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Functional Screening in Human Cardiac Organoids Reveals a Metabolic Mechanism for Cardiomyocyte Maturation

GSE93841 Homo sapiens (human) RNA-seq (gene expression) 9 samples Submitted 2017/08/30 Platform GPL16791
At a glance

RNA-seq (gene expression) · human · 9 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
9 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)
The mammalian heart undergoes maturation during postnatal life to meet the increased functional requirements of the adult. However, the key drivers of this process remain poorly defined. We developed as 96-well screening platform, using human pluripotent stem cell derived cardiac organoids, to determine the molecular requirements for in vitro cardiomyocyte maturation.
Read the full summary ↓
Here, we describe gene expression changes resulting from culturing human cardiac organoids in standard cell culture conditions and under optimized maturation conditions. We assessed our maturation conditions by comparing transcriptional changes of human cardiac organoids to RNA isolated from human heart. Interesting, analysis of these data revealed that a switch to fatty acid oxidative metabolism is a key governor of cardiomyocyte maturation and mature cardiac organoids were refractory to mitogenic stimuli.
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 GSE93841_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 PRJNA362579 and SRA study SRP097153. Searching any of these in the dataset finder brings you back here.

Samples in this study

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+ 9 more — browse all 9 samples with per-sample file links →

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