Differentiation-induced reduction in functional diversity restricts the ability of cytomegalovirus-specific CD8 T cells to eliminate virus-infected cells
RNA-seq (gene expression) · human · 31 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
- 31 samples: 25 distinct titles, 3 of them repeatedGroups 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
- Differentiation-induced reduction in functional diversity restricts the ability of cytomegalovirus-specific CD8 T cells to eliminate virus-infected cellsEBioMedicine · 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 GSE289829_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 PRJNA1225154 and SRA study SRP564604. Searching any of these in the dataset finder brings you back here.
How we read this: Read from 31 sample titles: 25 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.
- GSM8799883 NLV-specific T cells from HF donors , GEX_GEM1
- GSM8799884 NLV-specific T cells from HF donors , GEX_GEM2
- GSM8799885 NLV-specific T cells from HF donors , GEX_GEM3
- GSM8799886 NLV-specific T cells from HF donors , HTO_ADT_GEM1
- GSM8799887 NLV-specific T cells from HF donors , HTO_ADT_GEM2
- GSM8799888 NLV-specific T cells from HF donors , HTO_ADT_GEM3
- GSM8799889 NLV-specific T cells from HF donors , VDJ_GEM1
- GSM8799890 NLV-specific T cells from HF donors , VDJ_GEM2
- GSM8799891 NLV-specific T cells from HF donors , VDJ_GEM3
- GSM8799892 A_Low_freq, BulkRNA
- GSM8799893 B_Low_freq. BulkRNA
- GSM8799894 D_High_freq, BulkRNA
- GSM8799895 H_High_freq, BulkRNA
- GSM8799896 G_Low_freq, BulkRNA
- GSM8799897 I_Low_freq, BulkRNA
- GSM8799898 J_High_freq, BulkRNA
- GSM8799899 10.2_High_freq, BulkRNA
- GSM8799900 6.9.2_Low_freq, BulkRNA
- GSM8799901 6.9.3_High_freq, BulkRNA
- GSM8799902 6.10.1_Low_freq, BulkRNA
- GSM8799903 A_Low_freq, BulkTCR
- GSM8799904 B_Low_freq. BulkTCR
- GSM8799905 D_High_freq, BulkTCR
- GSM8799906 H_High_freq, BulkTCR
- GSM8799907 G_Low_freq, BulkTCR
- GSM8799908 I_Low_freq, BulkTCR
- GSM8799909 J_High_freq, BulkTCR
- GSM8799910 10.2_High_freq, BulkTCR
- GSM8799911 6.9.2_Low_freq, BulkTCR
- GSM8799912 6.9.3_High_freq, BulkTCR
- GSM8799913 6.10.1_Low_freq, BulkTCR
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- GSE206325 Intratumoral mregDC and Tfh-like niches enable local reinvigoration of CD8 T cells following PD-1 blockade 510 samples shares cd8
- GSE272993 Combination anti-PD-1 and anti-CTLA-4 therapy generates waves of clonal responses that include progenitor-exhausted CD8 T cells [dataset 1] 360 samples shares cd8
- GSE225063 Blockade of LAG-3 and PD-1 leads to co-expression of cytotoxic and exhaustion gene modules in CD8+ T cells to promote antitumor immunity 256 samples shares cd8
- GSE288199 Distinct CD8+ T cell dynamics associate with response to neoadjuvant cancer immunotherapies 180 samples shares cd8
- GSE288856 Clonal CD8+ T Cells Populate the Leptomeninges and Coordinate with Immune Cells in Human Degenerative Brain Diseases 113 samples shares cd8
- GSE308745 The Cd4+ T cell population Partners with Tpex CD8 T cells to mediate Antitumor Immunity in the Tumor Microenvironment.[PB cohort2] 87 samples shares cd8
- GSE298811 Immune dysregulation and stem-like CD8+ T cell enrichment in type 1 diabetes pancreatic lymph nodes 57 samples shares cd8
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.