Pharmacological Targeting of REV-ERBa/bPromotes HIV-1 Reactivation in CD4+T-Cells while Limiting Cell-to-Cell Dissemination
RNA-seq (gene expression) · human · 21 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
- 21 samples: 21 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 GSE253420_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 PRJNA1065492 and SRA study SRP484088. 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 21 sample titles: 21 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.
- GSM8020426 ALET-HIV2,DMSO
- GSM8020427 ALET-HIV6,DMSO
- GSM8020428 ALET-HIV6,SR9011 5 uM
- GSM8020429 ALET-HIV6,SR8278 10 uM
- GSM8020430 ALET-HIV7,DMSO
- GSM8020431 ALET-HIV7,SR9011 5 uM
- GSM8020432 ALET-HIV7,SR8278 10 uM
- GSM8020433 Leuka CLOCK6,DMSO
- GSM8020434 Leuka CLOCK6,SR9011 5 uM
- GSM8020435 Leuka CLOCK6,SR8278 10 uM
- GSM8020436 Leuka ER-1293,DMSO
- GSM8020437 ALET-HIV2,SR9011 5 uM
- GSM8020438 Leuka ER-1293,SR9011 5 uM
- GSM8020439 Leuka ER-1293,SR8278 10 uM
- GSM8020440 ST050,DMSO
- GSM8020441 ST050,SR9011 5 uM
- GSM8020442 ST050,SR8278 10 uM
- GSM8020443 ALET-HIV2,SR8278 10 uM
- GSM8020444 ALET-HIV5,DMSO
- GSM8020445 ALET-HIV5,SR9011 5 uM
- GSM8020446 ALET-HIV5,SR8278 10 uM
- GSE329693 Microbiome-Derived Metabolites Shape CD4⁺ T-Cell Differentiation and Immune Aging in Chronic HIV-1 Infection [RNA-Seq] 36 samples shares hiv-1, cd4
- GSE319139 The HIV-1 Vpr R77Q mutant alters host apoptotic gene regulation in CD4+ T cells 33 samples shares hiv-1, cd4
- GSE280563 HIV-1 m6A methylome investigation by m6A-SAC-seq [CD4+ T cells] 12 samples shares hiv-1, cd4
- GSE328010 RNA sequencing of naïve, activated and HIV-1 infected CD4+ T cells 9 samples shares hiv-1, cd4
- GSE247196 Productively HIV-1 infected and bystander primary human CD4+ T-cells 18 samples shares hiv-1, cd4
- GSE284664 RESET: A reversible TCR-coupled antigen receptor with superior targeting sensitivity and pharmacologically controlled anti-tumor activity 62 samples shares pharmacological, targeting
- GSE254965 Pharmacological Targeting of RIG-I Selectively Activates the Integrated Stress Response 11 samples shares pharmacological, targeting
- GSE267774 Specific CD4+ T cell phenotypes associate with bacterial control in people who ‘resist’ infection with Mycobacterium tuberculosis 3076 samples shares cd4
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.