- Last Updated: 9/16/2016
- Correspondence to: Katie Gayvert, kmg257 [at] cornell [dot] edu
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- R - tested on version 3.2.2 (2015-08-14) -- "Fire Safety"
- R dependecies (Feature Interpretation Tool): shiny, shinyjs, data.table, plyr, htmlwidgets, ggplot2, randomForest, grid, gridExtra, Cairo
- Additional R dependecies (Prediction Tool): ChemmineR, ChemmineOB, rcdk, Rcpi
To Install R Dependencies:
install.packages(c("shiny", "shinyjs", "data.table", "plyr", "htmlwidgets", "ggplot2", "randomForest", "grid", "gridExtra", "Cairo","rcdk"))
source("https://bioconductor.org/biocLite.R")
biocLite("Rcpi")
biocLite("ChemmineR")
biocLite("ChemmineOB")
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source("/path/to/PrOCTOR/R/PrOCTOR.R")
PrOCTOR(SMILE,target_list)
Example (Dexamethasone):
PrOCTOR(SMILE="[H][C@@]12C[C@@H](C)[C@](O)(C(=O)CO)[C@@]1(C)C[C@H](O)[C@@]1(F)[C@@]2([H])CCC2=CC(=O)C=C[C@]12C",
targets=c("NR3C1","NR0B1","ANXA1","NOS2"))
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library(shiny)
load("/path/to/PrOCTOR/shiny/PrOCTOR_prediction/initial_values.RData")
runApp("/path/to/PrOCTOR/shiny/PrOCTOR_prediction")
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library(shiny)
load("/path/to/PrOCTOR/shiny/PrOCTOR_interpretation/initial_values.RData")
runApp("/path/to/PrOCTOR/shiny/PrOCTOR_interpretation")
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- Feature Quantile Plot - quantile values for each feature
- Predictions - compares each model's current prediction to distributions of failed and approved drugs in training set
- Structure Feature Values - Current structural feature values
- Target Feature Values - Current target-based feature values
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- Pre-load features existing drug
- Change individual features using manually entered values *
- Change individual features by clicking new value on barplot *
* Change other correlated feature values along with selected feature (default set off)
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- Create GitHub repository
- Make functional interface where all changes update
- Allow user inputted structures and targets
- Finish commenting code
- Finish model fine-tuning