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Functional astrocytes differentiated from hiPSCs

GSE97904 Homo sapiens (human) RNA-seq (gene expression) 8 samples Submitted 2017/08/18 Platform GPL16791
At a glance

RNA-seq (gene expression) · human · 8 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
8 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)
Growing evidence implicates the importance of glia, particularly astrocytes, in neurological and psychiatric diseases. Here, we describe a rapid and robust method for the differentiation of highly pure populations of astrocytes from human induced pluripotent stem cells (hiPSCs), via a neural progenitor cell (NPC) intermediate. Using this method, we generated hiPSC-derived astrocyte populations (hiPSC-astrocytes) from 42 NPC lines (derived from 30 individuals) with an average of ~90% S100β-positive cells.
Read the full summary ↓
Transcriptomic analysis demonstrated that the hiPSC-astrocytes are highly similar to primary human fetal astrocytes and characteristic of a non-reactive state. hiPSC-astrocytes respond to inflammatory stimulants, display phagocytic capacity and enhance microglial phagocytosis. hiPSC-astrocytes also possess spontaneous calcium transient activity. Our novel protocol is a reproducible, straightforward (single media) and rapid (<30 days) method to generate homogenous populations of hiPSC-astrocytes that can be used for neuron-astrocyte and microglia-astrocyte co-cultures for the study of neuropsychiatric disorders.
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 GSE97904_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 PRJNA383243 and SRA study SRP104149. Searching any of these in the dataset finder brings you back here.

Samples in this study

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+ 8 more — browse all 8 samples with per-sample file links →

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