Selective modulation of gene expression in activated normal human peripheral blood mononuclear cells by store-operated calcium entry blocker BTP2
RNA-seq (gene expression) · human · 40 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
- 40 samples: 40 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
- Single-cell transcriptomics reveals targeted modulation of inflammatory repertoire by SOCE blockersbioRxiv : the preprint server for biology · 2025
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 GSE295784_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 PRJNA1256360 and SRA study SRP581956. 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 40 sample titles: 40 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.
- GSM8957644 bulkRNAseq_Donor1_PBMC(Control)
- GSM8957645 bulkRNAseq_Donor1_PBMC+PHA
- GSM8957646 bulkRNAseq_Donor1_PBMC+BTP2
- GSM8957647 bulkRNAseq_Donor1_PBMC+PHA+BTP2
- GSM8957648 bulkRNAseq_Donor1_PBMC+CM4620
- GSM8957649 bulkRNAseq_Donor1_PBMC+PHA+CM4620
- GSM8957650 bulkRNAseq_Donor2_PBMC(Control)
- GSM8957651 bulkRNAseq_Donor2_PBMC+PHA
- GSM8957652 bulkRNAseq_Donor2_PBMC+BTP2
- GSM8957653 bulkRNAseq_Donor2_PBMC+PHA+BTP2
- GSM8957654 bulkRNAseq_Donor2_PBMC+CM4620
- GSM8957655 bulkRNAseq_Donor2_PBMC+PHA+CM4620
- GSM8957656 bulkRNAseq_Donor3_PBMC(Control)
- GSM8957657 bulkRNAseq_Donor3_PBMC+PHA
- GSM8957658 bulkRNAseq_Donor3_PBMC+BTP2
- GSM8957659 bulkRNAseq_Donor3_PBMC+PHA+BTP2
- GSM8957660 bulkRNAseq_Donor3_PBMC+CM4620
- GSM8957661 bulkRNAseq_Donor3_PBMC+PHA+CM4620
- GSM8957662 bulkRNAseq_Donor4_PBMC(Control)
- GSM8957663 bulkRNAseq_Donor4_PBMC+PHA
- GSM8957664 bulkRNAseq_Donor4_PBMC+BTP2
- GSM8957665 bulkRNAseq_Donor4_PBMC+PHA+BTP2
- GSM8957666 bulkRNAseq_Donor4_PBMC+CM4620
- GSM8957667 bulkRNAseq_Donor4_PBMC+PHA+CM4620
- GSM8957668 scRNAseq_Donor1_Replicate1_GEX
- GSM8957669 scRNAseq_Donor1_Replicate2_GEX
- GSM8957670 scRNAseq_Donor2_Replicate1_GEX
- GSM8957671 scRNAseq_Donor2_Replicate2_GEX
- GSM8957672 scRNAseq_Donor3_Replicate1_GEX
- GSM8957673 scRNAseq_Donor3_Replicate2_GEX
- GSM8957674 scRNAseq_Donor4_Replicate1_GEX
- GSM8957675 scRNAseq_Donor4_Replicate2_GEX
- GSM8957676 scRNAseq_Donor1_Replicate1_CMP
- GSM8957677 scRNAseq_Donor1_Replicate2_CMP
- GSM8957678 scRNAseq_Donor2_Replicate1_CMP
- GSM8957679 scRNAseq_Donor2_Replicate2_CMP
- GSM8957680 scRNAseq_Donor3_Replicate1_CMP
- GSM8957681 scRNAseq_Donor3_Replicate2_CMP
- GSM8957682 scRNAseq_Donor4_Replicate1_CMP
- GSM8957683 scRNAseq_Donor4_Replicate2_CMP
- GSE327707 Sorted bulk RNA-seq profiling of human peripheral blood mononuclear cell populations across diverse in vitro immune stimuli 150 samples shares mononuclear, peripheral
- GSE202216 Rhinovirus-induced gene expression patterns that distinguish between neutrophilic asthma and other asthma inflammatory phenotypes in human peripheral blood mononuclear cells 102 samples shares mononuclear, peripheral
- GSE326415 Paired Transcriptomic Profiling of Airspace and Peripheral Blood Mononuclear Cells in Severe ARDS 63 samples shares mononuclear, peripheral
- GSE280114 Bulk RNA-seq data of orbital fibroblasts and peripheral blood mononuclear cells (PBMCs) from thyroid eye disease patients 59 samples shares mononuclear, peripheral
- GSE295224 Dual single-cell and bulk RNA sequencing reveal transcriptional profiles underlying heterogenous host-parasite interactions in human peripheral blood mononuclear cells 42 samples shares mononuclear, peripheral
- GSE326320 Integrative transcriptomic, network, and genomic analysis of peripheral blood mononuclear cells identifies candidate gene drivers of dupilumab clinical response in atopic dermatitis patients 36 samples shares mononuclear, peripheral
- GSE267718 Single cell RNA sequencing (scRNAseq) of urine-derived cells, peripheral blood mononuclear (PBMC), and tumor cells from bladder cancer patients. 33 samples shares mononuclear, peripheral
- GSE318371 Peripheral blood mononuclear cells single-cell landscape of newly diagnosed NK/T cell lymphoma patients 32 samples shares mononuclear, peripheral
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.