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| Status |
Public on Dec 10, 2024 |
| Title |
SA-9h, scRNA-seq, High sequencing depth results (0609-7) |
| Sample type |
SRA |
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| Source name |
bacterial cell
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| Organism |
Staphylococcus aureus |
| Characteristics |
strain: ATCC 25923
cell type: bacterial cell
genotype: WT
treatment: stationary growth phase
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| Extracted molecule |
total RNA |
| Extraction protocol |
For RiboD-PETRI, all cells were from pure culture in vitro. Cells were harvested by centrifuge;
For RiboD-PETRI, library was performed accarding to the Materials and Methods section;
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| Library strategy |
RNA-Seq |
| Library source |
transcriptomic single cell |
| Library selection |
cDNA |
| Instrument model |
Illumina NovaSeq 6000 |
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| Description |
RiboD-PETRI
Detailed_Computational_Pipeline.txt
scripts.tar.gz
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| Data processing |
The demultiplexing, barcodes processing, gene counting and aggregation of scRNA-seq datas were made by scripts compiled in Python 2.7.15 as previously described with some modifications. [lattman, W. Jiang, P. Oikonomou, S. Tavazoie, Prokaryotic single-cell RNA sequencing by in situ combinatorial indexing. Nature microbiology 5, 1192 (Oct, 2020).]. Downstream analysis of single cell data was performed using pipelines detailed in Seurat v4.3.0.
For corralation analysis of bulk RNA-Seq and scRNA-seq data, scRNA-seq data was combined with the UMI sums of all cells. Single-cell and bulk transcriptomes of E.coli were compared by computing the Pearson correlation of log2 transcripts reads of each gene between the two measurements.
For scRNA-seq data mRNA / total RNA ratio analysis, we removed the barcodes sequence contained in the front, and the interference of the last ten bases, and kept only 20 bases for mapping. Then we mapped the data from the different species to the corresponding reference genomes.
(Detailed codes were saved in "Detailed Computational Pipeline.docx" and "scripts" compressed package .)
Assembly: E.coli MG1655 K12
Supplementary files format and content: matrix files
Supplementary files format and content: xlsx file include raw counts for RNA-seq and UMI sums of scRNA-seq data
Supplementary files format and content: tab-delimited files includes raw counts for samples
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| Submission date |
Feb 28, 2024 |
| Last update date |
Dec 10, 2024 |
| Contact name |
Xiaodan Yan |
| E-mail(s) |
[email protected]
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| Phone |
13283874287
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| Organization name |
Wuhan University
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| Department |
Medical Research Institute
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| Street address |
Donghu Road, No. 115, Wuchang District,
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| City |
Wuhan |
| State/province |
Hubei Province |
| ZIP/Postal code |
430071 |
| Country |
China |
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| Platform ID |
GPL27158 |
| Series (2) |
| GSE260457 |
An Improved Bacterial Single-cell RNA-seq Reveals Biofilm Heterogeneity [scRNA-seq] |
| GSE260458 |
An Improved Bacterial Single-cell RNA-seq Reveals Biofilm Heterogeneity |
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| Relations |
| BioSample |
SAMN40188188 |
| SRA |
SRX23779280 |
| Supplementary file |
Size |
Download |
File type/resource |
| GSM8117653_Table-S14.Matrix_of_SA_data.txt.gz |
2.5 Mb |
(ftp)(http) |
TXT |
SRA Run Selector |
| Raw data are available in SRA |
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