Transcriptome-Proteome analysis of human naive and memory B cell subsets reveal isotype and subclass-specific phenotypes
RNA-seq (gene expression) · human · 59 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
- 59 samples: 9 conditions, mostly with about 8 replicates eachGroups 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
- Transcriptome-Proteome Analysis of Human Naive and Memory B Cell Subsets Reveals Isotype and Subclass-Specific PhenotypesEuropean journal of immunology · 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 GSE298777_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 PRJNA1271092 and SRA study SRP589328. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 59 samples.
How we read this: 9 replicated groups read from 59 sample titles; they account for 59 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.
- GSM9023066 IgMD_Donor 1 IgMD_Dono
- GSM9023067 IgM_Donor 1 IgM_Dono
- GSM9023068 IgA1_Donor 1 IgA1_Dono
- GSM9023069 IgA2_Donor 1 IgA2_Dono
- GSM9023070 IgG1_Donor 1 IgG1_Dono
- GSM9023071 IgG2_Donor 1 IgG2_Dono
- GSM9023072 IgG4_Donor 1 IgG4_Dono
- GSM9023073 Naive_Donor 2 Naive_Dono
- GSM9023074 IgMD_Donor 2 IgMD_Dono
- GSM9023075 IgM_Donor 2 IgM_Dono
- GSM9023076 IgA1_Donor 2 IgA1_Dono
- GSM9023077 IgA2_Donor 2 IgA2_Dono
- GSM9023078 IgG1_Donor 2 IgG1_Dono
- GSM9023079 IgG2_Donor 2 IgG2_Dono
- GSM9023080 IgG3_Donor 2 IgG3_Dono
- GSM9023081 Naive_Donor 3 Naive_Dono
- GSM9023082 IgMD_Donor 3 IgMD_Dono
- GSM9023083 IgM_Donor 3 IgM_Dono
- GSM9023084 IgA1_Donor 3 IgA1_Dono
- GSM9023085 IgA2_Donor 3 IgA2_Dono
- GSM9023086 IgG1_Donor 3 IgG1_Dono
- GSM9023087 IgG2_Donor 3 IgG2_Dono
- GSM9023088 IgG3_Donor 3 IgG3_Dono
- GSM9023089 Naive_Donor 4 Naive_Dono
- GSM9023090 IgMD_Donor 4 IgMD_Dono
- GSM9023091 IgA1_Donor 4 IgA1_Dono
- GSM9023092 IgA2_Donor 4 IgA2_Dono
- GSM9023093 IgG1_Donor 4 IgG1_Dono
- GSM9023094 IgG2_Donor 4 IgG2_Dono
- GSM9023095 IgG3_Donor 4 IgG3_Dono
- GSM9023096 IgG4_Donor 4 IgG4_Dono
- GSM9023097 IgA1_Donor 5 IgA1_Dono
- GSM9023098 IgA2_Donor 5 IgA2_Dono
- GSM9023099 IgG1_Donor 5 IgG1_Dono
- GSM9023100 IgG2_Donor 5 IgG2_Dono
- GSM9023101 IgG3_Donor 5 IgG3_Dono
- GSM9023102 IgG4_Donor 5 IgG4_Dono
- GSM9023103 Naive_Donor 6 Naive_Dono
- GSM9023104 IgMD_Donor 6 IgMD_Dono
- GSM9023105 IgM_Donor 6 IgM_Dono
+ 19 more — browse all 59 samples with per-sample file links →
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- GSE295447 On target: Transcriptomic analysis of 12 human iPSC-derived cell phenotypes shows precision in an extensive pharmacological investigation [set 2] 840 samples shares phenotypes
- GSE295444 On target: Transcriptomic analysis of 12 human iPSC-derived cell phenotypes shows precision in an extensive pharmacological investigation [set 1] 840 samples shares phenotypes
- GSE319130 Multi-omic analysis reveals molecular subtypes with distinct immunological phenotypes in SLE [RNA-Seq] 804 samples shares phenotypes
- GSE267774 Specific CD4+ T cell phenotypes associate with bacterial control in people who ‘resist’ infection with Mycobacterium tuberculosis 3076 samples shares phenotypes
- GSE288604 Whole blood transcriptomics characterize molecular phenotypes of pulmonary Mycobacterium avium complex disease 200 samples shares phenotypes
- GSE270863 High Dimensional Analysis of Sputum Cell Transcriptomes Identifies novel pathways associated with Clinical Phenotypes of Asthma 24 samples shares phenotypes
- GSE269335 Single-cell multimodal profiling of monocytes reveals diverse phenotypes and alterations linked to cardiovascular disease risks 118 samples shares phenotypes
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.