Transcriptome regulation in T-cells and monocytes in patients with Common Variable Immunodeficiency
RNA-seq (gene expression) · human · 20 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
- 20 samples: 20 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
- Distinct Proteomic and Transcriptomic Profiles in T-cells and Monocytes in Patients with Common Variable Immunodeficiency: an Exploratory StudyJournal of clinical immunology · 2026
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 GSE299706_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 PRJNA1276100 and SRA study SRP591700. 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 20 sample titles: 20 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.
- GSM9044506 S01,CD3_CVID, rep 1
- GSM9044507 S02,CD3_CVID, rep 2
- GSM9044508 S03,CD3_CVID, rep 3
- GSM9044509 S04,CD3_CVID, rep 4
- GSM9044510 S05,CD3_CVID, rep 5
- GSM9044511 S06,CD3_control, rep 1
- GSM9044512 S07,CD3_control, rep 2
- GSM9044513 S08,CD3_control, rep 3
- GSM9044514 S09,CD3_control, rep 4
- GSM9044515 S10,CD3_control, rep 5
- GSM9044516 S11,CD14_CVID, rep 1
- GSM9044517 S12,CD14_CVID, rep 2
- GSM9044518 S13,CD14_CVID, rep 3
- GSM9044519 S14,CD14_CVID, rep 4
- GSM9044520 S15,CD14_CVID, rep 5
- GSM9044521 S16,CD14_control, rep 1
- GSM9044522 S17,CD14_control, rep 2
- GSM9044523 S18,CD14_control, rep 3
- GSM9044524 S19,CD14_control, rep 4
- GSM9044525 S20,CD14_control, rep 5
- GSE330223 Convergence of cytokine dysregulation and antibody deficiency in common variable immunodeficiency with inflammatory complications 42 samples shares immunodeficiency, variable, common
- GSE274117 Expansion of cytotoxic CD4 T-cell clusters in lymph nodes of patients with Common Variable Immunodeficiency 8 samples shares immunodeficiency, variable, common
- GSE307095 RNA-seq profiling of resting naive and CD27bright memory B cells and in vitro activated CD27bright memory B cells reveals differences in B-cell activation patterns in common variable immunodeficiency (CVID) 50 samples shares immunodeficiency, variable, common
- GSE205672 Transcriptomes of human PBMCs and monocytes in sepsis patients 460 samples shares monocytes
- GSE252020 Decoding CD4+ T cell transcriptome in giant cell arteritis: novel pathways and altered cross-talk with monocytes [RNA-seq] 98 samples shares monocytes
- GSE279719 Human CD14+ monocytes from early inflammatory arthritis patients before and after a 5day-and 30day-period of methotrexate treatment 72 samples shares monocytes
- GSE295173 Multi-modal single-cell sequencing reveals network transition in circulating monocytes that aligns with faster recovery in trauma patients and favors a response to M-CSF [scRNA-Seq] 30 samples shares monocytes
- GSE267600 Mutations disrupting the kinase domain of IKKα lead to immunodeficiency and immune dysregulation in humans 30 samples shares immunodeficiency
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.