|
|
GEO help: Mouse over screen elements for information. |
|
Status |
Public on Apr 11, 2024 |
Title |
mouse epididymis cauda |
Sample type |
SRA |
|
|
Source name |
mouse epididymis cauda
|
Organism |
Mus musculus |
Characteristics |
tissue: mouse epididymis cauda
|
Extracted molecule |
total RNA |
Extraction protocol |
The mice and pigs’ testis were cut into pieces. The mice and pigs’ epididymis were collected and divided into epididymis caput, epididymis corpus and epididymis cauda. Cut the fresh tissue into pieces, transfer to the 0.2% collagenase IV and DNAse I digestion solution, and incubate at 37°C for 15 min. Self-designed using MGI C4 droplet generation device, through efficient mRNA capture magnetic beads and droplet recognition microbeads and single-cell RNA library preparation kit The single-cell (nuclear) suspension can be quickly prepared into the library corresponding to the sequencing platform. The DNBelab C library contains cDNA Library, which are derived from MRNA-capturing magnetic beads and droplet recognition microbeads, respectively.
|
|
|
Library strategy |
RNA-Seq |
Library source |
transcriptomic single cell |
Library selection |
cDNA |
Instrument model |
Illumina HiSeq 4000 |
|
|
Description |
10×Genomics
|
Data processing |
The demultiplexing, barcoded processing, gene counting and aggregation were made using the Cel Ranger software v2.1.1(https://support 10xgenomics. com/single-cel-gene-expression/software/pipelines/latestwhat- is-cel-range) Raw count matrices generated by Cell Ranger were imported to Seurat 4.3.0 and filtered for only high-quality cells. Briefly, we removed cells with less than 200 detected genes and genes detected in 3 or fewer cells. Gene expression values were log normalized and scaled before further downstream analyses. Cell clustering and UMAP analysis were performed based on the statistically significant principal components. Marker genes of each cell cluster were determined by Log Fold Change threshold above 0.25 using the default Wilcoxon rank-sum test. After identification of cell clusters, raw count matrices of data subsets were imported to Monocle and only expressed genes above threshold (0.1) were used for analyses. Differentially expressed genes or significantly variable genes among cells were identified by Monocle and used for ordering cells in pseudotime. Only genes with a dispersion ratio above 0.1 were used for training the pseudotime trajectories. To generate the pseudotime heatmaps, DEGs (Differentially Expressed Genes) among cell clusters in pseudotime with qval <0.1 were included and clustered hierarchically based on their expression trends. Assembly: 10mm Supplementary files format and content: Tab-separated values files and matrix files
|
|
|
Submission date |
Dec 10, 2023 |
Last update date |
Apr 11, 2024 |
Contact name |
JunLin Song |
E-mail(s) |
songjunlin123@sina.com
|
Organization name |
JunLin Song
|
Street address |
Changcheng Road
|
City |
Qingdao |
ZIP/Postal code |
266109 |
Country |
China |
|
|
Platform ID |
GPL21103 |
Series (1) |
GSE249819 |
The Single-Cell Landscape of Spermioteleosis in Mouse and Pig |
|
Relations |
BioSample |
SAMN38753412 |
SRA |
SRX22847470 |
Supplementary file |
Size |
Download |
File type/resource |
GSM7965380_Mwei_WK_barcodes.tsv.gz |
24.3 Kb |
(ftp)(http) |
TSV |
GSM7965380_Mwei_WK_features.tsv.gz |
159.5 Kb |
(ftp)(http) |
TSV |
GSM7965380_Mwei_WK_matrix.mtx.gz |
30.1 Mb |
(ftp)(http) |
MTX |
SRA Run Selector |
Raw data are available in SRA |
|
|
|
|
|