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RNA-seq for HEK293T: a high-throughput method for R-loop mapping and quantitative assessment

GSE219070 Homo sapiens (human) RNA-seq (gene expression) 2 samples Submitted 2024/06/12 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 2 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
2 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.
Paper
mDRIP-seq is a high-throughput method for quantitative profiling of R-loop landscapeScience bulletin · 2025
Summary (written by the submitters)
Current methods for R-loop mapping need to perform DNA:RNA immunoprecipitation for each sample individually, with consequent limitations in throughput. Here, we develop and validate mDRIP-seq, a multi-sample barcoding and pooling method for R-loop mapping. We show mDRIP-seq performs equivalently as conventional methods, but with the merits of high throughput and cost-efficiency.
Read the full summary ↓
We also show the simplicity of mDRIP-seq for relative and absolute quantitation of genomic R-loop fractions for multiple samples. Together, mDRIP-seq is a high-throughput and cost-efficient method for R-loop mapping and quantitative assessment and can be widely applied to large-scale dynamic profiles of these important structures for diverse organisms.
Published in
mDRIP-seq is a high-throughput method for quantitative profiling of R-loop landscape
Sun C, Wang Z, Li Q et al. · Science bulletin 2025 · PMID 38821747 · doi:10.1016/j.scib.2024.05.023
This dataset
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.

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 GSE219070_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA906981 and SRA study SRP410631. Searching any of these in the dataset finder brings you back here.

Samples in this study

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