Spatial transcriptomics and in situ immune cell profiling of the host ectocervical landscape of HIV infected Kenyan sex working women
Spatial transcriptomics · human · 10 samples
- What it is
- Spatial transcriptomicsGene activity measured with its position in a tissue section.
- Organism
- Homo sapiens (human)
- Samples
- 10 samples: 10 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
- Spatial transcriptomics and in situ immune cell profiling of the host ectocervical landscape of HIV infected Kenyan sex working womenFrontiers in immunology · 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 GSE290350_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: Spatial studies usually ship Space Ranger style folders (count matrix plus tissue images). Look for them among the supplementary files.
Also filed as BioProject PRJNA1227522. 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 10 sample titles: 10 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.
- GSM8811056 P004_ST
- GSM8811057 P008_ST
- GSM8811058 P026_ST
- GSM8811059 P044_ST
- GSM8811060 P067_ST
- GSM8811061 P007_ST
- GSM8811062 P016_ST
- GSM8811063 P023_ST
- GSM8811064 P028_ST
- GSM8811065 P047_ST
- GSE328010 RNA sequencing of naïve, activated and HIV-1 infected CD4+ T cells 9 samples shares hiv, infected
- GSE299348 Single-cell epigenetic, transcriptional, protein, and TCR states of HIV-1-infected cells in gut 117 samples shares hiv, infected
- GSE305896 Selective targeting of HIV infected clones by cognate peptide stimulation and antiproliferative drugs 10 samples shares hiv, infected
- GSE271370 Spatial transcriptomics unveils the in situ cellular and molecular hallmarks of the lung in fatal COVID-19 23 samples shares spatial, situ
- GSE279688 The role of LEDGF in transcription is exploited by HIV-1 to position integration 56 samples shares hiv
- GSE318861 Quantitative analysis of Tat-dependent and host-driven HIV transcription by ChIP-seq and RNA-seq 52 samples shares hiv
- GSE271689 Enhancing Immunotherapy Outcomes: Spatial Multi-Omics Predictive Models for Non-Small Cell Lung Cancer 586 samples shares spatial
- GSE271676 Spatial Transcriptional Landscape of Human Heart Failure 178 samples shares spatial
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.