This figure is produced by RNAseq_RTG_expression/analysis_RNA-Seq.ipynb
Whole-genome RNA sequencing was performed under normal conditions and osmotic stress [4] (GEO database's access number: GSE102475). This paper is selected because all RTG-related gene expressions are covered in this research, and this paper also provides stress condition that is informative to investigate the range of expressions of RTG elements.
The original data is downloaded and stored at Single Cell RNAseq_yeast_GSE102475.xlsx [4].
By using the differential gene expression [5], the relative expressions of Rtg1, Rtg2, Rtg3, Bmh1, Mks1 and Cit2 are analyzed by Discrete distributional differential expression [5] (D3E). Noted that Cit2 gene is used as an indicator of RTG response, while this procedure aims to get the relative expressions between RTG components rather than the exact RTG response. Zeros in RNA readouts from [4] were removed and filtered by genes of interest. The filtered data is summarized in the txt file called SingleCellRNAseq_yeast_GSE102475_LabelSep.txt. Further, differential gene expression analysis is done by D3E method by the following command
python D3ECmd.py SingelCellRNAseq_yeast_GSE102475_LabelSep.txt SingelCellRNAseq_yeast_GSE102475_LabelSep.out Stressed Unstressed -m 1 -t 0 -z 0 -n 1 -v
the installation details can be found at https://github.com/hemberg-lab/D3E [5]. Alternatively, the filtered RNA seq data can be processed by D3E online service (https://www.sanger.ac.uk/sanger/GeneRegulation_D3E/).
The mean expression values (mu1 in analysis_RNA-Seq.ipynb) are summarized in RNAseq_RTG_expression.csv that contains the relative expression levels of RTG components under normal and stressed conditions.
| File | Description |
|---|---|
| RNAseq_RTG_expression.csv | Differential gene expression of RTG elements |
| analysis_RNA-Seq.ipynb | Visualization of D3E processed differential gene expressions |
| get_RTG-Expression-Table_zero-removed.ipynb | Remove zeros in RNA-seq data and select genes of interest |
| SingleCellRNAseq_yeast_GSE102475_LabelSep.txt | RNA seq data of genes of interest (zeros are removed) |
| d3e_SC_resp_RtgGenes_GSE102475.csv | Differential gene expression (processed by https://www.sanger.ac.uk/sanger/GeneRegulation_D3E/) |
The following steps are needed to execute Jupyter notebooks under src/data/RNAseq_RTG_expression/. Noted that those notebooks are written in Python 3.7.
- Install Python 3.7 or above (https://www.python.org/)
- Install pip3 (https://pip.pypa.io/en/stable/)
- Install Python packages
pip3 install matplotlib pip3 install pandas pip3 install numpy pip3 install seaborn