The Effect of Weight Loss on Metabolic Processes of the Abdominal Subcutaneous Adipose Tissue: An Exploratory Study using total RNA Next Generation Sequencing
RNA-seq (gene expression) · human · 18 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
- 18 samples: 18 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.
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 GSE329809_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 PRJNA1461868 and SRA study SRP697145. 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 18 sample titles: 18 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.
- GSM9711671 22038a001 = B9 SS1
- GSM9711672 22038a004 = B9 IS2
- GSM9711673 22038a006 = B3 SS2
- GSM9711674 22038a008 = B3 IS2
- GSM9711675 22038a009 = B5 SS1
- GSM9711676 22038a011 = B5 IS1
- GSM9711677 22038a013 = C9 SS1
- GSM9711678 22038a016 = C9 IS2
- GSM9711679 22038a018 = C11 SS2
- GSM9711680 22038a020 = C11 IS2
- GSM9711681 22038a021 = C10 SS1
- GSM9711682 22038a023 = C10 IS1
- GSM9711683 22038a025 = A8 SS1
- GSM9711684 22038a028 = A8 IS2
- GSM9711685 22038a030 = A7 SS2
- GSM9711686 22038a032 = A7 IS2
- GSM9711687 22038a033 = A13 SS1
- GSM9711688 22038a036 = A13 IS2
- GSE303983 Molecular responses in abdominal subcutaneous adipose tissue after a session of endurance exercise: effects of exercise intensity 90 samples shares subcutaneous, abdominal, adipose
- GSE287627 Human Subcutaneous abdominal adipose tissue RNAseq - NYC sample 19 samples shares subcutaneous, abdominal, adipose
- GSE235529 snRNA-Seq from Younger and Older human abdominal subcutaneous white adipose tissue 10 samples shares subcutaneous, abdominal, adipose
- GSE255626 Next generation sequencing from primary glioblastoma patient tissues (Total RNA-seq) 109 samples shares generation, total
- GSE245948 A dynamic subcutaneous adipose transcriptome of human insulin resistance identifies a molecular predisposition shared with visceral adipose tissue 76 samples shares subcutaneous, adipose
- GSE302701 Single-nucleus RNA sequencing of human subcutaneous adipose tissue biopsies from 59 Finnish participants. 59 samples shares subcutaneous, adipose
- GSE316698 Single-nucleus RNA sequencing of human subcutaneous adipose tissue biopsies from 49 Mexican participants 49 samples shares subcutaneous, adipose
- GSE306796 Human Subcutaneous ABD/GLU/Thi adipose tissue RNAseq - NYC sample 32 samples shares subcutaneous, adipose
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.