CLIP (NOVA1 & AGO) and RNAseq (control & NOVA1KD) in human GBM cells
RNA-seq (gene expression) · human · 36 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
- 36 samples: 17 conditions, mostly in duplicateGroups 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
- NOVA1 acts as an oncogenic RNA-binding protein to regulate cholesterol homeostasis in human glioblastoma cellsProceedings of the National Academy of Sciences of the United States of America · 2024
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 GSE242124_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 PRJNA1011395 and SRA study SRP457903. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 36 samples.
How we read this: 17 replicated groups read from 36 sample titles; they account for 36 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.
- GSM7749266 CLIP_NOVA1_GBM1_1 CLIP_NOVA1_GBM1
- GSM7749267 CLIP_NOVA1_GBM1_2 CLIP_NOVA1_GBM1
- GSM7749268 CLIP_NOVA1_GBM2_1 CLIP_NOVA1_GBM2
- GSM7749269 CLIP_NOVA1_GBM2_2 CLIP_NOVA1_GBM2
- GSM7749270 CLIP_NOVA1_GBM3_1 CLIP_NOVA1_GBM3
- GSM7749271 CLIP_NOVA1_GBM3_2 CLIP_NOVA1_GBM3
- GSM7749272 CLIP_NOVA1_GBM4_1 CLIP_NOVA1_GBM4
- GSM7749273 CLIP_NOVA1_GBM4_2 CLIP_NOVA1_GBM4
- GSM7749274 CLIP_AGO_GBM1 CLIP_AGO_GBM
- GSM7749275 CLIP_AGO_GBM2 CLIP_AGO_GBM
- GSM7749276 CLIP_AGO_GBM3 CLIP_AGO_GBM
- GSM7749277 CLIP_AGO_GBM4 CLIP_AGO_GBM
- GSM7749278 RNAseq_GBM1_shControl_1 RNAseq_GBM1_shControl
- GSM7749279 RNAseq_GBM1_shControl_2 RNAseq_GBM1_shControl
- GSM7749280 RNAseq_GBM1_shNOVA1KD1_1 RNAseq_GBM1_shNOVA1KD1
- GSM7749281 RNAseq_GBM1_shNOVA1KD1_2 RNAseq_GBM1_shNOVA1KD1
- GSM7749282 RNAseq_GBM1_shNOVA1KD2_1 RNAseq_GBM1_shNOVA1KD2
- GSM7749283 RNAseq_GBM1_shNOVA1KD2_2 RNAseq_GBM1_shNOVA1KD2
- GSM7749284 RNAseq_GBM2_shControl_1 RNAseq_GBM2_shControl
- GSM7749285 RNAseq_GBM2_shControl_2 RNAseq_GBM2_shControl
- GSM7749286 RNAseq_GBM2_shNOVA1KD1_1 RNAseq_GBM2_shNOVA1KD1
- GSM7749287 RNAseq_GBM2_shNOVA1KD1_2 RNAseq_GBM2_shNOVA1KD1
- GSM7749288 RNAseq_GBM2_shNOVA1KD2_1 RNAseq_GBM2_shNOVA1KD2
- GSM7749289 RNAseq_GBM2_shNOVA1KD2_2 RNAseq_GBM2_shNOVA1KD2
- GSM7749290 RNAseq_GBM3_shControl_1 RNAseq_GBM3_shControl
- GSM7749291 RNAseq_GBM3_shControl_2 RNAseq_GBM3_shControl
- GSM7749292 RNAseq_GBM3_shNOVA1KD1_1 RNAseq_GBM3_shNOVA1KD1
- GSM7749293 RNAseq_GBM3_shNOVA1KD1_2 RNAseq_GBM3_shNOVA1KD1
- GSM7749294 RNAseq_GBM3_shNOVA1KD2_1 RNAseq_GBM3_shNOVA1KD2
- GSM7749295 RNAseq_GBM3_shNOVA1KD2_2 RNAseq_GBM3_shNOVA1KD2
- GSM7749296 RNAseq_GBM4_shControl_1 RNAseq_GBM4_shControl
- GSM7749297 RNAseq_GBM4_shControl_2 RNAseq_GBM4_shControl
- GSM7749298 RNAseq_GBM4_shNOVA1KD1_1 RNAseq_GBM4_shNOVA1KD1
- GSM7749299 RNAseq_GBM4_shNOVA1KD1_2 RNAseq_GBM4_shNOVA1KD1
- GSM7749300 RNAseq_GBM4_shNOVA1KD2_1 RNAseq_GBM4_shNOVA1KD2
- GSM7749301 RNAseq_GBM4_shNOVA1KD2_2 RNAseq_GBM4_shNOVA1KD2
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- GSE211643 Epigenetic control over IFN Type-I response antagonizes self-renewal in acute myeloid leukemia 23 samples shares ago, control
- GSE211642 Epigenetic Control over IFN Type-I Response antagonizes self-renewal in acute myeloid leukemia (RNA-seq) 18 samples shares ago, control
- GSE259370 Analysis of a pair of HCA-7 derived cells with low expressing (CC) or high expressing (CC-CR) levels of miR-100 and miR-125b and RNA collected from Ago2 RNA immunoprecipitation (RNAseq_human_AGO2_IP.8635) 11 samples shares ago
- GSE309239 High-dimensional profiling uncovers heterogeneity, lineage-specific precursors and inflammation-induced changes in the mononuclear phagocyte compartment of the human intestine 28 samples shares ago
- GSE260944 Mutability and hypermutation antagonize immunoglobulin codon optimality; Analysis of human MLN B cells. 14 samples shares ago
- GSE79577 High throughput characterization of the m6A demethylase FTO by CLIP and RNAseq 12 samples shares clip
- GSE213807 RNA-seq and iCLIP-seq of cells that harbor retinitis pigmentosa mutations 31 samples shares clip
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.