Effect of TAC on human and mouse cells [RNA-seq]
RNA-seq (gene expression) · human · 26 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
- 26 samples: 6 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 GSE231454_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 PRJNA966086 and SRA study SRP435507. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 20 samples.
How we read this: 6 replicated groups read from 26 sample titles; they account for 20 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.
- GSM7286206 PBMCs_DMSO-treated_mouse_rep1 PBMCs_DMSO-treated_mouse
- GSM7286207 PBMCs_DMSO-treated_mouse_rep2 PBMCs_DMSO-treated_mouse
- GSM7286208 PBMCs_DMSO-treated_mouse_rep3 PBMCs_DMSO-treated_mouse
- GSM7286209 PBMCs_DMSO-treated_mouse_rep4 PBMCs_DMSO-treated_mouse
- GSM7286210 PBMCs_TAC-treated_mouse_rep1 PBMCs_TAC-treated_mouse
- GSM7286211 PBMCs_TAC-treated_mouse_rep2 PBMCs_TAC-treated_mouse
- GSM7286212 PBMCs_TAC-treated_mouse_rep3 PBMCs_TAC-treated_mouse
- GSM7286213 PBMCs_TAC-treated_mouse_rep4 PBMCs_TAC-treated_mouse
- GSM7286214 DMSO-treated_MRC5_rep1 DMSO-treated_MRC5
- GSM7286215 DMSO-treated_MRC5_rep2 DMSO-treated_MRC5
- GSM7286216 DMSO-treated_MRC5_rep3 DMSO-treated_MRC5
- GSM7286217 TAC-treated_MRC5_rep1 TAC-treated_MRC5
- GSM7286218 TAC-treated_MRC5_rep2 TAC-treated_MRC5
- GSM7286219 TAC-treated_MRC5_rep3 TAC-treated_MRC5
- GSM7286220 DMSO_treated_human_iPSC_derived_neurons_rep1 DMSO_treated_human_iPSC…
- GSM7286221 DMSO_treated_human_iPSC_derived_neurons_rep2 DMSO_treated_human_iPSC…
- GSM7286222 DMSO_treated_human_iPSC_derived_neurons_rep3 DMSO_treated_human_iPSC…
- GSM7286223 TAC_treated_human_iPSC_derived_neurons_rep1 TAC_treated_human_iPSC_…
- GSM7286224 TAC_treated_human_iPSC_derived_neurons_rep2 TAC_treated_human_iPSC_…
- GSM7286225 TAC_treated_human_iPSC_derived_neurons_rep3 TAC_treated_human_iPSC_…
- GSM8229342 Mouse hippocampus from DMSO-treated mouse1 [HS1129_S1]
- GSM8229343 Mouse hippocampus from DMSO-treated mouse2 [HS1129_S2]
- GSM8229344 Mouse hippocampus from DMSO-treated mouse3 [HS1129_S3]
- GSM8229345 Mouse hippocampus from TAC-treated mouse1 [HS1129_S4]
- GSM8229346 Mouse hippocampus from TAC-treated mouse2 [HS1129_S5]
- GSM8229347 Mouse hippocampus from TAC-treated mouse3 [HS1129_S6]
- GSE65360 Single-cell chromatin accessibility data using scATAC-seq 1632 samples shares tac
- GSE320163 Minimizing far-extending chromatin perturbation in genome editing preserves stem cell identity [ATAC-Seq] 377 samples shares tac
- GSE270774 MYC couples SWI/SNF and metabolic reprogramming to sustain minimal residual disease in mTORC1-activated cancer cells [CUT&RUN, ATAC-seq] 32 samples shares tac
- GSE273476 LncRNA CISTR-ACT regulates cell size in human and mouse by guiding FOSL2 [RNA-Seq] 181 samples shares rna-seq
- GSE248942 Spatiotemporal control of SMARCA5 by a MAPK-RUNX1 axis distinguishes mutant KRAS-driven pancreatic malignancy from tissue regeneration (ATAC-Seq) 123 samples shares tac
- GSE249159 scRNA-seq of CD4+ T cells from mouse allergic airway inflammation model and human patients with eosinophilic chronic rhinosinusitis (ECRS) 10 samples shares rna-seq
- GSE256232 Quantitative analysis of cis-regulatory elements in transcription with KAS-ATAC-seq 67 samples shares tac
- GSE259220 Cas13bt3 knockdown of VEGFA mRNA in mammalian cells and mouse retina [RNA-Seq] 61 samples shares rna-seq
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.