aaomics

Omics data analysis reveals the system-level constraint on cellular amino acid composition

Software

To create a stand-alone environment named aaomics with Python 3 and all the required package versions (especially for cobrapy is also available), run the following code:

$ conda create -n aaomics python=3

$ conda activate aaomics

$ pip install ipykernel  
$ python -m ipykernel install --user --name aaomics --display-name "aaomics"  
$ pip install pandas
$ pip install Bio
$ pip install matplotlib
$ pip install seaborn
$ pip install cobra

You can read more about using conda environments in the Managing Environments section of the conda documentation.

Steps to reproduce the main analysis in the publication

1.analysis_workflow.ipynb

• Data Acquisition
• Get protein MW/Sequence corresponding to gene id using uniprot API
• Get amino acid composiotion from protein sequence
• Amino acid composition condsider protein sequence
• Amino acids composition of each protein (g / g protein) consider expression level under different conditions
• Amino acids composition of each condaition (g / g total protein) consider expression level

2.draw_figure_in_article.ipynb

• The mass distribution of each AA in per unit mass of different proteins
• The mass ratio distribution of different proteins in per unit mass of total protein (only the pro-teins with a mean mass ratio among the top 50 are displayed)
• The mass distribution of each AA per unit mass of total protein
• Distribution of the mass ratio of twenty AAs per unit mass of total protein in different species