Single-cell profiling reveals a critical role for hypoxia-inducible factor-1a signaling in leukocytes during human craniotomy infection
Single-cell RNA-seq · human · 14 samples
- What it is
- Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
- Organism
- Homo sapiens (human)
- Samples
- 14 samples: 4 × Blood, Patient vs 4 × Bone Flap, Patient vs 2 × Subgalea, PatientGroups 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
- Tissue niche influences immune and metabolic profiles to Staphylococcus aureus biofilm infectionNature communications · 2024
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 GSE249319_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.
Also filed as BioProject PRJNA1048516 and SRA study SRP475748. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 10 samples.
How we read this: 3 replicated groups read from 14 sample titles; they account for 10 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.
- GSM7933979 Blood, Patient 11 Blood, Patient
- GSM7933980 Bone Flap, Patient 11 Bone Flap, Patient
- GSM7933981 Subgalea and Epidural, Patient 11
- GSM7933982 Blood, Patient 14 Blood, Patient
- GSM7933983 Bone Flap, Patient 14 Bone Flap, Patient
- GSM7933984 Subgalea, Patient 14 Subgalea, Patient
- GSM7933985 Blood, Patient 15 Blood, Patient
- GSM7933986 Bone Flap, Patient 15 Bone Flap, Patient
- GSM7933987 Epigalea, Patient 15
- GSM7933988 Subgalea, Patient 15 Subgalea, Patient
- GSM7933989 Blood, Patient 7 Blood, Patient
- GSM7933990 Bone Flap, Patient 7 Bone Flap, Patient
- GSM7933991 Dura, Patient 7
- GSM7933992 Intracranial Tissue, Patient 7
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- GSE243013 A single-cell atlas of immune heterogeneity in anti-PD1-treated non-small cell lung cancer 243 samples shares single-cell
- GSE263733 Single-cell transcriptome analysis reveals subtype-specific clonal evolution and microenvironmental changes in liver metastasis of pancreatic adenocarcinoma and their clinical implications 218 samples shares single-cell
- GSE282122 A longitudinal single-cell atlas of anti-tumour necrosis factor treatment in inflammatory bowel disease 216 samples shares single-cell
- GSE328048 Single-cell transcriptome reveals keratinocyte subclusters that contribute to altered differentiation and inflammatory responses in atopic dermatitis 116 samples shares single-cell
- GSE327167 Single-cell RNA-seq profiling of pleural mesothelioma and comparator pleural specimens 113 samples shares single-cell
- GSE266265 Endometrial Insights: Unmasking Endometriosis through Single-Cell Profiling and AI-Based Prediction 60 samples shares single-cell
- GSE287301 Single-cell RNA-sequencing of HNSCC-infiltrating T cells 48 samples shares single-cell
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.