RNA-Seq of gut of colorectal cancer mice fed black rice and control diets
RNA-seq (gene expression) · mouse · 38 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
- 38 samples: 12 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 GSE225104_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 PRJNA933928 and SRA study SRP422041. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 38 samples.
How we read this: 12 replicated groups read from 38 sample titles; they account for 38 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.
- GSM7039381 B_F_Apc_1 B_F_Apc
- GSM7039382 B_F_Apc_2 B_F_Apc
- GSM7039383 B_F_Apc_3 B_F_Apc
- GSM7039384 B_M_Apc_1 B_M_Apc
- GSM7039385 B_M_Apc_2 B_M_Apc
- GSM7039386 B_M_Apc_3 B_M_Apc
- GSM7039387 C_F_Apc_1 C_F_Apc
- GSM7039388 C_F_Apc_2 C_F_Apc
- GSM7039389 C_F_Apc_3 C_F_Apc
- GSM7039390 C_M_Apc_1 C_M_Apc
- GSM7039391 C_M_Apc_2 C_M_Apc
- GSM7039392 C_M_Apc_3 C_M_Apc
- GSM7039393 WT_F_Apc_1 WT_F_Apc
- GSM7039394 WT_F_Apc_2 WT_F_Apc
- GSM7039395 WT_F_Apc_3 WT_F_Apc
- GSM7039396 WT_M_Apc_1 WT_M_Apc
- GSM7039397 WT_M_Apc_2 WT_M_Apc
- GSM7039398 WT_M_Apc_3 WT_M_Apc
- GSM7039399 B_F_AOM_1 B_F_AOM
- GSM7039400 B_F_AOM_2 B_F_AOM
- GSM7039401 B_F_AOM_3 B_F_AOM
- GSM7039402 B_M_AOM_1 B_M_AOM
- GSM7039403 B_M_AOM_2 B_M_AOM
- GSM7039404 B_M_AOM_3 B_M_AOM
- GSM7039405 C_F_AOM_1 C_F_AOM
- GSM7039406 C_F_AOM_2 C_F_AOM
- GSM7039407 C_F_AOM_3 C_F_AOM
- GSM7039408 C_M_AOM_1 C_M_AOM
- GSM7039409 C_M_AOM_2 C_M_AOM
- GSM7039410 C_M_AOM_3 C_M_AOM
- GSM7039411 B1 B
- GSM7039412 B2 B
- GSM7039413 B3 B
- GSM7039414 B4 B
- GSM7039415 C1 C
- GSM7039416 C2 C
- GSM7039417 C3 C
- GSM7039418 C4 C
- GSE306116 Caspase-3 Control of RNA Splicing and Mitochondrial Dynamics in Microglia during Parkinson’s Disease [RNA-Seq] 12 samples shares rna-seq, control
- GSE300288 Single-cell and spatial transcriptomics analysis of tobacco-associated lung adenocarcinoma development, and in response to targeting inflammation alone or in combination with immune checkpoint blockade in precancerous phase [scRNA-seq] 31 samples shares rna-seq
- GSE338763 Inflammatory Neuropathy in Mouse and Primate Models of Colorectal Cancer 24 samples shares colorectal
- GSE297298 Single-cell RNA-sequencing identifies anti-cancer immune phenotypes in the early lung metastatic niche during breast cancer 18 samples shares rna-seq
- GSE326100 scRNA-seq of mouse cochlea organoid cells 768 samples shares rna-seq
- GSE311449 Single cell RNA-seq of mouse brain vascular cells with Smart-seq2 method 391 samples shares rna-seq
- GSE319614 Bulk RNA-seq transcriptome profiling of hippocampus across 17 autism spectrum disorder mouse models 269 samples shares rna-seq
- GSE228960 Bulk RNA-Seq from kidneys of uninephrectomized db/db mice as a model of severe diabetic kidney disease 28 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.