Single-cell RNA sequencing of MC38 subcutaneous allograft tumors in C57BL/6J mice treated with FOLFOX alone or in combination with a composite probiotics
Single-cell RNA-seq · mouse · 9 samples
- What it is
- Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
- Organism
- Mus musculus (mouse)
- Samples
- 9 samples: 3 × NC vs 3 × FOLFOX vs 3 × FOLFOX+PROBIOTICSGroups 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 GSE316313_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.
Also filed as BioProject PRJNA1402282 and SRA study SRP661827. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 9 samples.
How we read this: 3 replicated groups read from 9 sample titles; they account for 9 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.
- GSM9449354 NC2 NC
- GSM9449355 NC6 NC
- GSM9449356 NC12 NC
- GSM9449357 FOLFOX17 FOLFOX
- GSM9449358 FOLFOX18 FOLFOX
- GSM9449359 FOLFOX25 FOLFOX
- GSM9449360 FOLFOX+PROBIOTICS32 FOLFOX+PROBIOTICS
- GSM9449361 FOLFOX+PROBIOTICS33 FOLFOX+PROBIOTICS
- GSM9449362 FOLFOX+PROBIOTICS38 FOLFOX+PROBIOTICS
- GSE274825 RNA sequencing of MC38 tumor cells from control-diet- and high-fat-diet-fed C57BL/6J mice 10 samples shares c57bl, mc38
- GSE278980 Single-cell screens identify ADAM12 as a fibroblast checkpoint impeding anti-tumor immunity - RNA-seq of C57BL/6 murine models 32 samples shares c57bl, single-cell
- GSE311912 Probiotics Complex Synergizes with FOLFOX to Enhance Antitumor Response and Ameliorate Chemotherapy-induced Intestinal Toxicity via Upregulation of NAD+ Metabolism 27 samples shares folfox, probiotics
- GSE319517 Growth of subcutaneous MC38 colorectal cancer triggers mild cachexia 8 samples shares mc38, subcutaneous
- GSE341190 Single-cell transcriptomes of subcutaneous and orthotopic RM-1 mouse prostate tumors collected 7 days after sham or irreversible electroporation 10 samples shares subcutaneous, single-cell
- GSE228455 Gene expression profile at single cell level of monocytes sorted from C57BL/6J mouse ear tissue at 3 weeks post Leishmania major infection [scRNA-seq] 218 samples shares c57bl
- GSE228456 Cell-intrinsic effect of IL-7R signaling of monocytes within C57BL/6J mouse ears infected with Leishmania major [bulk RNA-seq] 87 samples shares c57bl
- GSE291439 C57BL6 Substrain Differences in Hippocampal-Dependent Learning and Transcriptome 72 samples shares c57bl
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.