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Repeat-element-aware profiling of plasma cell-free RNA

GSE136651 Homo sapiens (human) RNA-seq (gene expression) 34 samples Submitted 2023/09/01 Platform GPL18573Platform GPL24106
At a glance

RNA-seq (gene expression) · human · 34 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
34 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)
Liquid biopsies provide a means for the profiling of cell-free RNAs secreted by cells throughout the body. Although well-annotated coding and noncoding transcripts in blood are readily detectable and can serve as biomarkers of disease, the overall diagnostic utility of the cell-free transcriptome remains unclear. Here we show that transposable elements and other repeat RNA elements are enriched in the cell-free transcriptome of patients with cancer, and that they serve as signatures for the accurate classification of the disease.
Read the full summary ↓
We used repeat-element-aware sequencing and analysis technology and single-molecule nanopore sequencing to profile the cell-free transcriptome in plasma from patients with cancer and to examine millions of genomic features comprised of all annotated genes and of repeat elements throughout the genome. By aggregating individual repeat elements to the subfamily level, we found that samples with pancreatic cancer are enriched with specific Alu subfamilies, whereas other cancers exhibit their own characteristic cell-free RNA profile. Our findings show that repetitive RNA sequences are abundant in blood and can be used as disease-specific diagnostic biomarkers.
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 GSE136651_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 PRJNA562932 and SRA study SRP219660. Searching any of these in the dataset finder brings you back here.

Samples in this study

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+ 34 more — browse all 34 samples with per-sample file links →

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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.