Lipid metabolism dysregulation in solar lentigo: a multi-system-level analysis reveals membrane instability and energy homeostasis disruption
RNA-seq (gene expression) · human · 14 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
- 14 samples: 7 × Lentigo vs 7 × ControlGroups 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
- Lipid metabolism dysregulation in solar lentigo: a multi-system-level analysis reveals membrane instability and energy homeostasis disruptionFrontiers in cell and developmental biology · 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 GSE318414_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 PRJNA1418692. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 14 samples.
How we read this: 2 replicated groups read from 14 sample titles; they account for 14 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.
- GSM9494041 Lentigo 1 Lentigo
- GSM9494048 Lentigo 2 Lentigo
- GSM9494052 Lentigo 3 Lentigo
- GSM9494054 Lentigo 4 Lentigo
- GSM9494057 Lentigo 5 Lentigo
- GSM9494062 Lentigo 6 Lentigo
- GSM9494063 Lentigo 7 Lentigo
- GSM9494067 Control 1 Control
- GSM9494068 Control 2 Control
- GSM9494069 Control 3 Control
- GSM9494070 Control 4 Control
- GSM9494071 Control 5 Control
- GSM9494072 Control 6 Control
- GSM9494073 Control 7 Control
- GSE271896 Deep longitudinal immune profiling reveals reprogramming of memory T cells that links to B cell dysregulation with age 868 samples shares dysregulation
- GSE260603 Dissecting depression symptoms: multi-omics clustering uncovers immune-related subgroups and cell-type specific dysregulation 273 samples shares dysregulation
- GSE275067 Deep longitudinal immune profiling reveals reprogramming of memory T cells that links to B cell dysregulation with age. 252 samples shares dysregulation
- GSE264443 Dynamic gene expression analysis reveals distinct severity phases of immune and cellular dysregulation in COVID-19 189 samples shares dysregulation
- GSE338964 Computational modeling and preclinical evaluation support targeting somatic instability for Huntington’s disease treatment. 104 samples shares instability
- GSE277813 VAV3 antagonizes Skeletal Muscle Disulfidptosis to maintain Glucose Homeostasis in Type 2 Diabetes 99 samples shares homeostasis
- GSE330022 Multidimensional Exposure Architecture Shapes Vaping-Associated Transcriptomic Dysregulation in Oral Epithelium 83 samples shares dysregulation
- GSE269826 Conserved patterns of transcriptional dysregulation, heterogeneity and cell states in clear cell kidney cancer [scRNA-seq] 79 samples shares dysregulation
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.