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Next Generation Sequencing Facilitates Quantitative Analysis of HIV Elite controller, HIV ART, HIV ART-naive and healthy control Transcriptomes

GSE157198 Homo sapiens (human) RNA-seq (gene expression) 44 samples Submitted 2021/12/09 Platform GPL16791
At a glance

RNA-seq (gene expression) · human · 44 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
44 samples
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.
Summary (written by the submitters)
A small group of HIV-1-infected individuals, termed elite controllers (ECs), display control of HIV replication in the absence of antiretroviral therapy (ART). However, the mechanisms of resistance to HIV in ECs remains largely unknown. To identify host factors specific to the ECs that might be involved in controlling HIV infection, we performed RNA-seq transcriptome analysis, and a total of 44 samples were included.
Read the full summary ↓
The monocytes from each sample were enriched, sequenced, and subjected to comparative transcriptome analysis to screen candidate genes that might affect resistance to HIV infection. we found several candidate genes with highly divergent expression that might contribute to the different outcomes of HIV infection in ECs and non-ECs. This finding will help elucidate the mechanisms by which ECs restrict HIV replication and represents a new approach for treatment of HIV.
This dataset
Open GSE157198 in finder → Find more human RNA-seq datasets →
Download · which file do I need?

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.

1 · Just have a look

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.

Series matrix ↓
2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE157198_RAW.tar (it can run to tens of gigabytes).

All supplementary files ↗ Whole study · RAW.tar ↓
3 · Start from the raw reads

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.

Raw reads on ENA ↗

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 PRJNA660430 and SRA study SRP279457. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 35041523) ↗
Samples in this study

The sample list for this study is not cached yet. Press Load samples and it will be fetched from NCBI.

+ 44 more — browse all 44 samples with per-sample file links →

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