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DHX9 suppresses spurious RNA processing defects originating from the Alu invasion of the human genome [XL1 DHX9 FLASH CLIP-seq]

GSE89276 Homo sapiens (human) RNA-seq (gene expression) 6 samples Submitted 2017/03/28 Platform GPL18573
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)
Transposable elements increase genetic diversity thus making them an important part of evolution and gene regulation in all organisms that carry these sequences. Bulk of our nascent transcriptome is comprised of transposable elements that have the propensity to form strong secondary structures. It is essential to resolve such strong secondary structures to maintain normal cellular function.
Read the full summary ↓
Here, we show that the major nuclear RNA helicase DHX9/RHA interacts and remodels embedded Alu retrotransposable elements in the human transcriptome and B1 retrotransposable elements in the mouse transcriptome. To understand the function of DHX9 we used FLASH (Fast cloning of RNA After some Sort of affinity purification for High-throughput sequencing) to identify the in-vivo targets of human DHX9.
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 GSE89276_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 PRJNA351228 and SRA study SRP092248. Searching any of these in the dataset finder brings you back here.

Samples in this study

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

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