← BioTransfer GEO Dataset Finder
GEO series

High-throughput RNA sequencing on circular RNA profiles of human bladder cancer tissues and normal bladder tissues

GSE97239 Homo sapiens (human) RNA-seq (gene expression) 6 samples Submitted 2017/08/04 Platform GPL11154
At a glance

RNA-seq (gene expression) · human · 6 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)
Topic
Bladder cancerThis series is part of our curated briefing on it.
Samples
6 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)
In order to find out circular RNAs profiles in human bladder cancer tissues and normal bladder tissues, we characterized circuclar RNA transcripts by performing RNA-Seq on ribosomal RNA-depleted total RNA from three pairs of human bladder cancer tissues and paired normal bladder tissues.A computational pipeline based on the anchor alignment of unmapped reads was used to identify circular RNAs.
Read the full summary ↓
Collectively, we identified16,535 distict circular RNAs, most of them origined from exons (88.96%), others from introns, linc RNA, intergenic region, 3’UTR and 5’UTR. Among all these circRNAs, 571 circRNAs were differentially expressed between bladder cancer tissues and normal bladder tissues, and 524 circRNAs were downregulated in bladder cancer tissues (91.2%), others were upreguluated. These significantly differential expressed circular RNA might have regulatory function in bladder cancer, and worth to be further explored.
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 GSE97239_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 PRJNA381054 and SRA study SRP102798. Searching any of these in the dataset finder brings you back here.

Samples in this study

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

+ 6 more — browse all 6 samples with per-sample file links →

More Bladder cancer datasets

Search all human RNA-seq datasets in GEO →

Share this dataset

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.