Different effects of bariatric surgery on epigenetic plasticity in skeletal muscle of individuals with and without type 2 diabetes
RNA-seq (gene expression) · human · 52 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
- 52 samples: 26 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.
- Paper
- Different effects of bariatric surgery on epigenetic plasticity in skeletal muscle of individuals with and without type 2 diabetesDiabetes & metabolism · 2024
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 GSE272133_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 PRJNA1135180 and SRA study SRP519687. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 52 samples.
How we read this: 26 replicated groups read from 52 sample titles; they account for 52 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.
- GSM8393756 OB_Participant_1_w0 OB_Participant_1_w
- GSM8393757 OB_Participant_2_w0 OB_Participant_2_w
- GSM8393758 OB_Participant_3_w0 OB_Participant_3_w
- GSM8393759 OB_Participant_4_w0 OB_Participant_4_w
- GSM8393760 OB_Participant_5_w0 OB_Participant_5_w
- GSM8393761 OB_Participant_6_w0 OB_Participant_6_w
- GSM8393762 OB_Participant_7_w0 OB_Participant_7_w
- GSM8393763 OB_Participant_8_w0 OB_Participant_8_w
- GSM8393764 OB_Participant_9_w0 OB_Participant_9_w
- GSM8393765 OB_Participant_10_w0 OB_Participant_10_w
- GSM8393766 OB_Participant_11_w0 OB_Participant_11_w
- GSM8393767 OB_Participant_12_w0 OB_Participant_12_w
- GSM8393768 OB_Participant_13_w0 OB_Participant_13_w
- GSM8393769 OB_Participant_1_w52 OB_Participant_1_w
- GSM8393770 OB_Participant_2_w52 OB_Participant_2_w
- GSM8393771 OB_Participant_3_w52 OB_Participant_3_w
- GSM8393772 OB_Participant_4_w52 OB_Participant_4_w
- GSM8393773 OB_Participant_5_w52 OB_Participant_5_w
- GSM8393774 OB_Participant_6_w52 OB_Participant_6_w
- GSM8393775 OB_Participant_7_w52 OB_Participant_7_w
- GSM8393776 OB_Participant_8_w52 OB_Participant_8_w
- GSM8393777 OB_Participant_9_w52 OB_Participant_9_w
- GSM8393778 OB_Participant_10_w52 OB_Participant_10_w
- GSM8393779 OB_Participant_11_w52 OB_Participant_11_w
- GSM8393780 OB_Participant_12_w52 OB_Participant_12_w
- GSM8393781 OB_Participant_13_w52 OB_Participant_13_w
- GSM8393782 T2D_Participant_1_w0 T2D_Participant_1_w
- GSM8393783 T2D_Participant_2_w0 T2D_Participant_2_w
- GSM8393784 T2D_Participant_3_w0 T2D_Participant_3_w
- GSM8393785 T2D_Participant_4_w0 T2D_Participant_4_w
- GSM8393786 T2D_Participant_5_w0 T2D_Participant_5_w
- GSM8393787 T2D_Participant_6_w0 T2D_Participant_6_w
- GSM8393788 T2D_Participant_7_w0 T2D_Participant_7_w
- GSM8393789 T2D_Participant_8_w0 T2D_Participant_8_w
- GSM8393790 T2D_Participant_9_w0 T2D_Participant_9_w
- GSM8393791 T2D_Participant_10_w0 T2D_Participant_10_w
- GSM8393792 T2D_Participant_11_w0 T2D_Participant_11_w
- GSM8393793 T2D_Participant_12_w0 T2D_Participant_12_w
- GSM8393794 T2D_Participant_13_w0 T2D_Participant_13_w
- GSM8393795 T2D_Participant_1_w52 T2D_Participant_1_w
+ 12 more — browse all 52 samples with per-sample file links →
- GSE270503 Epigenetic heterogeneity and state-specific transcriptional programs determine differential drug response in osteosarcoma [Cut&Run] 56 samples shares epigenetic, different
- GSE324208 Epigenetic reprogramming drives cellular and phenotypic plasticity in liposarcoma 42 samples shares epigenetic, plasticity
- GSE274680 Inflammation and lymphocyte activation during longitudinal progression to rheumatoid arthritis in at-risk individuals 243 samples shares individuals
- GSE328048 Single-cell transcriptome reveals keratinocyte subclusters that contribute to altered differentiation and inflammatory responses in atopic dermatitis 116 samples shares different
- GSE315928 Differential T cell clonal dynamics underlie outcomes to frontline chemoimmunotherapy in advanced gastric cancer [paired scRNA/TCR-seq] 94 samples shares different
- GSE245175 Neuroblastoma heterogeneity and plasticity over disease progression are rooted in the dynamics of an early sympathetic transcriptional trajectory 79 samples shares plasticity
- GSE306915 Integrated epigenetic and genetic programming of primary human T cells [RNA-seq] 77 samples shares epigenetic
- GSE310095 Whole Blood Transcriptomics Differentiates Circulating Gene Expression Between Coronary Artery Disease and Peripheral Artery Disease 71 samples shares different
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.