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GEO help: Mouse over screen elements for information. |
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| Status |
Public on Aug 31, 2021 |
| Title |
KO.AFKD2 |
| Sample type |
SRA |
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| Source name |
AFKD2
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| Organism |
Mus musculus |
| Characteristics |
genotypes: Dnmt3a3b double KO
cell line: AFKD2
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| Treatment protocol |
After the harvest, live cells were collected by FACS moflo.
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| Growth protocol |
Mouse ES cells were cultured in 2iL. EpiLC differentiation were performed in actinvin a, bFgf and 1% KSR medium.
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| Extracted molecule |
total RNA |
| Extraction protocol |
10xgenomics
10xgenomics
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| Library strategy |
RNA-Seq |
| Library source |
transcriptomic |
| Library selection |
cDNA |
| Instrument model |
Illumina HiSeq 2000 |
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| Data processing |
Preliminary sequencing results (bcl files) were converted to fastq files with CellRanger (version 3.0) following the standard 10x Genomics protocol. Barcodes and unique molecular identifier (UMI) ends were trimmed to 26 bp, and mRNA ends to 98 bp.
Reads were then aligned to the mouse reference genome (mm10) and gene counts were obtained using the GRCm38.92 annotation in CellRanger.
We used Seurat (version 2.3.0) (Butler et al., 2018) to further process the single-cell RNA-seq data. Cells that have between 200 and 5500 unique gene counts, and with less than 5% mitochondrial gene content were filtered
Log-normalization using a scale factor of 10,000 was performed, and the data was scaled to produce standardized expression values for each gene across all cells (z-score transformation), while also regressing out unwanted variation in the percent of mitochondrial gene content.
We determined the top 2,000 most highly variable genes, and performed principal component analysis. Clusters were determined using the Louvain community detection method as implemented by the FindCluster function in Seurat with a resolution of 0.9. Visualisation was performed after using tSNE dimensional reduction on the first 18 principal components. Differential expression was performed using the Wilcoxon rank sum test, using a threshold of log2 fold change greater than 0.1 and p-value less than 0.05.
Genome_build: mm10
Supplementary_files_format_and_content: Gene expression matrix and cell type identities
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| Submission date |
Sep 21, 2020 |
| Last update date |
Aug 31, 2021 |
| Contact name |
Irina Mohorianu |
| E-mail(s) |
data-submissions@stemcells.cam.ac.uk
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| Organization name |
University of Cambridge
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| Department |
Wellcome-MRC Cambridge Stem Cell Institute
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| Street address |
Puddicombe Way
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| City |
Cambridge |
| ZIP/Postal code |
CB2 0AW |
| Country |
United Kingdom |
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| Platform ID |
GPL13112 |
| Series (2) |
| GSE158310 |
De novo DNA methylation suppresses aberrant fate trajectory during epiblast transition [RNA-seq] |
| GSE158347 |
Disabling de novo DNA methylation in embryonic stem cells allows an illegitimate fate trajectory |
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| Relations |
| BioSample |
SAMN16233425 |
| SRA |
SRX9163330 |
| Supplementary data files not provided |
SRA Run Selector |
| Raw data are available in SRA |
| Processed data are available on Series record |
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