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Next-generation sequencing measuring genome-wide RNA decay by s4U Seq in naïve CD4+ T cells from Mettl3 WT and KO mice

GSE100278 Mus musculus (mouse) RNA-seq (gene expression) 20 samples Submitted 2017/08/17 Platform GPL17021
At a glance

RNA-seq (gene expression) · mouse · 20 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
Mus musculus (mouse)
Samples
20 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)
Naïve T cells of Mettl3 KO and WT were pulse labeled by s4U for 15 min before and after IL-7 stimulation for 15min/30min/45min/60min/75min/90min. The total input RNAs or s4U nascent RNAs were isolated and prepared for next-generation sequencing. The RNA response to IL-7 and RNA decay rates were then modeled and calculated, to infer the m6A/Mettl3 effects.
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 GSE100278_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 PRJNA391351 and SRA study SRP110048. Searching any of these in the dataset finder brings you back here.

Samples in this study

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