An R package for colorectal cancer screening and microbiome analysis

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Documentation for package ‘CrcBiomeScreen’ version 0.99.15

• DESCRIPTION file
• User guides, package vignettes and other documentation
• Package NEWS
• Package README

Help Pages

checkClassBalance	Check the sample distribution of the dataset and give the suggestion if need the class weight or not
CrcBiomeScreen-class	CrcBiomeScreen Class
CreateCrcBiomeScreenObject	Create a CrcBiomeScreen S4 object for microbiome-based CRC analysis
CreateCrcBiomeScreenObjectFromTSE	Create a CrcBiomeScreen object from TreeSummarizedExperiment
EvaluateCrcBiomeScreen	Evaluate the performance of model predictions
EvaluateModel	Evaluate the model to select the optimal model
EvaluateRF	Evaluate the Random Forest model
EvaluateXGBoost	Evaluate the XGBoost model
FilterDataSet	Filter the CrcBiomeScreenObject dataset based on a specific label
getAbsoluteAbundance	Accessor for AbsoluteAbundance slot of CrcBiomeScreen object
getAbsoluteAbundance-method	Accessor for AbsoluteAbundance slot of CrcBiomeScreen object
getModelData	Accessor for ModelData slot of CrcBiomeScreen object
getModelData-method	Accessor for SampleData slot of CrcBiomeScreen object
getModelResult	Accessor for ModelResult slot of CrcBiomeScreen object
getModelResult-method	Accessor for ModelResult slot of CrcBiomeScreen object
getNormalizedData	Accessor for NormalizedData slot of CrcBiomeScreen object
getNormalizedData-method	Accessor for NormalizedData slot of CrcBiomeScreen object
getOutlierSamples	Accessor for OutlierSamples
getOutlierSamples-method	Accessor for OutlierSamples
getPredictResult	Accessor for PredictResult slot of CrcBiomeScreen object
getPredictResult-method	Accessor for PredictResult slot of CrcBiomeScreen object
getRelativeAbundance	Accessor for RelativeAbundance slot of CrcBiomeScreen object
getRelativeAbundance-method	Accessor for RelativeAbundance slot of CrcBiomeScreen object
getSampleData	Accessor for SampleData slot of CrcBiomeScreen object
getSampleData-method	Accessor for SampleData slot of CrcBiomeScreen object
getTaxaData	Accessor for TaxaData slot of CrcBiomeScreen object
getTaxaData-method	Accessor for TaxaData slot of CrcBiomeScreen object
getTaxaLevelData	Accessor for TaxaLevelData slot
getTaxaLevelData-method	Accessor for TaxaLevelData slot
KeepTaxonomicLevel	Summarize abundance data at a given taxonomic level
LoadTaxaTable	Load a custom taxa table for ASV/OTU data
ModelingRF	The packaging function for Random Forest modeling
ModelingRF_noweights	The function for modeling random forest without using class weights
ModelingXGBoost	The packaging function for XGBoost modeling
ModelingXGBoost_noweights	The packaging function for XGBoost modeling without using class weights
NHSBCSP_screeningData	NHSBCSP screening dataset
NormalizeData	Normalise the absolute data to relative data by using Total Sum Scaling and Geometric Mean of Pairwise Ratios (GMPR)
PredictCrcBiomeScreen	Predict the class and probabilities for new data
qcByCmdscale	Quality control using classical MDS and outlier detection
RunScreening	Run the screening process for the microbiome data
setNormalizedData-setter	setNormalizedData<-: Setter for NormalizedData slot of CrcBiomeScreen object
setNormalizedData<-	setNormalizedData<-: Setter for NormalizedData slot of CrcBiomeScreen object
setNormalizedData<--method	setNormalizedData<-: Setter for NormalizedData slot of CrcBiomeScreen object
setTaxaData-setter	setTaxaData<-: Setter for TaxaData slot of CrcBiomeScreen object
setTaxaData<-	setTaxaData<-: Setter for TaxaData slot of CrcBiomeScreen object
setTaxaData<--method	setTaxaData<-: Setter for TaxaData slot of CrcBiomeScreen object
SplitDataSet	Split the dataset into training and test sets
SplitTaxas	Split and clean taxonomy strings
Thomas_2018_RelativeAbundance	Thomas 2018 relative abundance dataset
TrainModels	Train the different models
ValidateModelOnData	Predict the validation data by using the trained model in CrcBiomeScreenObject
ZellerG_2014_RelativeAbundance	Zeller 2014 relative abundance dataset