Immunometabolic Endotypes Define Distinct Clinical Trajectories in Type 2 Diabetes [bulk RNA-seq]
Single-cell RNA-seq · human · 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
- Homo sapiens (human)
- Samples
- 42 samples: 40 × CRC vs 2 × CARDGroups 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 GSE309941_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 PRJNA1364023. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 42 samples.
How we read this: 2 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.
- GSM9285049 CARD318 CARD
- GSM9285050 CARD338 CARD
- GSM9285051 CRC21212 CRC
- GSM9285052 CRC21221 CRC
- GSM9285053 CRC21239 CRC
- GSM9285054 CRC21268 CRC
- GSM9285055 CRC21292 CRC
- GSM9285056 CRC21300 CRC
- GSM9285057 CRC21318 CRC
- GSM9285058 CRC21345 CRC
- GSM9285059 CRC21355 CRC
- GSM9285060 CRC21377 CRC
- GSM9285061 CRC21424 CRC
- GSM9285062 CRC21425 CRC
- GSM9285063 CRC21434 CRC
- GSM9285064 CRC22008 CRC
- GSM9285065 CRC22042 CRC
- GSM9285066 CRC22095 CRC
- GSM9285067 CRC22116 CRC
- GSM9285068 CRC22117 CRC
- GSM9285069 CRC22122 CRC
- GSM9285070 CRC22124 CRC
- GSM9285071 CRC22147 CRC
- GSM9285072 CRC22188 CRC
- GSM9285073 CRC22195 CRC
- GSM9285074 CRC22223 CRC
- GSM9285075 CRC22229 CRC
- GSM9285076 CRC22258 CRC
- GSM9285077 CRC22267 CRC
- GSM9285078 CRC22278 CRC
- GSM9285079 CRC22318 CRC
- GSM9285080 CRC22342 CRC
- GSM9285081 CRC22356 CRC
- GSM9285082 CRC22397 CRC
- GSM9285083 CRC23079 CRC
- GSM9285084 CRC23187 CRC
- GSM9285085 CRC23218 CRC
- GSM9285086 CRC23244 CRC
- GSM9285087 CRC23295 CRC
- GSM9285088 CRC23433 CRC
+ 2 more — browse all 42 samples with per-sample file links →
- GSE309967 Immunometabolic Endotypes Define Distinct Clinical Trajectories in Type 2 Diabetes 48 samples shares immunometabolic, trajectories, endotypes, distinct, clinical, diabetes, define
- GSE316337 Multi-omics profiling reveals microbiota, metabolite, lipid, and immunological heterogeneity underlying distinct pathophysiological mechanisms of age-related endotypes in type 1 diabetes 54 samples shares endotypes, distinct, diabetes
- GSE274999 Clinical response to azacitidine in MDS is associated with distinct DNA methylation changes in HSPCs [RNA-Seq] 52 samples shares distinct, clinical, rna-seq
- GSE319130 Multi-omic analysis reveals molecular subtypes with distinct immunological phenotypes in SLE [RNA-Seq] 804 samples shares distinct, rna-seq
- GSE312983 A single-nucleus RNA-seq atlas of colorectal cancer across the age continuum reveals distinct features of early-onset colorectal cancer 189 samples shares distinct, rna-seq
- GSE330551 Th2-primed innate immune amplification defines a distinct atopic dermatitis endotype 174 samples shares distinct, define
- GSE298908 Positionally distinct interferon-stimulated dermal immune-acting fibroblasts promote neutrophil recruitment in Sweet's syndrome [RNA-seq] 113 samples shares distinct, rna-seq
- GSE322943 Dissecting the cellular architecture of breast cancer brain metastases reveals prognostically distinct immune landscapes [RNA-Seq] 100 samples shares distinct, 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.