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DMS-MaPseq: A genome-wide or targeted approach for RNA structure probing in vivo

GSE84537 Homo sapiens (human) RNA-seq (gene expression) 29 samples Submitted 2016/09/16 Platform GPL21656Platform GPL17342Platform GPL17275Platform GPL16791Platform GPL16479Platform GPL15520Platform GPL17143Platform GPL21246Platform GPL21306Platform GPL20301
At a glance

RNA-seq (gene expression) · human · 29 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
29 samples: 28 distinct titles, 1 of them repeatedGroups are read from the sample names, not from the paper. Check the list below.
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)
Here we present dimethyl sulfate mutational profiling with sequencing (DMS-MaPseq), which encodes DMS modifications as mismatches using a thermostable group II intron reverse transcriptase (TGIRT). DMS-MaPseq yields a high signal-to-noise ratio, can report multiple structural features for each molecule, and allows genome-wide studies as well as focused investigations of low abundance RNAs.
Read the full summary ↓
We apply DMS-MaPseq to Drosophila melanogaster ovaries—the first experimental analysis of RNA structure in an animal tissue—and demonstrate its utility in the discovery of a functional RNA structure involved in the non-canonical GUG translation initiation of the human FXR2 mRNA. Additionally, we use DMS-MaPseq to compare the in vivo structure of messages in their pre-mRNA and mature forms. These applications illustrate DMS-MaPseq’s capacity to dramatically expand our ability to monitor RNA structure in vivo.
This dataset
Open GSE84537 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 GSE84537_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 PRJNA329551 and SRA study SRP078863. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 27819661) ↗
Study design
28 distinct titles, 1 of them repeated
Scer_Tagmentation_pre-mRNA_RPL14A_and_RPL31B ×2

How we read this: Read from 29 sample titles: 28 distinct titles with little repetition. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.

Samples in this study
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.