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Transcriptional profiles by deep sequencing (RNA-seq) of in vivo-generated mouse iPSCs, in vitro-generated mouse iPSCs, and mouse ESCs

GSE48364 Mus musculus (mouse) RNA-seq (gene expression) 14 samples Submitted 2013/09/12 Platform GPL11002
At a glance

RNA-seq (gene expression) · mouse · 14 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
14 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)
We have generated “reprogrammable” transgenic mice that ubiquitously express the four Yamanaka factors in an inducible manner. Transitory induction of the transgene results in multiple teratomas emerging from a variety of organs, thus indicating that full reprogramming into iPSCs can occur in vivo. By performing bone marrow transplant experiments, we demonstrate that both hematopoietic cells, as well as non-hematopoietic cells can be reprogrammed in vivo.
Read the full summary ↓
Remarkably, reprogrammable mice also present circulating iPSCs in the bloodstream (in vivo-iPSCs) with all the expected properties of bona fide iPSCs. Moreover, in contrast to in vitro-iPSCs or embryonic stem cells (ESCs), in vivo-iPSCs have an increased capacity to undergo trophectoderm lineage differentiation, which suggests that in vivo-iPSCs are more plastic or primitive than in vitro-generated iPSCs or ESCs.
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 GSE48364_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 PRJNA209846 and SRA study SRP026364. Searching any of these in the dataset finder brings you back here.

Samples in this study

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+ 14 more — browse all 14 samples with per-sample file links →

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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.