Optimizing murine sample sizes for RNA-seq studies revealed from large-scale comparative analysis
RNA-seq (gene expression) · mouse · 479 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
- Mus musculus (mouse)
- Samples
- 479 samples: 8 conditions, mostly with about 54 replicates eachGroups 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.
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 GSE272152_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 PRJNA1135223 and SRA study SRP519601. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 400 samples.
How we read this: 8 replicated groups read from the first 400 of 479 sample titles; they account for 400 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.
- GSM8394245 kidney.WT.1291205 kidney.WT
- GSM8394246 kidney.WT.1291206 kidney.WT
- GSM8394247 kidney.Het.1291216 kidney.Het
- GSM8394248 kidney.Het.1291217 kidney.Het
- GSM8394249 kidney.WT.1291218 kidney.WT
- GSM8394250 kidney.WT.1291219 kidney.WT
- GSM8394251 kidney.Het.1291220 kidney.Het
- GSM8394252 kidney.Het.1291221 kidney.Het
- GSM8394253 kidney.WT.1291222 kidney.WT
- GSM8394254 kidney.Het.1291223 kidney.Het
- GSM8394255 kidney.Het.1291224 kidney.Het
- GSM8394256 kidney.Het.1291225 kidney.Het
- GSM8394257 kidney.WT.1291226 kidney.WT
- GSM8394258 kidney.Het.1291227 kidney.Het
- GSM8394259 kidney.WT.1291228 kidney.WT
- GSM8394260 kidney.Het.1291229 kidney.Het
- GSM8394261 kidney.Het.1291230 kidney.Het
- GSM8394262 kidney.WT.1291231 kidney.WT
- GSM8394263 kidney.Het.1291232 kidney.Het
- GSM8394264 kidney.WT.1291233 kidney.WT
- GSM8394265 kidney.Het.1291234 kidney.Het
- GSM8394266 kidney.Het.1291235 kidney.Het
- GSM8394267 kidney.WT.1291236 kidney.WT
- GSM8394268 kidney.Het.1291237 kidney.Het
- GSM8394269 kidney.WT.1291238 kidney.WT
- GSM8394270 kidney.WT.1291239 kidney.WT
- GSM8394271 kidney.Het.1291240 kidney.Het
- GSM8394272 kidney.WT.1291241 kidney.WT
- GSM8394273 kidney.WT.1291242 kidney.WT
- GSM8394274 kidney.Het.1291243 kidney.Het
- GSM8394275 kidney.Het.1291244 kidney.Het
- GSM8394276 kidney.Het.1291245 kidney.Het
- GSM8394277 kidney.WT.1291246 kidney.WT
- GSM8394278 kidney.Het.1291247 kidney.Het
- GSM8394279 kidney.Het.1291248 kidney.Het
- GSM8394280 kidney.WT.1291249 kidney.WT
- GSM8394281 kidney.WT.1291250 kidney.WT
- GSM8394282 kidney.WT.1291251 kidney.WT
- GSM8394283 kidney.WT.1291252 kidney.WT
- GSM8394284 kidney.WT.1291253 kidney.WT
+ 439 more — browse all 479 samples with per-sample file links →
- GSE205592 Obesity-instructed TREM2-high macrophages identified by comparative analysis of diabetic mouse and human kidney at single-cell resolution [scRNA-seq: DKD_mouse] 41 samples shares comparative, rna-seq
- GSE283201 Comparative gene expression profiling analysis of hippocampus and liver RNA-seq data for young (3-month-old) and aged (22-month-old) WT mice in both control and ethanol feeding conditions. 32 samples shares comparative, rna-seq
- GSE215960 Subclonal evolution revealed by single-cell profiles of expressed mutations identifies adaptation mechanisms to immunotherapy in melanoma [scRNA-seq] 192 samples shares revealed, rna-seq
- GSE205593 Obesity-instructed TREM2-high macrophages identified by comparative analysis of diabetic mouse and human kidney at single-cell resolution [scRNA-seq: Baseline_mouse] 24 samples shares comparative, rna-seq
- GSE217457 scRNA-seq analysis revealed the molecular characteristics of HSPCs and erythroid cells in bone marrow upon HAPC 10 samples shares revealed, rna-seq
- GSE117677 Influence of low-input RNA from FF and FFPE samples on gene expression quantification by NanoString, microarray and RNA-seq: a comparative study [RNA-seq] 66 samples shares comparative, rna-seq
- GSE337004 Comparative RNA-seq analysis of PM2.5 responses in wildtype and malignantly transformed mouse mammary epithelial cells cultured as spheroids 8 samples shares comparative, rna-seq
- GSE269973 Signaling basis of gastric epithelial cell differentiation revealed by human and mouse organoids [RNA-Seq] 32 samples shares revealed, 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.