Single-cell RNA-seq of Lgr5-eGFP+ intestinal stem cells upon Wnt and R-spondin modulation in vivo
Single-cell RNA-seq · mouse · 14 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
- 14 samples: 7 conditions, mostly in duplicateGroups 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 GSE92865_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 PRJNA358672 and SRA study SRP095593. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 14 samples.
How we read this: 7 replicated groups read from 14 sample titles; they account for 14 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.
- GSM2438914 Fc_1 Fc
- GSM2438915 Fc_2 Fc
- GSM2438916 Fzd8_Fc_1 Fzd8_Fc
- GSM2438917 Fzd8_Fc_2 Fzd8_Fc
- GSM2438918 LGR5_ECD_1 LGR5_ECD
- GSM2438919 LGR5_ECD_2 LGR5_ECD
- GSM2438920 Lgr5_eGFP_neg_1 Lgr5_eGFP_neg
- GSM2438921 Lgr5_eGFP_neg_2 Lgr5_eGFP_neg
- GSM2438922 Rspo1_Fc_1 Rspo1_Fc
- GSM2438923 Rspo1_Fc_2 Rspo1_Fc
- GSM2438924 Rspo2_Fc_1 Rspo2_Fc
- GSM2438925 Rspo2_Fc_2 Rspo2_Fc
- GSM2438926 scFv_DKK1c_1 scFv_DKK1c
- GSM2438927 scFv_DKK1c_2 scFv_DKK1c
- GSE303460 Spatiotemporal single-cell atlas of suture stem cell dynamics in craniosynostosis [scRNA-Seq] 14 samples shares single-cell, rna-seq, stem
- GSE329635 Single-cell RNA sequencing of small intestinal organoid self-organization [scRNA-Seq] 10 samples shares single-cell, intestinal, rna-seq
- GSE277789 Spatiotemporal and genetic cell lineage tracing of endodermal organogenesis at single-cell resolution [Smart-seq3-RNA-seq-add] 830 samples shares single-cell, rna-seq
- GSE166225 Inference of emergent spatio-temporal processes from single-cell sequencing reveals feedback between de novo DNA methylation and chromatin condensates [RNA-seq] 288 samples shares single-cell, rna-seq
- 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 single-cell, rna-seq
- GSE262879 Single-cell RNA-sequencing of murine pancreatic tumors derived from the orthotopic transplantation of Smad4 wild-type (WT) or Smad4 knockout (KO) pancreatic ductal adenocarcinoma (PDAC) KPC organoids in nu/nu mice. 18 samples shares single-cell, rna-seq
- GSE227108 Integrated single-cell analysis defines the epigenetic basis of castration-resistant prostate luminal cells (scRNA-seq) 18 samples shares single-cell, rna-seq
- GSE264278 TIme-cource single-cell RNA-seq analysis of bleomycin and LPS-induced lung injury and fibrosis 18 samples shares single-cell, 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.