GEO series

Analysis and design of RNA sequencing experiments for identifying mRNA isoform regulation

GSE23694 Homo sapiens (human) RNA-seq (gene expression) 6 samples Submitted 2010/11/07 Platform GPL9185Platform GPL9052

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)
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)

Through alternative splicing, most human genes express multiple isoforms that may have distinct or even antagonistic functions. To infer isoform regulation based on data from high-throughput sequencing of cDNA fragments (RNA-Seq), we have developed MISO, a computational model that estimates the expression level of alternatively spliced exons and mRNA isoforms and provides intuitive measures of conﬁdence in these estimates.

Read the full summary ↓

Incorporation of the length distribution of inserted cDNA fragments in paired-end RNA-Seq analysis in MISO enables dramatic improvements in estimation of alternative splicing levels relative to previous methods. We show that one lane of paired-end RNA-Seq data can provide far more information about splicing than two lanes of single-end data, depending critically on properties of the distribution of cDNA fragment lengths in the sequenced library. MISO also leads to an intuitive method to detect diﬀerentially regulated exons or isoforms. Application of this method implicates the RNA splicing factor hnRNP H in regulation of alternative cleavage and polyadenylation, a role that is supported by UV crosslinking/immunoprecipitation/high-throughput sequencing (CLIP-Seq) analysis. Together, our results provide a probabilistic framework for RNA-Seq analysis, derive functional insights into pre-mRNA processing, and yield guidelines for the optimal design of RNA-Seq experiments for studies of gene and isoform expression.

This dataset

Open GSE23694 in finder → Find more 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 GSE23694_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 PRJNA130865 and SRA study SRP003495. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 21057496) ↗

Samples in this study

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

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Search all RNA-seq datasets in GEO →

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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.