Hyperactive PI3K-delta in Th1 and Th2 differentiation [RNA-seq]
Single-cell RNA-seq · mouse · 42 samples
- What it is
- Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
- Organism
- Mus musculus (mouse)
- Samples
- 42 samples: 14 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 GSE277881_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 PRJNA1164690 and SRA study SRP534424. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 42 samples.
How we read this: 14 replicated groups read from 42 sample titles; they account for 42 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.
- GSM8533810 WT_Control_Naive 1 WT_Control_Naive
- GSM8533811 Mut_Control_Naive 1 Mut_Control_Naive
- GSM8533812 WT_Control_Naive 2 WT_Control_Naive
- GSM8533813 Mut_Control_Naive 2 Mut_Control_Naive
- GSM8533814 WT_Control_Naive 3 WT_Control_Naive
- GSM8533815 Mut_Control_Naive 3 Mut_Control_Naive
- GSM8533816 WT Control Th0 1 WT Control Th0
- GSM8533817 WT aIL2 Th0 1 WT aIL2 Th0
- GSM8533818 Mut Control Th0 1 Mut Control Th0
- GSM8533819 Mut aIL2 Th0 1 Mut aIL2 Th0
- GSM8533820 WT Control Th0 2 WT Control Th0
- GSM8533821 WT aIL2 Th0 2 WT aIL2 Th0
- GSM8533822 Mut Control Th0 2 Mut Control Th0
- GSM8533823 Mut aIL2 Th0 2 Mut aIL2 Th0
- GSM8533824 WT Control Th0 3 WT Control Th0
- GSM8533825 WT aIL2 Th0 3 WT aIL2 Th0
- GSM8533826 Mut Control Th0 3 Mut Control Th0
- GSM8533827 Mut aIL2 Th0 3 Mut aIL2 Th0
- GSM8533828 WT Control Th1 1 WT Control Th1
- GSM8533829 WT aIL2 Th1 1 WT aIL2 Th1
- GSM8533830 Mut Control Th1 1 Mut Control Th1
- GSM8533831 Mut aIL2 Th1 1 Mut aIL2 Th1
- GSM8533832 WT Control Th1 2 WT Control Th1
- GSM8533833 WT aIL2 Th1 2 WT aIL2 Th1
- GSM8533834 Mut Control Th1 2 Mut Control Th1
- GSM8533835 Mut aIL2 Th1 2 Mut aIL2 Th1
- GSM8533836 WT Control Th1 3 WT Control Th1
- GSM8533837 WT aIL2 Th1 3 WT aIL2 Th1
- GSM8533838 Mut Control Th1 3 Mut Control Th1
- GSM8533839 Mut aIL2 Th1 3 Mut aIL2 Th1
- GSM8533840 WT Control Th2 1 WT Control Th2
- GSM8533841 WT aIL2 Th2 1 WT aIL2 Th2
- GSM8533842 Mut Control Th2 1 Mut Control Th2
- GSM8533843 Mut aIL2 Th2 1 Mut aIL2 Th2
- GSM8533844 WT Control Th2 2 WT Control Th2
- GSM8533845 WT aIL2 Th2 2 WT aIL2 Th2
- GSM8533846 Mut Control Th2 2 Mut Control Th2
- GSM8533847 Mut aIL2 Th2 2 Mut aIL2 Th2
- GSM8533848 WT Control Th2 3 WT Control Th2
- GSM8533849 WT aIL2 Th2 3 WT aIL2 Th2
+ 2 more — browse all 42 samples with per-sample file links →
- GSE267967 Foxp3 and BATF cooperatively direct cis-regulatory programs and gene expression for functional differentiation of Treg cells [RNA-seq] 26 samples shares rna-seq
- GSE215759 Mettl3-dependent m6A modification is essential for effector differentiation and memory formation of CD8+ T cells [RNA-seq] 15 samples shares rna-seq
- GSE277228 Changing dynamics of the fibroblast differentiation hierarchy during mammary gland morphogenesis and tumorigenesis [scRNA-Seq I] 13 samples shares rna-seq
- GSE264105 Plate-based scRNA-seq of plasma-positive microglia and plasma-negative microglia in young mice 1111 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
- GSE326452 Bulk RNA-seq of mouse brain following closed head injury: role of IL-1R1 signaling 200 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.