Disruption of nuclear speckle integrity dysregulates RNA splicing in C9ORF72-FTD/ALS
RNA-seq (gene expression) · human · 15 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
- 15 samples: 5 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.
- Paper
- Disruption of nuclear speckle integrity dysregulates RNA splicing in C9ORF72-FTD/ALSNeuron · 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 GSE248404_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 PRJNA1043685 and SRA study SRP473371. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 15 samples.
How we read this: 5 replicated groups read from 15 sample titles; they account for 15 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.
- GSM7913025 i3N,shScramble rep1 i3N,shScramble
- GSM7913026 i3N,shScramble rep2 i3N,shScramble
- GSM7913027 i3N,shScramble rep3 i3N,shScramble
- GSM7913028 i3N, shSON rep1 i3N, shSON
- GSM7913029 i3N, shSON rep2 i3N, shSON
- GSM7913030 i3N, shSON rep3 i3N, shSON
- GSM7913031 i3N, shSRRM2 rep1 i3N, shSRRM2
- GSM7913032 i3N, shSRRM2 rep2 i3N, shSRRM2
- GSM7913033 i3N, shSRRM2 rep3 i3N, shSRRM2
- GSM8414921 i3N, iGC2 rep1 i3N, iGC2
- GSM8414922 i3N, iGC2 rep2 i3N, iGC2
- GSM8414923 i3N, iGC2 rep3 i3N, iGC2
- GSM8414924 i3N, iGC186 rep1 i3N, iGC186
- GSM8414925 i3N, iGC186 rep2 i3N, iGC186
- GSM8414926 i3N, iGC186 rep3 i3N, iGC186
- GSE270387 Single cell profiling of peripheral blood mononuclear cells in diverse men with prostate cancer reveals lethal disease-associated immune signatures 165 samples shares als, nuclear
- GSE305971 Integrative single-cell analysis reveals malignant archetypes and proliferative hierarchies in multiple myeloma 2105 samples shares als
- GSE314342 Genome-scale perturb-seq in primary human CD4+ T cells reveals genes regulating T cell programs and human immune traits. 577 samples shares als
- GSE263733 Single-cell transcriptome analysis reveals subtype-specific clonal evolution and microenvironmental changes in liver metastasis of pancreatic adenocarcinoma and their clinical implications 218 samples shares als
- GSE328048 Single-cell transcriptome reveals keratinocyte subclusters that contribute to altered differentiation and inflammatory responses in atopic dermatitis 116 samples shares als
- GSE267625 Whole blood transcriptome in long-COVID patients reveals association with lung function and immune response 111 samples shares als
- GSE273700 Whole transcriptome analysis reveals T cell signaling activation in septic patients with thrombocytopenia 104 samples shares als
- GSE130970 Gene expression predicts histological severity and reveals distinct molecular profiles of nonalcoholic fatty liver disease 78 samples shares als
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.