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Transcriptome analysis of pulmonary CCR2+ inflammatory monocytes challenged with Cryptococcus neoformans

GSE122765 Mus musculus (mouse) RNA-seq (gene expression) 3 samples Submitted 2019/02/11 Platform GPL17021
At a glance

RNA-seq (gene expression) · mouse · 3 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
3 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 encapsulated yeast Cryptococcus neoformans can cause a fatal meningoencephalitis in immunocompromised patients. C. neoformans infection is acquired through the respiratory tract, but the cellular and molecular mechanisms of the pulmonary innate immune response are still not well defined. To investigate the response of CCR2+ inflammatory monocytes to C. neoformans, we compared the transcriptomes of CCR2+ inflammatory monocytes from the lungs of naïve versus infected mice.
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 GSE122765_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 PRJNA506250 and SRA study SRP169944. Searching any of these in the dataset finder brings you back here.

Samples in this study

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+ 3 more — browse all 3 samples with per-sample file links →

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