A phase II randomized trial with autologous polyclonal expanded regulatory T cells in children with new-onset type 1 diabetes
RNA-seq (gene expression) · human · 117 samples
- What it is
- RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
- Organism
- Homo sapiens (human)
- Samples
- 117 samples: 105 × libGroups 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
- A phase 2 randomized trial with autologous polyclonal expanded regulatory T cells in children with new-onset type 1 diabetesScience translational medicine · 2024
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 GSE243278_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: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.
Also filed as BioProject PRJNA1017509 and SRA study SRP460597. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 105 samples.
How we read this: 1 replicated groups read from 117 sample titles; they account for 105 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.
- GSM7780646 1_TG02-17-012_Infusion
- GSM7780647 2_102-017_3
- GSM7780648 3_102-017_5
- GSM7780649 4_102-017_8
- GSM7780650 5_TG02-17-063_Infusion
- GSM7780651 6_106-003_3
- GSM7780652 7_106-003_5
- GSM7780653 8_106-003_8
- GSM7780654 13_TG02-17-045_Infusion
- GSM7780655 14_108-008_3
- GSM7780656 15_108-008_6
- GSM7780657 16_108-008_7
- GSM7782550 lib77826 lib
- GSM7782551 lib77827 lib
- GSM7782552 lib77828 lib
- GSM7782553 lib77829 lib
- GSM7782554 lib77830 lib
- GSM7782555 lib77831 lib
- GSM7782556 lib77832 lib
- GSM7782557 lib77833 lib
- GSM7782558 lib77834 lib
- GSM7782559 lib77835 lib
- GSM7782560 lib77836 lib
- GSM7782561 lib77837 lib
- GSM7782562 lib77838 lib
- GSM7782563 lib77839 lib
- GSM7782564 lib77840 lib
- GSM7782565 lib77841 lib
- GSM7782566 lib77842 lib
- GSM7782567 lib77843 lib
- GSM7782568 lib77844 lib
- GSM7782569 lib77845 lib
- GSM7782570 lib77846 lib
- GSM7782571 lib77847 lib
- GSM7782572 lib77848 lib
- GSM7782573 lib77849 lib
- GSM7782574 lib77850 lib
- GSM7782575 lib77851 lib
- GSM7782576 lib77852 lib
- GSM7782577 lib77853 lib
+ 77 more — browse all 117 samples with per-sample file links →
- GSE280975 Single-cell transcriptomics reveals markers of regulatory T cell dysfunction in Gestational Diabetes Mellitus 33 samples shares regulatory, diabetes
- GSE285773 Single cell RNA profiling of blood CD4+ T cells identifies distinct helper and dysfunctional regulatory clusters in children with SLE [CD4+ T cells] 26 samples shares regulatory, children
- GSE298578 Single cell RNA profiling of blood CD4+ T cells identifies distinct helper and dysfunctional regulatory clusters in children with SLE (5' PBMC validation dataset) 14 samples shares regulatory, children
- GSE273594 Single-cell multiome profiling reveals pancreas cell type-specific gene regulatory programs of type 1 diabetes progression [multiome] 8 samples shares regulatory, diabetes
- GSE327727 D-SPIN constructs regulatory network models from scRNA-seq revealing organizing principles of perturbation response 194 samples shares regulatory
- GSE325670 Promoter mutagenesis and a massively parallel reporter screen of the MAPT locus identifies cis-regulatory elements and genetic variation effects 140 samples shares regulatory
- GSE224689 Regulatory principles of human mitochondrial gene expression revealed by kinetic analysis of the RNA life cycle. 113 samples shares regulatory
- GSE224662 Regulatory principles of human mitochondrial gene expression revealed by kinetic analysis of the RNA life cycle 98 samples shares regulatory
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.