Investigating the Therapeutic Potential of the Antioxidant Epigallocatechin Gallate in Fetal Alcohol Spectrum Disorders: Cognition and RNASeq
RNA-seq (gene expression) · human · 16 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
- 16 samples: 16 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
- Cognitive and transcriptomic effects of Epigallocatechin gallate in fetal alcohol spectrum disordersScientific reports · 2026
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 GSE307141_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 PRJNA1314641 and SRA study SRP617419. 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 16 sample titles: 16 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.
- GSM9217251 Sample 135, baseline (t0)
- GSM9217252 Sample 143, baseline (t0)
- GSM9217253 Sample 149, baseline (t0)
- GSM9217254 Sample 161, baseline (t0)
- GSM9217255 Sample 164, baseline (t0)
- GSM9217256 Sample 174, baseline (t0)
- GSM9217257 Sample 160, baseline (t0)
- GSM9217258 Sample 146, baseline (t0)
- GSM9217259 Sample 135, 12 months EGCG treatment (t12)
- GSM9217260 Sample 143, 12 months EGCG treatment (t12)
- GSM9217261 Sample 149, 12 months EGCG treatment (t12)
- GSM9217262 Sample 161, 12 months EGCG treatment (t12)
- GSM9217263 Sample 164, 12 months EGCG treatment (t12)
- GSM9217264 Sample 174, 12 months EGCG treatment (t12)
- GSM9217265 Sample 160, 12 months EGCG treatment (t12)
- GSM9217266 Sample 146, 12 months EGCG treatment (t12)
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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.