A high-fidelity CRISPR-Cas13 system improves abnormalities associated with C9ORF72-linked ALS/FTD
RNA-seq (gene expression) · human · 54 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
- 54 samples: 18 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
- A high-fidelity CRISPR-Cas13 system improves abnormalities associated with C9ORF72-linked ALS/FTDNature communications · 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 GSE251822_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 PRJNA1055505 and SRA study SRP479547. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 54 samples.
How we read this: 18 replicated groups read from 54 sample titles; they account for 54 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.
- GSM7988716 WT_NTG_1 WT_NTG
- GSM7988717 WT_NTG_2 WT_NTG
- GSM7988718 WT_NTG_3 WT_NTG
- GSM7988719 WT_S13_1 WT_S13
- GSM7988720 WT_S13_2 WT_S13
- GSM7988721 WT_S13_3 WT_S13
- GSM7988722 N2V7_NTG_1 N2V7_NTG
- GSM7988723 N2V7_NTG_2 N2V7_NTG
- GSM7988724 N2V7_NTG_3 N2V7_NTG
- GSM7988725 N2V7_S13_1 N2V7_S13
- GSM7988726 N2V7_S13_2 N2V7_S13
- GSM7988727 N2V7_S13_3 N2V7_S13
- GSM7988728 N2V8_NTG_1 N2V8_NTG
- GSM7988729 N2V8_NTG_2 N2V8_NTG
- GSM7988730 N2V8_NTG_3 N2V8_NTG
- GSM7988731 N2V8_S13_1 N2V8_S13
- GSM7988732 N2V8_S13_2 N2V8_S13
- GSM7988733 N2V8_S13_3 N2V8_S13
- GSM7988734 UT_1 UT
- GSM7988735 UT_2 UT
- GSM7988736 UT_3 UT
- GSM7988737 WT_S3_1 WT_S3
- GSM7988738 WT_S3_2 WT_S3
- GSM7988739 WT_S3_3 WT_S3
- GSM7988740 WT_S4_1 WT_S4
- GSM7988741 WT_S4_2 WT_S4
- GSM7988742 WT_S4_3 WT_S4
- GSM7988743 WT_S7_1 WT_S7
- GSM7988744 WT_S7_2 WT_S7
- GSM7988745 WT_S7_3 WT_S7
- GSM7988746 N2V7_S3_1 N2V7_S3
- GSM7988747 N2V7_S3_2 N2V7_S3
- GSM7988748 N2V7_S3_3 N2V7_S3
- GSM7988749 N2V7_S4_1 N2V7_S4
- GSM7988750 N2V7_S4_2 N2V7_S4
- GSM7988751 N2V7_S4_3 N2V7_S4
- GSM7988752 N2V7_S7_1 N2V7_S7
- GSM7988753 N2V7_S7_2 N2V7_S7
- GSM7988754 N2V7_S7_3 N2V7_S7
- GSM7988755 N2V8_S3_1 N2V8_S3
+ 14 more — browse all 54 samples with per-sample file links →
- GSE266330 Single cell profiling of bone metastasis ecosystems from multiple cancer types reveals convergent and divergent mechanisms of bone colonization 63 samples shares als, system
- GSE303478 Systematic investigation reveals extensive Epstein-Barr virus transcriptional regulation of the human genome 217 samples shares als, system
- GSE233321 Single-cell map of the healthy human immune system across the lifespan reveals unique infant immune signatures 118 samples shares als, system
- 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
- GSE49711 RNA-Seq reveals an unprecedented complexity of the neuroblastoma transcriptome and is suitable for clinical endpoint prediction [RNA-Seq] 498 samples shares als
- GSE274680 Inflammation and lymphocyte activation during longitudinal progression to rheumatoid arthritis in at-risk individuals 243 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
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.