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Generation of human microglia-like cells to study neurological disease

GSE89189 Homo sapiens (human) RNA-seq (gene expression) 43 samples Submitted 2017/04/19 Platform GPL16791
At a glance

RNA-seq (gene expression) · human · 43 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
43 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)
Microglia play important roles in developmental and homeostatic brain function, and influence the establishment and progression of many neurological disorders. Here, we demonstrate that renewable human iPSCs can be efficiently differentiated to microglial-like cells (iMGL) to study neurological diseases, such as Alzheimer's disease (AD).
Read the full summary ↓
We find that iMGLs develop in vitro similarly to microglia in vivo and whole transcriptome analysis demonstrates that they are highly similar to adult and fetal human microglia. Functional assessment of iMGLs reveal that they secrete cytokines in response to inflammatory stimuli, migrate and undergo calcium transients, and robustly phagocytose CNS substrates. We also show novel use of iMGLs to examine the effects of fibrillar Aβ and brain-derived tau oligomers on AD-related gene expression and to interrogate mechanisms involved in synaptic pruning. Taken together, these findings demonstrate that iMGLs can be used in high-throughput studies of microglial function, providing important new insight into human neurological disease.
This dataset
Open GSE89189 in finder → Find more human RNA-seq datasets →
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.

Series matrix ↓
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 GSE89189_RAW.tar (it can run to tens of gigabytes).

All supplementary files ↗ Whole study · RAW.tar ↓
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.

Raw reads on ENA ↗

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 PRJNA350562 and SRA study SRP092075. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 28426964) ↗
Samples in this study

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+ 43 more — browse all 43 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.