Genetic Effects in Response to Exercise and Diet-induced Weight-loss in Human Skeletal Muscle Tissues
RNA-seq (gene expression) · human · 108 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
- 108 samples: 108 samples, each with a distinct title — no replicated groupsGroups 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
- Impact of polymorphisms on gene expression and splicing in response to exercise and diet-induced weight loss in human skeletal muscle tissuesCell genomics · 2025
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 GSE282733_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 PRJNA1190094 and SRA study SRP547263. Searching any of these in the dataset finder brings you back here.
Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.
How we read this: Read from 108 sample titles: 108 distinct titles with little repetition. 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.
- GSM8649492 2016_04_28_13_24_45_801
- GSM8649493 2016_04_28_14_00_30_114
- GSM8649494 2016_05_11_17_18_00_824
- GSM8649495 2016_05_11_17_16_14_218
- GSM8649496 2016_05_16_21_12_47_475
- GSM8649497 2016_05_16_21_11_15_856
- GSM8649498 2016_05_16_17_34_42_92
- GSM8649499 2016_05_16_17_18_34_289
- GSM8649500 2016_05_16_17_49_45_376
- GSM8649501 2016_05_16_17_51_10_518
- GSM8649502 2016_05_18_13_58_32_327
- GSM8649503 2016_05_16_17_00_59_839
- GSM8649504 2016_05_16_16_45_29_108
- GSM8649505 2016_05_16_16_41_52_417
- GSM8649506 2016_05_16_21_54_35_96
- GSM8649507 2016_05_16_21_59_32_901
- GSM8649508 2016_05_16_22_17_51_922
- GSM8649509 2016_05_16_22_17_36_662
- GSM8649510 2016_04_28_15_23_36_476
- GSM8649511 2016_04_28_15_59_55_73
- GSM8649512 2016_04_28_13_25_15_06
- GSM8649513 2016_04_28_13_25_26_926
- GSM8649514 2016_04_28_17_11_11_462
- GSM8649515 2016_04_28_17_19_50_455
- GSM8649516 2016_04_28_14_02_38_956
- GSM8649517 2016_04_28_13_59_15_791
- GSM8649518 2016_05_16_21_18_02_776
- GSM8649519 2016_05_16_21_35_33_708
- GSM8649520 2016_05_16_22_40_54_326
- GSM8649521 2016_05_16_22_39_23_687
- GSM8649522 2016_05_16_20_51_34_25
- GSM8649523 2016_05_16_21_00_26_706
- GSM8649524 2016_05_11_16_23_27_159
- GSM8649525 2016_05_11_16_49_18_593
- GSM8649526 2016_05_16_22_59_56_285
- GSM8649527 2016_05_16_23_12_24_585
- GSM8649528 2016_05_16_14_53_39_957
- GSM8649529 2016_05_16_15_11_48_308
- GSM8649530 2016_05_16_21_57_28_96
- GSM8649531 2016_05_16_22_15_13_752
+ 68 more — browse all 108 samples with per-sample file links →
- GSE252357 The 24-Hour Time Course of Integrated Molecular Responses to Resistance Exercise in Human Skeletal Muscle Implicates MYC as a Hypertrophic Regulator 61 samples shares exercise, skeletal, muscle
- GSE272133 Different effects of bariatric surgery on epigenetic plasticity in skeletal muscle of individuals with and without type 2 diabetes 52 samples shares skeletal, genetic, muscle
- GSE292369 Acute Nutritional Ketosis During Early Recovery from Exercise Does Not Affect Skeletal Muscle Transcriptomic Response 36 samples shares exercise, skeletal, muscle
- GSE262576 Extracellular Vesicle miR-1 Delivery from Skeletal Muscle to Adipose Tissue Modifies Lipolytic Pathways in Response to Resistance Exercise in Humans 12 samples shares exercise, skeletal, muscle
- GSE243339 Clues to Drivers of Juvenile Dermatomyositis: Genetic Alterations after Type I Interferon and JAK Inhibitor Treatment in Pediatric Bioengineered Skeletal Muscle 83 samples shares skeletal, genetic, muscle
- GSE263838 The interactive effect of sustained sleep restriction and resistance exercise on skeletal muscle transcriptomics in young females 38 samples shares exercise, skeletal, muscle
- GSE276889 Mitochondria isolated from male skeletal muscle contain a small and distinct population of microRNA that are differentially expressed following acute endurance exercise 33 samples shares exercise, skeletal, muscle
- GSE249921 Skeletal Muscle Transcriptome of Young and Old Humans and Response to Training 185 samples shares skeletal, muscle
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.