Single-cell transcriptomic effects of LOX knockdown on tumor cell xenografts implanted on aged mouse breast dECM scaffolds
Single-cell RNA-seq · human · 12 samples
- What it is
- Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
- Organism
- Homo sapiens (human)
- Samples
- 12 samples: 12 samples, each with a distinct title — no replicated groupsGroups 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 GSE333415_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 PRJNA1471051 and SRA study SRP704119. Searching any of these in the dataset finder brings you back here.
Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.
How we read this: Read from 12 sample titles: 12 distinct titles with little repetition. 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.
- GSM9764195 Parse Evercode WT scRNA-seq — human tumor cell, pLKO ctrl rep 1 (pLKO-T-1)
- GSM9764196 Parse Evercode WT scRNA-seq — human tumor cell, shLOX KD rep 1 (shLOX-T-1)
- GSM9764197 Parse Evercode WT scRNA-seq — human tumor cell, pLKO ctrl rep 2 (pLKO-T-2)
- GSM9764198 Parse Evercode WT scRNA-seq — human tumor cell, shLOX KD rep 2 (shLOX-T-2)
- GSM9764199 Parse Evercode WT scRNA-seq — human tumor cell, pLKO ctrl rep 3 (pLKO-T-3)
- GSM9764200 Parse Evercode WT scRNA-seq — human tumor cell, shLOX KD rep 3 (shLOX-T-3)
- GSM9764201 Parse Evercode WT scRNA-seq — mouse CD11b+ myeloid, pLKO ctrl rep 1 (pLKO-I-1)
- GSM9764202 Parse Evercode WT scRNA-seq — mouse CD11b+ myeloid, shLOX KD rep 1 (shLOX-I-1)
- GSM9764203 Parse Evercode WT scRNA-seq — mouse CD11b+ myeloid, pLKO ctrl rep 2 (pLKO-I-2)
- GSM9764204 Parse Evercode WT scRNA-seq — mouse CD11b+ myeloid, shLOX KD rep 2 (shLOX-I-2)
- GSM9764205 Parse Evercode WT scRNA-seq — mouse CD11b+ myeloid, pLKO ctrl rep 3 (pLKO-I-3)
- GSM9764206 Parse Evercode WT scRNA-seq — mouse CD11b+ myeloid, shLOX KD rep 3 (shLOX-I-3)
- GSE246613 Single-cell and spatial profiling identify three response trajectories to pembrolizumab and radiation therapy in triple negative breast cancer 266 samples shares single-cell, breast
- GSE284115 Single-cell transcriptomics of myeloid milieu reveals an angiogenic niche in triple-negative breast cancer 6 samples shares single-cell, breast
- GSE310423 Determinants of long-term response to patritumab deruxtecan (HER3-DXd) in breast cancer patient-derived xenografts. 167 samples shares xenografts, breast
- GSE235950 Comparison of transcriptional profiles of human psoriatic skin and skin from K14-CreER/GPX4flox mouse model. 18 samples shares lox
- GSE150672 Highly Efficient, Massively-Parallel Single-Cell RNA-Seq Reveals Cellular States and Molecular Features of Human Skin Pathology 438 samples shares single-cell
- GSE38495 Full-length mRNA-Seq from single-cell levels of RNA and individual circulating tumor cells 121 samples shares single-cell
- GSE92872 Pooled CRISPR screening with single-cell transcriptome read-out 100 samples shares single-cell
- GSE259220 Cas13bt3 knockdown of VEGFA mRNA in mammalian cells and mouse retina [RNA-Seq] 61 samples shares knockdown
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.