Single cell multiomic analysis of the impact of Delta-9-tetrahydrocannabinol on HIV infected CD4 T cells
Single-cell RNA-seq · human · 16 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
- 16 samples: 16 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.
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 GSE313059_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 PRJNA1378196 and SRA study SRP653799. 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 16 sample titles: 16 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.
- GSM9359918 PBMCs, 500nMTHC, 0hr, rep1 scRNA
- GSM9359919 PBMCs, 500nMTHC, 3hr, rep1 scRNA
- GSM9359920 PBMCs, 500nMTHC, 6hr, rep1 scRNA
- GSM9359921 PBMCs, 500nMTHC, 12hr, rep1 scRNA
- GSM9359922 PBMCs, 500nMTHC, 0hr, rep2 scRNA
- GSM9359923 PBMCs, 500nMTHC, 6hr, rep2 scRNA
- GSM9359924 PBMCs, 500nMTHC, 0hr, rep3 scRNA
- GSM9359925 PBMCs, 500nMTHC, 6hr, rep3 scRNA
- GSM9366820 PBMCs, 500nMTHC, 0hr, rep1 scATAC
- GSM9366821 PBMCs, 500nMTHC, 3hr, rep1 scATAC
- GSM9366822 PBMCs, 500nMTHC, 6hr, rep1 scATAC
- GSM9366823 PBMCs, 500nMTHC, 12hr, rep1 scATAC
- GSM9366824 PBMCs, 500nMTHC, 0hr, rep2 scATAC
- GSM9366825 PBMCs, 500nMTHC, 6hr, rep2 scATAC
- GSM9366826 PBMCs, 500nMTHC, 0hr, rep3 scATAC
- GSM9366827 PBMCs, 500nMTHC, 6hr, rep3 scATAC
- GSE247196 Productively HIV-1 infected and bystander primary human CD4+ T-cells 18 samples shares hiv, cd4, infected
- GSE328010 RNA sequencing of naïve, activated and HIV-1 infected CD4+ T cells 9 samples shares hiv, cd4, infected
- GSE299348 Single-cell epigenetic, transcriptional, protein, and TCR states of HIV-1-infected cells in gut 117 samples shares hiv, infected
- GSE178178 Transcriptomic analysis of Hsp90 inhibitor (Hsp90i)-treated HIV-infected pediatric tonsillar mononuclear cells 16 samples shares hiv, infected
- GSE299125 Paracrine Signals from HIV-1 Infected Immune Cells Reprogram Cervical Cancer Pathways 35 samples shares hiv, infected
- GSE291361 Differential impact of inflammatory microglia signals and chronic HIV-1 Tat exposure on A1-like polarization of astrocytes 24 samples shares hiv, impact
- GSE305896 Selective targeting of HIV infected clones by cognate peptide stimulation and antiproliferative drugs 10 samples shares hiv, infected
- GSE279688 The role of LEDGF in transcription is exploited by HIV-1 to position integration 56 samples shares hiv
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.