Immune Checkpoint Molecules as Biomarkers of Outcomes in Staphylococcus aureus Bone Infections
RNA-seq (gene expression) · human · 18 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
- 18 samples: 18 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.
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 GSE269658_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 PRJNA1123174 and SRA study SRP513423. 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 18 sample titles: 18 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.
- GSM8324285 Sample_INF_34_058_BT_Bcell
- GSM8324286 Sample_INF_34_058_BT_GEX
- GSM8324287 Sample_INF_34_058_BT_Tcell
- GSM8324288 Sample_INF_56_059_BT_Bcell
- GSM8324289 Sample_INF_56_059_BT_GEX
- GSM8324290 Sample_INF_56_059_BT_Tcell
- GSM8324291 Sample_STE_058_BT_Bcell
- GSM8324292 Sample_STE_058_BT_GEX
- GSM8324293 Sample_STE_058_BT_Tcell
- GSM8324294 Sample_STE_059_BT_Bcell
- GSM8324295 Sample_STE_059_BT_GEX
- GSM8324296 Sample_STE_059_BT_Tcell
- GSM8324297 Sample_INF_057_Bcell
- GSM8324298 Sample_INF_057_GEX
- GSM8324299 Sample_INF_057_Tcell
- GSM8324300 Sample_STE_075_Bcell
- GSM8324301 Sample_STE_057_GEX
- GSM8324302 Sample_STE_057_Tcell
- GSE287540 Transcriptomic and proteomic characterization of cell and protein biomarkers of checkpoint inhibitor-induced liver injury [bulk RNA-seq] 128 samples shares checkpoint, biomarkers
- GSE287541 Transcriptomic and proteomic characterization of cell and protein biomarkers of checkpoint inhibitor-induced liver injury [scRNA-seq] 92 samples shares checkpoint, biomarkers
- GSE76262 Expression data of induced sputum from Unbiased BIOmarkers in Prediction of REspiratory Disease outcomes (U-BIOPRED) Project 139 samples shares biomarkers, outcomes
- GSE280232 Divergent clinical and immunologic outcomes based on STK11 co-mutation status in resectable KRAS-mutant lung cancers following neoadjuvant immune checkpoint blockade 42 samples shares checkpoint, outcomes
- GSE270047 Analytical performance of OncoPrism-HNSCC, an RNA-based assay to inform immune checkpoint inhibitor treatment decisions for recurrent/metastatic head and neck squamous cell carcinoma 434 samples shares checkpoint
- GSE318645 Dual Immune Checkpoint Blockade Induces Distinct Systemic and Intratumoral Immune Activation in Recurrent Glioblastoma 226 samples shares checkpoint
- GSE313307 Systemic infections alter cortical transcriptional signatures in Alzheimer′s disease 202 samples shares infections
- GSE325054 Time-Resolved Multi-Omics Identify Biomarkers of Immediate Reactions to mRNA Vaccination [RNA-Seq] 187 samples shares biomarkers
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.