Mechanism of quercetin in the treatment of endometriosis based on network pharmacology and transcriptome sequencing
RNA-seq (gene expression) · human · 12 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
- 12 samples: 6 × DG vs 6 × NCGroups 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 GSE281569_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 PRJNA1184737 and SRA study SRP544523. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 12 samples.
How we read this: 2 replicated groups read from 12 sample titles; they account for 12 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.
- GSM8623786 DG1 DG
- GSM8623787 DG2 DG
- GSM8623788 DG3 DG
- GSM8623789 DG4 DG
- GSM8623790 DG5 DG
- GSM8623791 DG6 DG
- GSM8623792 NC1 NC
- GSM8623793 NC2 NC
- GSM8623794 NC3 NC
- GSM8623795 NC4 NC
- GSM8623796 NC5 NC
- GSM8623797 NC6 NC
- GSE192636 mRNA, lncRNA and circular RNA expression profiles and ceRNA network construction of granulosa cells in ovarian endometriosis 10 samples shares endometriosis, network
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- GSE310252 Transcriptome-based classification of resected pancreatic ductal adenocarcinoma enhances prognostic modelling accuracy of overall survival following adjuvant treatment 118 samples shares treatment
- GSE290695 Identification of Crohn’s disease subtypes in single cell RNA sequencing signatures of treatment naïve samples across the gastrointestinal tract 95 samples shares treatment
- GSE283703 Transcriptome analysis of adult patients with severe Obstructive Sleep Apnea before and after CPAP treatment. 71 samples shares treatment
- GSE334345 Exploratory investigation of changes in blood transcriptome following mepolizumab treatment for asthma 54 samples shares treatment
- GSE319641 RNA-Seq profiling of pre- and on-treatment tumor samples from breast cancer patients enrolled in the NeoTRIP trial. 401 samples shares treatment
- GSE254951 Impact of Hydroxycarbamide Treatment on the Whole Blood Transcriptome in Sickle Cell Disease 50 samples shares treatment
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.