Mechanisms by which whole genome doubling drives breast tumor evolution [scRNA-seq]
Single-cell RNA-seq · mouse · 20 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
- 20 samples: 8 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.
- Paper
- Whole-genome doubling drives immune evasion by silencing antigen presentationCancer cell · 2026
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 GSE274140_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 PRJNA1145269 and SRA study SRP524701. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 20 samples.
How we read this: 8 replicated groups read from 20 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.
- GSM8444156 AJ_WGD-_Tumor1 AJ_WGD-_Tumo
- GSM8444157 AJ_WGD-_Tumor2 AJ_WGD-_Tumo
- GSM8444158 AJ_WGD-_Tumor3 AJ_WGD-_Tumo
- GSM8444159 AJ_WGD+_Tumor1 AJ_WGD+_Tumo
- GSM8444160 AJ_WGD+_Tumor2 AJ_WGD+_Tumo
- GSM8444161 AJ_WGD+_Tumor3 AJ_WGD+_Tumo
- GSM8444162 NSG_WGD-_Tumor1 NSG_WGD-_Tumo
- GSM8444163 NSG_WGD-_Tumor2 NSG_WGD-_Tumo
- GSM8444164 NSG_WGD-_Tumor3 NSG_WGD-_Tumo
- GSM8444165 NSG_WGD+_Tumor1 NSG_WGD+_Tumo
- GSM8444166 NSG_WGD+_Tumor2 NSG_WGD+_Tumo
- GSM8444167 NSG_WGD+_Tumor3 NSG_WGD+_Tumo
- GSM8444168 AJ_WGD-_Day8_Tumor1 AJ_WGD-_Day8_Tumo
- GSM8444169 AJ_WGD-_Day8_Tumor2 AJ_WGD-_Day8_Tumo
- GSM8444170 AJ_WGD-_Day14_Tumor3 AJ_WGD-_Day14_Tumo
- GSM8444171 AJ_WGD-_Day14_Tumor4 AJ_WGD-_Day14_Tumo
- GSM8444172 AJ_WGD+_Day8_Tumor1 AJ_WGD+_Day8_Tumo
- GSM8444173 AJ_WGD+_Day8_Tumor2 AJ_WGD+_Day8_Tumo
- GSM8444174 AJ_WGD+_Day14_Tumor3 AJ_WGD+_Day14_Tumo
- GSM8444175 AJ_WGD+_Day14_Tumor4 AJ_WGD+_Day14_Tumo
- GSE287528 Gas6-Axl signaling drives oral regenerative wound repair [scRNA-seq] 10 samples shares scrna-seq, drives
- GSE304945 Tumor-borne ADAMTSL4 drives cancer cachexia via TGFβ signaling pathway 32 samples shares drives
- GSE245838 Anchored screening identifies transcription factor blueprints underlying dendritic cell diversity and subset-specific anti-tumor immunity [mouse scRNA-seq] 21 samples shares scrna-seq
- GSE329919 Tumor microbial burden drives immune responses through regulation of Interferon signaling 20 samples shares drives
- GSE269347 Daunorubicin-induced T cell remodeling facilitates a high antitumor response to PD-1 blockade therapy by promoting the expansion and effector function of CD8+ prolifeating T cells [scRNA-Seq] 16 samples shares scrna-seq
- GSE277228 Changing dynamics of the fibroblast differentiation hierarchy during mammary gland morphogenesis and tumorigenesis [scRNA-Seq I] 13 samples shares scrna-seq
- GSE273440 A tumor-associated photoreceptor signature unifies distinct central nervous system malignancies [scRNA-seq] 13 samples shares scrna-seq
- GSE299487 LY6D Identifies Persistent Tumor-Initiating Cells Driving Pancreatic Tumorigenesis [scRNA-seq] 12 samples shares scrna-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.