https://github.com/biocomputingup/cholesterol-model

https://github.com/biocomputingup/cholesterol-model

Last synced: 11 months ago
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• Host: GitHub
• URL: https://github.com/biocomputingup/cholesterol-model
• Owner: BioComputingUP
• Created: 2019-09-13T13:34:04.000Z (almost 7 years ago)
• Default Branch: master
• Last Pushed: 2020-02-12T12:17:41.000Z (over 6 years ago)
• Last Synced: 2025-04-03T17:53:02.620Z (about 1 year ago)
• Language: R
• Size: 28.3 KB
• Stars: 1
• Watchers: 6
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          
# Scripts ro run in silico model for cholesterol level prediction 

 

## REQUIREMENTS

```

R:

>install.packages('deSolve')

>install.packages('pracma')

>install.packages('minpack.lm')

>install.packages('plotrix')

>install.packages('gridExtra)

>install.packages('ggplot2')

```

## USAGE

to run all analyses, you have just to run the following command inside the src folder: Rscript ./main_VdP_V01_revision.R

      This script will compute all statistics and make plots

      This script expects a folder structure like this to run:

            * ./src : contains all scripts

            * ./results : will contain all performance tables and plots

            * ./results/paper/ : will contain all paper tables and plots    

            * ./data : will contain all input tables 

      

      These are Input needed:

            * input tables in ./data

      Running the script these Output files will be generated in ./results

           * table with fmut optimized (HDL, LDL)

           * table with fmut optimized (TC), only for DHCR7 gene

           * boxplot of cholesterol levels (training set)

           * table with difference between predicted and experimental cholesterol

           * table with trained vs van de Pas et al. fmut

           * sensitivity analysis plot (HDL, LDL, TC)

           * barplot with HDL levels (predicted, real)

           * table with HDL levels (predicted, real)

           * barplot with LDL levels (predicted, real)

           * table with LDL levels (predicted, real)

           * table with number of mutations and patients for each gene

           * percentage of difference between predicted and experimental

           * barplot with TC levels (predicted, real)

           * table with predicted and real blood cholesterol values

           * table with PCC, KCC, RMSD and Rsquared of predicted blood cholesterol values

           * table with TC levels (predicted, real)

           * table with standard deviation of model predictions

           * table with bootstrap