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Unveiling Multi-Omics and Immune Landscapes in COVID-19 Patients' Ovaries Microenvironment for Oocyte Competency Biomarkers Identification

GSE282892 Homo sapiens (human) RNA-seq (gene expression) 26 samples Submitted 2024/12/25 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 26 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
26 samples: 17 × Non-COVID19 vs 9 × COVID19Groups 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.
Summary (written by the submitters)
Background: The outbreak of coronavirus disease 2019 (COVID-19) poses a considerable health threat to humanity, with potential implications for the ovarian microenvironment remaining uncertain. Methods: Transcriptomic and proteomic analyses of ovarian granulosa cells, along with metabolomic and lipidomic profiling of follicular fluid, were conducted on 17 non-COVID-19 cases and 9 COVID-19 cases.
Read the full summary ↓
This study received approval from the ethics committee (KYLL-2022-581). Generalized estimating equations model was performed to identify oocyte competency biomarkers. Additionally, cell proliferation, apoptosis, and altered pathways were examined following lentivirus transfection. Methods: Transcriptomic and proteomic analyses of ovarian granulosa cells, along with metabolomic and lipidomic profiling of follicular fluid, were conducted on 17 non-COVID-19 cases and 9 COVID-19 cases. This study received approval from the ethics committee (KYLL-2022-581). Generalized estimating equations model was performed to identify oocyte competency biomarkers. Additionally, cell proliferation, apoptosis, and altered pathways were examined following lentivirus transfection. Conclusions: By integrating untargeted metabolomic and lipidomic features, we identified biomarkers indicative of oocyte competency influenced by COVID-19.
This dataset
Open GSE282892 in finder → Find more human RNA-seq datasets →
Download · which file do I need?

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.

1 · Just have a look

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.

Series matrix ↓
2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE282892_RAW.tar (it can run to tens of gigabytes).

All supplementary files ↗ Whole study · RAW.tar ↓
3 · Start from the raw reads

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.

Raw reads on ENA ↗

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 PRJNA1190953 and SRA study SRP547726. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
17 × Non-COVID19 vs 9 × COVID19

Supports a between-group comparison across 26 samples.

How we read this: 2 replicated groups read from 26 sample titles; they account for 26 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.

Samples in this study
Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

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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.