNA
- GSM9510628 iGLUTs_D7_3182_gRNA_R3 iGLUTs_D7_3182_gRNA
- GSM9510629 iGLUTs_D7_3182_gRNA_R4 iGLUTs_D7_3182_gRNA
- GSM9510630 iGABAs_D36_553_gRNA_R1 iGABAs_D36_553_gRNA
- GSM9510631 iGABAs_D36_553_gRNA_R2 iGABAs_D36_553_gRNA
- GSM9510632 iGABAs_D36_553_gRNA_R3 iGABAs_D36_553_gRNA
- GSM9510633 iGABAs_D36_553_gRNA_R4 iGABAs_D36_553_gRNA
- GSM9510634 iGLUTs_D21_3182_gRNA_R1 iGLUTs_D21_3182_gRNA
- GSM9510635 iGLUTs_D21_3182_gRNA_R2 iGLUTs_D21_3182_gRNA
- GSM9510636 iGLUTs_D21_3182_gRNA_R3 iGLUTs_D21_3182_gRNA
- GSM9510637 iGLUTs_D21_3182_gRNA_R4 iGLUTs_D21_3182_gRNA
- GSM9663163 D0_WT_R1 D0_WT
- GSM9663164 D0_WT_R2 D0_WT
- GSM9663165 D0_WT_R3 D0_WT
- GSM9663166 Day77_KO_R1 Day77_KO
- GSM9663167 Day77_KO_R2 Day77_KO
- GSM9663168 Day77_KO_R3 Day77_KO
- GSM9663169 Day77_WT_R1 Day77_WT
- GSM9663170 Day77_WT_R2 Day77_WT
+ 20 more — browse all 60 samples with per-sample file links →
- GSE319096 A CRISPR screen in human iPSC-derived neurons reveals convergent transcriptomic effects of neurodevelopmental disorder genes [CRISPR Screen] 32 samples shares neurodevelopmental, disorder
- GSE119316 Impaired oxysterol-liver X receptor signaling underlies aberrant cortical neurogenesis in a stem cell model of neurodevelopmental disorder 71 samples shares neurodevelopmental, disorder
- GSE262442 Scaled and efficient derivation of loss-of-function alleles in risk genes for neurodevelopmental and psychiatric disorders in human iPSCs 69 samples shares neurodevelopmental, disorder
- GSE327684 RNAseq validation of Neurodevelopmental disorder associated genes knockout efficiency [RNAseq] 19 samples shares neurodevelopmental, disorder
- GSE249942 Requirements for the neurodevelopmental disorder-associated gene ZNF292 in human cortical interneuron development and function 55 samples shares neurodevelopmental, disorder
- GSE301239 SETBP1 variants outside the degron disrupt DNA-binding, transcription and neuronal differentiation capacity to cause a heterogeneous neurodevelopmental disorder [induced neurons] 51 samples shares neurodevelopmental, disorder
- GSE271268 Gene expression analysis in obsessive-compulsive disorder with and without comorbid neurodevelopmental disorders 28 samples shares neurodevelopmental, disorder
- GSE316724 Deep mutational scanning of CHD2 for variant interpretation in neurodevelopmental disorders [RNA-seq] 16 samples shares neurodevelopmental, disorder
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.