FastRet Retention time prediction

This shiny function will show you a GUI where you can choose between three modes:

• Train new Model

• Selective Measuring

• Utilize Model on new data

Each mode is briefly described below. For more information about the inputs, see the (?) behind the corresponding input.

Train new Model

This mode allows you to create and evaluate a model on your own new data. The model can be trained with various parameters and the regression model and predictor set can be downloaded afterwards. This step outputs a scatterplot of your regression model and a boxplot showing its general performance.

Selective Measuring

This mode calculates the best k molecules to be measured for a retention time prediction on a given dataset. It uses a combination of Ridge Regression and k-means to determine the best representatives of your dataset. The representatives and their corresponding clusters can be downloaded afterwards as an excel file. This step should be used once you have a predictive model and/or dataset and want to use it for a new column/gradient/temperature... combination.

Utilize model on new data

This step requires a pretrained model which can be uploaded. You can then use your model to predict retention times of new metabolites by providing either a single SMILE/HMDB ID combination or a list of molecules.

Usage

FastRet(port = 8080, host = "0.0.0.0")

Arguments

port

The port the application should listen on

host

The address the application should listen on

Value

A shiny app. This function returns a shiny app that can be run to interact with the model.