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Single-cell RNA-Seq reveals dynamic, random monoallelic gene expression in mammalian cells

GSE45719 Mus musculus (mouse) Single-cell RNA-seq 317 samples Submitted 2014/01/10 Platform GPL13112
At a glance

Single-cell RNA-seq · mouse · 317 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism
Mus musculus (mouse)
Samples
317 samples: 45 conditions, mostly in duplicateGroups are read from the sample names, not from the paper. Check the list below.
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)
In the diploid genome, genes come in two copies, which can have different DNA sequence and where one is maternal and one is paternal. In a particular cell, a gene could potentially be expressed from both copies (biallelic expression) or only one (monoallelic). We performed RNA-Sequencing on individual cells, from zygote to the cells of the late blastocyst, and also individual cells from the adult liver.
Read the full summary ↓
Using first generation crosses between two distantly related mouse strains, CAST/Ei and C57BL/6, we determined the expression separately from the maternal and paternal alleles. We found that half of the genes were expressed by only one allele, randomly so that some cells would express the paternal allele, some the maternal and a few cell both alleles. We also observed the spread of the progressive inactivation of the paternal X chromosome.
This dataset
Open GSE45719 in finder → Find more mouse 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 GSE45719_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA195938 and SRA study SRP020490. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 24408435) ↗
Study design
45 conditions, mostly in duplicate
midblast_1 ×22 midblast_2 ×20 lateblast_1 ×19 midblast_3 ×18 earlyblast_2 ×15 earlyblast_3 ×15 16cell_1 ×14 16cell_5 ×13 +74 more

Supports a between-group comparison across 280 samples.

How we read this: 45 replicated groups read from 317 sample titles; they account for 280 of them. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.

Samples in this study

+ 277 more — browse all 317 samples with per-sample file links →

Datasets on a similar topic

Search all mouse RNA-seq datasets in GEO →

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