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All_Tumor_ML_predict_tumor_vs_normal_FA_Patent.R
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All_Tumor_ML_predict_tumor_vs_normal_FA_Patent.R
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# All_Tumor_sequence_center_effects.R
# Author: Greg Poore
# Date: Aug 21, 2018
# Purpose: To explore the contribution of sequence center to cancer microbiome profiles
#-------------------------------#
# Load dependencies
require(devtools)
require(ggbiplot)
require(doMC)
# require(caretEnsemble)
# require(plotly)
numCores <- detectCores()
registerDoMC(cores=numCores)
## Import data
load("tcgaVbDataAndMetadataAndSNM.RData")
load("snmDataSampleTypeWithExpStrategyFINAL.RData")
#----------------------------------------------------
## To avoid the error below when training the GBM learner, a custom GBM grid can be entered
# The dataset size is too small or subsampling rate is too large: nTrain*bag.fraction <= n.minobsinnode
defaultGBMGrid <- expand.grid(interaction.depth = seq(1,3),
n.trees = floor((1:3) * 50),
shrinkage = 0.1,
n.minobsinnode = 5)
customGBMGrid <- expand.grid(interaction.depth = seq(1,3),
n.trees = floor((1:3) * 50),
shrinkage = 0.1,
n.minobsinnode = 1)
glmnetGrid <- expand.grid(.alpha = seq(.05, 1, length = 15),
.lambda = c((1:5)/10))
### Testing ###
# 1252 T / 129 N
# source("predTumorVsNormalEnsembleFA.R")
source("predTumorVsNormalFA_Patent.R")
bicPredTumorVsNormalTissue <- predTumorVsNormalFA_Patent(qcMLMetadata = metadataSamplesAllQC,
qcMLDataSNM = snmDataSampleTypeWithExpStrategy,
cancerTypeString = "Breast Invasive Carcinoma",
nlTissueComparison = "Solid Tissue Normal",
tumorTissueComparison = "Primary Tumor",
flagForAlternativeNormal = FALSE,
cancerTypeStringAlternativeNormal = NULL,
caretModel = "gbm",
samplingStrategy = "up",
numResampleIter = 1,
numKFold = 2,
trainSetProp = 0.7,
plotPath = "./roc-ggplots-predicting-tumor-vs-normal",
caretTuneGrid = customGBMGrid)
# tmpPredTumorVsNormalTissue <- predTumorVsNormalFA_Patent(qcMLMetadata = metadataSamplesAllQC,
# qcMLDataSNM = snmDataSampleTypeWithExpStrategy,
# cancerTypeString = "Uterine Corpus Endometrial Carcinoma",
# nlTissueComparison = "Solid Tissue Normal",
# tumorTissueComparison = "Primary Tumor",
# flagForAlternativeNormal = FALSE,
# cancerTypeStringAlternativeNormal = NULL,
# caretModel = "gbm",
# samplingStrategy = "up",
# numResampleIter = 1,
# numKFold = 2,
# trainSetProp = 0.7,
# plotPath = "./roc-ggplots-predicting-tumor-vs-normal",
# caretTuneGrid = customGBMGrid)
#---------- Predict tumor vs normal using cancer microbiome in Acute Myeloid Leukemia ----------#
## NB: AML is not in the QC metadata
#---------- Predict tumor vs normal using cancer microbiome in Adrenocortical Carcinoma ----------#
# 79 T / 110 N (RCC)
adrenocorticalcarcinomaPredTumorVsRCCNormalTissue <- predTumorVsNormalFA_Patent(qcMLMetadata = metadataSamplesAllQC,
qcMLDataSNM = snmDataSampleType,
cancerTypeString = "Adrenocortical Carcinoma",
nlTissueComparison = "Solid Tissue Normal",
tumorTissueComparison = "Primary Tumor",
flagForAlternativeNormal = TRUE,
cancerTypeStringAlternativeNormal = "Kidney Renal Clear Cell Carcinoma",
caretModel = "gbm",
numResampleIter = 1,
numKFold = 2,
testSetProp = 0.7,
caretTuneGrid = defaultGBMGrid)
#---------- Predict tumor vs normal using cancer microbiome in Bladder Urothelial Carcinoma ----------#
# 557 T / 48 N
bladderPredTumorVsNormalTissue <- predTumorVsNormalFA_Patent(qcMLMetadata = metadataSamplesAllQC,
qcMLDataSNM = snmDataSampleType,
cancerTypeString = "Bladder Urothelial Carcinoma",
nlTissueComparison = "Solid Tissue Normal",
tumorTissueComparison = "Primary Tumor",
flagForAlternativeNormal = FALSE,
cancerTypeStringAlternativeNormal = NULL,
caretModel = "gbm",
numResampleIter = 1,
numKFold = 2,
testSetProp = 0.7,
caretTuneGrid = defaultGBMGrid)
# 557 T / 124 NB
bladderPredTumorVsNormalBlood <- predTumorVsNormalFA_Patent(qcMLMetadata = metadataSamplesAllQC,
qcMLDataSNM = snmDataSampleType,
cancerTypeString = "Bladder Urothelial Carcinoma",
nlTissueComparison = "Blood Derived Normal",
tumorTissueComparison = "Primary Tumor",
flagForAlternativeNormal = FALSE,
cancerTypeStringAlternativeNormal = NULL,
caretModel = "gbm",
numResampleIter = 1,
numKFold = 2,
testSetProp = 0.7,
caretTuneGrid = defaultGBMGrid)
#---------- Predict tumor vs normal using cancer microbiome in Brain Lower Grade Glioma ----------#
# 607 T / 92 NB
blggPredTumorVsNormalBlood <- predTumorVsNormalFA_Patent(qcMLMetadata = metadataSamplesAllQC,
qcMLDataSNM = snmDataSampleType,
cancerTypeString = "Brain Lower Grade Glioma",
nlTissueComparison = "Blood Derived Normal",
tumorTissueComparison = "Primary Tumor",
flagForAlternativeNormal = FALSE,
cancerTypeStringAlternativeNormal = NULL,
caretModel = "gbm",
numResampleIter = 1,
numKFold = 2,
testSetProp = 0.7,
caretTuneGrid = defaultGBMGrid)
# 34 RT / 607 T
blggPredPrimaryTumorVsRecurrentTumor <- predTumorVsNormalFA_Patent(qcMLMetadata = metadataSamplesAllQC,
qcMLDataSNM = snmDataSampleType,
cancerTypeString = "Brain Lower Grade Glioma",
nlTissueComparison = "Primary Tumor",
tumorTissueComparison = "Recurrent Tumor",
flagForAlternativeNormal = FALSE,
cancerTypeStringAlternativeNormal = NULL,
caretModel = "gbm",
numResampleIter = 1,
numKFold = 2,
testSetProp = 0.7,
caretTuneGrid = defaultGBMGrid)
#---------- Predict tumor vs normal using cancer microbiome in Breast Invasive Carcinoma ----------#
# 1252 T / 129 N
bicPredTumorVsNormalTissue <- predTumorVsNormalFA_Patent(qcMLMetadata = metadataSamplesAllQC,
qcMLDataSNM = snmDataSampleTypeWithExpStrategy,
cancerTypeString = "Breast Invasive Carcinoma",
nlTissueComparison = "Solid Tissue Normal",
tumorTissueComparison = "Primary Tumor",
flagForAlternativeNormal = FALSE,
cancerTypeStringAlternativeNormal = NULL,
caretModel = "gbm",
numResampleIter = 1,
numKFold = 2,
testSetProp = 0.7,
caretTuneGrid = defaultGBMGrid)
# 1252 T / 107 NB
bicPredTumorVsNormalBlood <- predTumorVsNormalFA_Patent(qcMLMetadata = metadataSamplesAllQC,
qcMLDataSNM = snmDataSampleType,
cancerTypeString = "Breast Invasive Carcinoma",
nlTissueComparison = "Blood Derived Normal",
tumorTissueComparison = "Primary Tumor",
flagForAlternativeNormal = FALSE,
cancerTypeStringAlternativeNormal = NULL,
caretModel = "gbm",
numResampleIter = 1,
numKFold = 2,
testSetProp = 0.7,
caretTuneGrid = defaultGBMGrid)
# 9 M / 1252 T ************
bicGBMGrid <- expand.grid(interaction.depth = seq(1,3),
n.trees = floor((1:3) * 50),
shrinkage = 0.1,
n.minobsinnode = 1)
bicPredPrimaryTumorVsMetastaticTumor <- predTumorVsNormalFA_Patent(qcMLMetadata = metadataSamplesAllQC,
qcMLDataSNM = snmDataSampleType,
cancerTypeString = "Breast Invasive Carcinoma",
nlTissueComparison = "Primary Tumor",
tumorTissueComparison = "Metastatic",
flagForAlternativeNormal = FALSE,
cancerTypeStringAlternativeNormal = NULL,
caretModel = "gbm",
numResampleIter = 1,
numKFold = 2,
testSetProp = 0.7,
caretTuneGrid = bicGBMGrid)
#---------- Predict tumor vs normal using cancer microbiome in Cervical Squamous Cell Carcinoma and Endocervical Adenocarcinoma ----------#
# 374 T / 5 N ***************
cervGBMGrid <- expand.grid(interaction.depth = seq(1,3),
n.trees = floor((1:3) * 50),
shrinkage = 0.1,
n.minobsinnode = 1)
cervicalPredTumorVsNormalTissue <- predTumorVsNormalFA_Patent(qcMLMetadata = metadataSamplesAllQC,
qcMLDataSNM = snmDataSampleType,
cancerTypeString = "Cervical Squamous Cell Carcinoma and Endocervical Adenocarcinoma",
nlTissueComparison = "Solid Tissue Normal",
tumorTissueComparison = "Primary Tumor",
flagForAlternativeNormal = FALSE,
cancerTypeStringAlternativeNormal = NULL,
caretModel = "gbm",
numResampleIter = 1,
numKFold = 2,
testSetProp = 0.7,
caretTuneGrid = cervGBMGrid)
# 374 T / 70 NB
cervicalPredTumorVsNormalBlood <- predTumorVsNormalFA_Patent(qcMLMetadata = metadataSamplesAllQC,
qcMLDataSNM = snmDataSampleType,
cancerTypeString = "Cervical Squamous Cell Carcinoma and Endocervical Adenocarcinoma",
nlTissueComparison = "Blood Derived Normal",
tumorTissueComparison = "Primary Tumor",
flagForAlternativeNormal = FALSE,
cancerTypeStringAlternativeNormal = NULL,
caretModel = "gbm",
numResampleIter = 1,
numKFold = 2,
testSetProp = 0.7,
caretTuneGrid = defaultGBMGrid)
#---------- Predict tumor vs normal using cancer microbiome in Cholangiocarcinoma ----------#
# 36 T / 9 N *************
cholGBMGrid <- expand.grid(interaction.depth = seq(1,3),
n.trees = floor((1:3) * 50),
shrinkage = 0.1,
n.minobsinnode = 1)
cholPredTumorVsNormalTissue <- predTumorVsNormalFA_Patent(qcMLMetadata = metadataSamplesAllQC,
qcMLDataSNM = snmDataSampleType,
cancerTypeString = "Cholangiocarcinoma",
nlTissueComparison = "Solid Tissue Normal",
tumorTissueComparison = "Primary Tumor",
flagForAlternativeNormal = FALSE,
cancerTypeStringAlternativeNormal = NULL,
caretModel = "gbm",
numResampleIter = 1,
numKFold = 2,
testSetProp = 0.7,
caretTuneGrid = cholGBMGrid)
#---------- Predict tumor vs normal using cancer microbiome in Colon Adenocarcinoma ----------#
# 837 T / 70 N
colonPredTumorVsNormalTissue <- predTumorVsNormalFA_Patent(qcMLMetadata = metadataSamplesAllQC,
qcMLDataSNM = snmDataSampleType,
cancerTypeString = "Colon Adenocarcinoma",
nlTissueComparison = "Solid Tissue Normal",
tumorTissueComparison = "Primary Tumor",
flagForAlternativeNormal = FALSE,
cancerTypeStringAlternativeNormal = NULL,
caretModel = "gbm",
numResampleIter = 1,
numKFold = 2,
testSetProp = 0.7,
caretTuneGrid = defaultGBMGrid)
# 837 T / 109 NB
colonPredTumorVsNormalBlood <- predTumorVsNormalFA_Patent(qcMLMetadata = metadataSamplesAllQC,
qcMLDataSNM = snmDataSampleType,
cancerTypeString = "Colon Adenocarcinoma",
nlTissueComparison = "Blood Derived Normal",
tumorTissueComparison = "Primary Tumor",
flagForAlternativeNormal = FALSE,
cancerTypeStringAlternativeNormal = NULL,
caretModel = "gbm",
numResampleIter = 1,
numKFold = 2,
testSetProp = 0.7,
caretTuneGrid = defaultGBMGrid)
#---------- Predict tumor vs normal using cancer microbiome in Esophageal Carcinoma ----------#
# 253 T / 37 N
esophagealcarcinomaPredTumorVsNormalTissue <- predTumorVsNormalFA_Patent(qcMLMetadata = metadataSamplesAllQC,
qcMLDataSNM = snmDataSampleType,
cancerTypeString = "Esophageal Carcinoma",
nlTissueComparison = "Solid Tissue Normal",
tumorTissueComparison = "Primary Tumor",
flagForAlternativeNormal = FALSE,
cancerTypeStringAlternativeNormal = NULL,
caretModel = "gbm",
numResampleIter = 1,
numKFold = 2,
testSetProp = 0.7,
caretTuneGrid = defaultGBMGrid)
# 253 T / 48 NB
esophagealcarcinomaPredTumorVsNormalBlood <- predTumorVsNormalFA_Patent(qcMLMetadata = metadataSamplesAllQC,
qcMLDataSNM = snmDataSampleType,
cancerTypeString = "Esophageal Carcinoma",
nlTissueComparison = "Blood Derived Normal",
tumorTissueComparison = "Primary Tumor",
flagForAlternativeNormal = FALSE,
cancerTypeStringAlternativeNormal = NULL,
caretModel = "gbm",
numResampleIter = 1,
numKFold = 2,
testSetProp = 0.7,
caretTuneGrid = defaultGBMGrid)
#---------- Predict tumor vs normal using cancer microbiome in Glioblastoma Multiforme ----------#
# 405 T / 5 N *********************
# gbmGBMGrid <- expand.grid(interaction.depth = seq(1,3),
# n.trees = floor((1:3) * 50),
# shrinkage = 0.1,
# n.minobsinnode = 1)
# gbmPredTumorVsNormalTissue <- predTumorVsNormalFA_Patent(qcMLMetadata = metadataSamplesAllQC,
# qcMLDataSNM = snmDataSampleType,
# cancerTypeString = "Glioblastoma Multiforme",
# nlTissueComparison = "Solid Tissue Normal",
# tumorTissueComparison = "Primary Tumor",
# flagForAlternativeNormal = FALSE,
# cancerTypeStringAlternativeNormal = NULL,
# caretModel = "gbm",
# numResampleIter = 1,
# numKFold = 2,
# testSetProp = 0.7,
# caretTuneGrid = gbmGBMGrid)
# 405 T / 74 NB
gbmPredTumorVsNormalBlood <- predTumorVsNormalFA_Patent(qcMLMetadata = metadataSamplesAllQC,
qcMLDataSNM = snmDataSampleType,
cancerTypeString = "Glioblastoma Multiforme",
nlTissueComparison = "Blood Derived Normal",
tumorTissueComparison = "Primary Tumor",
flagForAlternativeNormal = FALSE,
cancerTypeStringAlternativeNormal = NULL,
caretModel = "gbm",
numResampleIter = 1,
numKFold = 2,
testSetProp = 0.7,
caretTuneGrid = defaultGBMGrid)
#---------- Predict tumor vs normal using cancer microbiome in Head and Neck Squamous Cell Carcinoma ----------#
# 692 T / 70 N
hnsccPredTumorVsNormalTissue <- predTumorVsNormalFA_Patent(qcMLMetadata = metadataSamplesAllQC,
qcMLDataSNM = snmDataSampleType,
cancerTypeString = "Head and Neck Squamous Cell Carcinoma",
nlTissueComparison = "Solid Tissue Normal",
tumorTissueComparison = "Primary Tumor",
flagForAlternativeNormal = FALSE,
cancerTypeStringAlternativeNormal = NULL,
caretModel = "gbm",
numResampleIter = 1,
numKFold = 2,
testSetProp = 0.7,
caretTuneGrid = defaultGBMGrid)
# 692 T / 143 NB
hnsccPredTumorVsNormalBlood <- predTumorVsNormalFA_Patent(qcMLMetadata = metadataSamplesAllQC,
qcMLDataSNM = snmDataSampleType,
cancerTypeString = "Head and Neck Squamous Cell Carcinoma",
nlTissueComparison = "Blood Derived Normal",
tumorTissueComparison = "Primary Tumor",
flagForAlternativeNormal = FALSE,
cancerTypeStringAlternativeNormal = NULL,
caretModel = "gbm",
numResampleIter = 1,
numKFold = 2,
testSetProp = 0.7,
caretTuneGrid = defaultGBMGrid)
#---------- Predict tumor vs normal using cancer microbiome in Kidney Chromophobe ----------#
# 116 T / 66 N
kidneychromophobePredTumorVsNormalTissue <- predTumorVsNormalFA_Patent(qcMLMetadata = metadataSamplesAllQC,
qcMLDataSNM = snmDataSampleType,
cancerTypeString = "Kidney Chromophobe",
nlTissueComparison = "Solid Tissue Normal",
tumorTissueComparison = "Primary Tumor",
flagForAlternativeNormal = FALSE,
cancerTypeStringAlternativeNormal = NULL,
caretModel = "gbm",
numResampleIter = 1,
numKFold = 2,
testSetProp = 0.7,
caretTuneGrid = defaultGBMGrid)
# 116 T / 9 NB ************
# kidneychromophobePredTumorVsNormalBlood <- predTumorVsNormalFA_Patent(qcMLMetadata = metadataSamplesAllQC,
# qcMLDataSNM = snmDataSampleType,
# cancerTypeString = "Kidney Chromophobe",
# nlTissueComparison = "Blood Derived Normal",
# tumorTissueComparison = "Primary Tumor",
# flagForAlternativeNormal = FALSE,
# cancerTypeStringAlternativeNormal = NULL,
# caretModel = "gbm",
# numResampleIter = 1,
# numKFold = 2,
# testSetProp = 0.7,
# caretTuneGrid = defaultGBMGrid)
#---------- Predict tumor vs normal using cancer microbiome in Kidney Renal Clear Cell Carcinoma ----------#
# 1026 T / 110 N
rccPredTumorVsNormalTissue <- predTumorVsNormalFA_Patent(qcMLMetadata = metadataSamplesAllQC,
qcMLDataSNM = snmDataSampleType,
cancerTypeString = "Kidney Renal Clear Cell Carcinoma",
nlTissueComparison = "Solid Tissue Normal",
tumorTissueComparison = "Primary Tumor",
flagForAlternativeNormal = FALSE,
cancerTypeStringAlternativeNormal = NULL,
caretModel = "gbm",
numResampleIter = 1,
numKFold = 2,
testSetProp = 0.7,
caretTuneGrid = defaultGBMGrid)
# 1026 T / 5 NB **************
# rccPredTumorVsNormalBlood <- predTumorVsNormalFA_Patent(qcMLMetadata = metadataSamplesAllQC,
# qcMLDataSNM = snmDataSampleType,
# cancerTypeString = "Kidney Renal Clear Cell Carcinoma",
# nlTissueComparison = "Blood Derived Normal",
# tumorTissueComparison = "Primary Tumor",
# flagForAlternativeNormal = FALSE,
# cancerTypeStringAlternativeNormal = NULL,
# caretModel = "gbm",
# numResampleIter = 1,
# numKFold = 2,
# testSetProp = 0.7,
# caretTuneGrid = defaultGBMGrid)
#---------- Predict tumor vs normal using cancer microbiome in Kidney Renal Papillary Cell Carcinoma ----------#
# 328 T / 36 N
rpccPredTumorVsNormalTissue <- predTumorVsNormalFA_Patent(qcMLMetadata = metadataSamplesAllQC,
qcMLDataSNM = snmDataSampleType,
cancerTypeString = "Kidney Renal Papillary Cell Carcinoma",
nlTissueComparison = "Solid Tissue Normal",
tumorTissueComparison = "Primary Tumor",
flagForAlternativeNormal = FALSE,
cancerTypeStringAlternativeNormal = NULL,
caretModel = "gbm",
numResampleIter = 1,
numKFold = 2,
testSetProp = 0.7,
caretTuneGrid = defaultGBMGrid)
# 328 T / 35 NB
rpccPredTumorVsNormalBlood <- predTumorVsNormalFA_Patent(qcMLMetadata = metadataSamplesAllQC,
qcMLDataSNM = snmDataSampleType,
cancerTypeString = "Kidney Renal Papillary Cell Carcinoma",
nlTissueComparison = "Blood Derived Normal",
tumorTissueComparison = "Primary Tumor",
flagForAlternativeNormal = FALSE,
cancerTypeStringAlternativeNormal = NULL,
caretModel = "gbm",
numResampleIter = 1,
numKFold = 2,
testSetProp = 0.7,
caretTuneGrid = defaultGBMGrid)
#---------- Predict tumor vs normal using cancer microbiome in Liver Hepatocellular Carcinoma ----------#
# 425 T / 72 N
hccPredTumorVsNormalTissue <- predTumorVsNormalFA_Patent(qcMLMetadata = metadataSamplesAllQC,
qcMLDataSNM = snmDataSampleType,
cancerTypeString = "Liver Hepatocellular Carcinoma",
nlTissueComparison = "Solid Tissue Normal",
tumorTissueComparison = "Primary Tumor",
flagForAlternativeNormal = FALSE,
cancerTypeStringAlternativeNormal = NULL,
caretModel = "gbm",
numResampleIter = 1,
numKFold = 2,
testSetProp = 0.7,
caretTuneGrid = defaultGBMGrid)
# 425 T / 32 NB
hccPredTumorVsNormalBlood <- predTumorVsNormalFA_Patent(qcMLMetadata = metadataSamplesAllQC,
qcMLDataSNM = snmDataSampleType,
cancerTypeString = "Liver Hepatocellular Carcinoma",
nlTissueComparison = "Blood Derived Normal",
tumorTissueComparison = "Primary Tumor",
flagForAlternativeNormal = FALSE,
cancerTypeStringAlternativeNormal = NULL,
caretModel = "gbm",
numResampleIter = 1,
numKFold = 2,
testSetProp = 0.7,
caretTuneGrid = defaultGBMGrid)
#---------- Predict tumor vs normal using cancer microbiome in Lung Adenocarcinoma ----------#
# 711 T / 134 N
ladPredTumorVsNormalTissue <- predTumorVsNormalFA_Patent(qcMLMetadata = metadataSamplesAllQC,
qcMLDataSNM = snmDataSampleType,
cancerTypeString = "Lung Adenocarcinoma",
nlTissueComparison = "Solid Tissue Normal",
tumorTissueComparison = "Primary Tumor",
flagForAlternativeNormal = FALSE,
cancerTypeStringAlternativeNormal = NULL,
caretModel = "gbm",
numResampleIter = 1,
numKFold = 2,
testSetProp = 0.7,
caretTuneGrid = defaultGBMGrid)
# 711 T / 104 NB
ladPredTumorVsNormalBlood <- predTumorVsNormalFA_Patent(qcMLMetadata = metadataSamplesAllQC,
qcMLDataSNM = snmDataSampleType,
cancerTypeString = "Lung Adenocarcinoma",
nlTissueComparison = "Blood Derived Normal",
tumorTissueComparison = "Primary Tumor",
flagForAlternativeNormal = FALSE,
cancerTypeStringAlternativeNormal = NULL,
caretModel = "gbm",
numResampleIter = 1,
numKFold = 2,
testSetProp = 0.7,
caretTuneGrid = defaultGBMGrid)
#---------- Predict tumor vs normal using cancer microbiome in Lung Squamous Cell Carcinoma ----------#
# 552 T / 83 N
lsccPredTumorVsNormalTissue <- predTumorVsNormalFA_Patent(qcMLMetadata = metadataSamplesAllQC,
qcMLDataSNM = snmDataSampleType,
cancerTypeString = "Lung Squamous Cell Carcinoma",
nlTissueComparison = "Solid Tissue Normal",
tumorTissueComparison = "Primary Tumor",
flagForAlternativeNormal = FALSE,
cancerTypeStringAlternativeNormal = NULL,
caretModel = "gbm",
numResampleIter = 1,
numKFold = 2,
testSetProp = 0.7,
caretTuneGrid = defaultGBMGrid)
# 552 T / 18 NB **************
lsccGBMGrid <- expand.grid(interaction.depth = seq(1,3),
n.trees = floor((1:3) * 50),
shrinkage = 0.1,
n.minobsinnode = 1)
lsccPredTumorVsNormalBlood <- predTumorVsNormalFA_Patent(qcMLMetadata = metadataSamplesAllQC,
qcMLDataSNM = snmDataSampleType,
cancerTypeString = "Lung Squamous Cell Carcinoma",
nlTissueComparison = "Blood Derived Normal",
tumorTissueComparison = "Primary Tumor",
flagForAlternativeNormal = FALSE,
cancerTypeStringAlternativeNormal = NULL,
caretModel = "gbm",
numResampleIter = 1,
numKFold = 2,
testSetProp = 0.7,
caretTuneGrid = lsccGBMGrid)
#---------- Predict tumor vs normal using cancer microbiome in Lymphoid Neoplasm Diffuse Large B-cell Lymphoma ----------#
# 55 T / 7 NB **************
dlbclGBMGrid <- expand.grid(interaction.depth = seq(1,3),
n.trees = floor((1:3) * 50),
shrinkage = 0.1,
n.minobsinnode = 1)
dlbclPredTumorVsNormalBlood <- predTumorVsNormalFA_Patent(qcMLMetadata = metadataSamplesAllQC,
qcMLDataSNM = snmDataSampleType,
cancerTypeString = "Lymphoid Neoplasm Diffuse Large B-cell Lymphoma",
nlTissueComparison = "Blood Derived Normal",
tumorTissueComparison = "Primary Tumor",
flagForAlternativeNormal = FALSE,
cancerTypeStringAlternativeNormal = NULL,
caretModel = "gbm",
numResampleIter = 1,
numKFold = 2,
testSetProp = 0.7,
caretTuneGrid = dlbclGBMGrid)
#---------- Predict tumor vs normal using cancer microbiome in Mesothelioma ----------#
# 87 T / 134 N (LAD)
mesotheliomaPredTumorVsLADNormalTissue <- predTumorVsNormalFA_Patent(qcMLMetadata = metadataSamplesAllQC,
qcMLDataSNM = snmDataSampleType,
cancerTypeString = "Mesothelioma",
nlTissueComparison = "Solid Tissue Normal",
tumorTissueComparison = "Primary Tumor",
flagForAlternativeNormal = TRUE,
cancerTypeStringAlternativeNormal = "Lung Adenocarcinoma",
caretModel = "gbm",
numResampleIter = 1,
numKFold = 2,
testSetProp = 0.7,
caretTuneGrid = defaultGBMGrid)
#---------- Predict tumor vs normal using cancer microbiome in Ovarian Serous Cystadenocarcinoma ----------#
# 919 T / 16 N ************
ovGBMGrid <- expand.grid(interaction.depth = seq(1,3),
n.trees = floor((1:3) * 50),
shrinkage = 0.1,
n.minobsinnode = 1)
ovarianPredTumorVsNormalTissue <- predTumorVsNormalFA_Patent(qcMLMetadata = metadataSamplesAllQC,
qcMLDataSNM = snmDataSampleType,
cancerTypeString = "Ovarian Serous Cystadenocarcinoma",
nlTissueComparison = "Solid Tissue Normal",
tumorTissueComparison = "Primary Tumor",
flagForAlternativeNormal = FALSE,
cancerTypeStringAlternativeNormal = NULL,
caretModel = "gbm",
numResampleIter = 1,
numKFold = 2,
testSetProp = 0.7,
caretTuneGrid = ovGBMGrid)
# 919 T / 68 NB
ovarianPredTumorVsNormalBlood <- predTumorVsNormalFA_Patent(qcMLMetadata = metadataSamplesAllQC,
qcMLDataSNM = snmDataSampleType,
cancerTypeString = "Ovarian Serous Cystadenocarcinoma",
nlTissueComparison = "Blood Derived Normal",
tumorTissueComparison = "Primary Tumor",
flagForAlternativeNormal = FALSE,
cancerTypeStringAlternativeNormal = NULL,
caretModel = "gbm",
numResampleIter = 1,
numKFold = 2,
testSetProp = 0.7,
caretTuneGrid = defaultGBMGrid)
#---------- Predict tumor vs normal using cancer microbiome in Pancreatic Adenocarcinoma ----------#
# 178 T / 4 N ****************
padGBMGrid <- expand.grid(interaction.depth = seq(1,3),
n.trees = floor((1:3) * 50),
shrinkage = 0.1,
n.minobsinnode = 1)
padPredTumorVsNormalTissue <- predTumorVsNormalFA_Patent(qcMLMetadata = metadataSamplesAllQC,
qcMLDataSNM = snmDataSampleType,
cancerTypeString = "Pancreatic Adenocarcinoma",
nlTissueComparison = "Solid Tissue Normal",
tumorTissueComparison = "Primary Tumor",
flagForAlternativeNormal = FALSE,
cancerTypeStringAlternativeNormal = NULL,
caretModel = "gbm",
numResampleIter = 1,
numKFold = 2,
testSetProp = 0.7,
caretTuneGrid = padGBMGrid,
bag.fraction = 0.75)
#---------- Predict tumor vs normal using cancer microbiome in Pheochromocytoma and Paraganglioma ----------#
# 179 T / 3 N ****************
pheoGBMGrid <- expand.grid(interaction.depth = seq(1,3),
n.trees = floor((1:3) * 50),
shrinkage = 0.1,
n.minobsinnode = 1)
pheoPredTumorVsNormalTissue <- predTumorVsNormalFA_Patent(qcMLMetadata = metadataSamplesAllQC,
qcMLDataSNM = snmDataSampleType,
cancerTypeString = "Pheochromocytoma and Paraganglioma",
nlTissueComparison = "Solid Tissue Normal",
tumorTissueComparison = "Primary Tumor",
flagForAlternativeNormal = FALSE,
cancerTypeStringAlternativeNormal = NULL,
caretModel = "gbm",
numResampleIter = 1,
numKFold = 2,
testSetProp = 0.5,
caretTuneGrid = pheoGBMGrid,
bag.fraction = 0.9)
#---------- Predict tumor vs normal using cancer microbiome in Prostate Adenocarcinoma ----------#
# 641 T / 67 N
prostatePredTumorVsNormalTissue <- predTumorVsNormalFA_Patent(qcMLMetadata = metadataSamplesAllQC,
qcMLDataSNM = snmDataSampleType,
cancerTypeString = "Prostate Adenocarcinoma",
nlTissueComparison = "Solid Tissue Normal",
tumorTissueComparison = "Primary Tumor",
flagForAlternativeNormal = FALSE,
cancerTypeStringAlternativeNormal = NULL,
caretModel = "gbm",
numResampleIter = 1,
numKFold = 2,
testSetProp = 0.7,
caretTuneGrid = defaultGBMGrid)
# 641 T / 121 NB
prostatePredTumorVsNormalBlood <- predTumorVsNormalFA_Patent(qcMLMetadata = metadataSamplesAllQC,
qcMLDataSNM = snmDataSampleType,
cancerTypeString = "Prostate Adenocarcinoma",
nlTissueComparison = "Blood Derived Normal",
tumorTissueComparison = "Primary Tumor",
flagForAlternativeNormal = FALSE,
cancerTypeStringAlternativeNormal = NULL,
caretModel = "gbm",
numResampleIter = 1,
numKFold = 2,
testSetProp = 0.7,
caretTuneGrid = defaultGBMGrid)
#---------- Predict tumor vs normal using cancer microbiome in Rectum Adenocarcinoma ----------#
# 641 T / 67 N
rectumGBMGrid <- expand.grid(interaction.depth = seq(1,3),
n.trees = floor((1:3) * 50),
shrinkage = 0.1,
n.minobsinnode = 1)
rectumPredTumorVsNormalTissue <- predTumorVsNormalFA_Patent(qcMLMetadata = metadataSamplesAllQC,
qcMLDataSNM = snmDataSampleType,
cancerTypeString = "Rectum Adenocarcinoma",
nlTissueComparison = "Solid Tissue Normal",
tumorTissueComparison = "Primary Tumor",
flagForAlternativeNormal = FALSE,
cancerTypeStringAlternativeNormal = NULL,
caretModel = "gbm",
numResampleIter = 1,
numKFold = 2,
testSetProp = 0.7,
caretTuneGrid = rectumGBMGrid)
# 641 T / 121 NB
rectumPredTumorVsNormalBlood <- predTumorVsNormalFA_Patent(qcMLMetadata = metadataSamplesAllQC,
qcMLDataSNM = snmDataSampleType,
cancerTypeString = "Rectum Adenocarcinoma",
nlTissueComparison = "Blood Derived Normal",
tumorTissueComparison = "Primary Tumor",
flagForAlternativeNormal = FALSE,
cancerTypeStringAlternativeNormal = NULL,
caretModel = "gbm",
numResampleIter = 1,
numKFold = 2,
testSetProp = 0.7,
caretTuneGrid = defaultGBMGrid)
#---------- Predict tumor vs normal using cancer microbiome in Sarcoma ----------#
# 299 T / 7 N *************
sarcomaGBMGrid <- expand.grid(interaction.depth = seq(1,3),
n.trees = floor((1:3) * 50),
shrinkage = 0.1,
n.minobsinnode = 1)
sarcomaPredTumorVsNormalTissue <- predTumorVsNormalFA_Patent(qcMLMetadata = metadataSamplesAllQC,
qcMLDataSNM = snmDataSampleType,
cancerTypeString = "Sarcoma",
nlTissueComparison = "Solid Tissue Normal",
tumorTissueComparison = "Primary Tumor",
flagForAlternativeNormal = FALSE,
cancerTypeStringAlternativeNormal = NULL,
caretModel = "gbm",
numResampleIter = 1,
numKFold = 2,
testSetProp = 0.7,
caretTuneGrid = sarcomaGBMGrid)
# 299 T / 36 NB
sarcomaPredTumorVsNormalBlood <- predTumorVsNormalFA_Patent(qcMLMetadata = metadataSamplesAllQC,
qcMLDataSNM = snmDataSampleType,
cancerTypeString = "Sarcoma",
nlTissueComparison = "Blood Derived Normal",
tumorTissueComparison = "Primary Tumor",
flagForAlternativeNormal = FALSE,
cancerTypeStringAlternativeNormal = NULL,
caretModel = "gbm",
numResampleIter = 1,
numKFold = 2,
testSetProp = 0.7,
caretTuneGrid = defaultGBMGrid)
#---------- Predict tumor vs normal using cancer microbiome in Skin Cutaneous Melanoma ----------#
# 122 T / 158 N
skincutaneousmelanomaPredTumorVsNormalBlood <- predTumorVsNormalFA_Patent(qcMLMetadata = metadataSamplesAllQC,
qcMLDataSNM = snmDataSampleType,
cancerTypeString = "Skin Cutaneous Melanoma",
nlTissueComparison = "Blood Derived Normal",
tumorTissueComparison = "Primary Tumor",
flagForAlternativeNormal = FALSE,
cancerTypeStringAlternativeNormal = NULL,
caretModel = "gbm",
numResampleIter = 1,
numKFold = 2,
testSetProp = 0.7,
caretTuneGrid = defaultGBMGrid)
# 511 M / 122 T
skincutaneousmelanomaPredMetastaticTumorVsPrimaryTumor <- predTumorVsNormalFA_Patent(qcMLMetadata = metadataSamplesAllQC,
qcMLDataSNM = snmDataSampleType,
cancerTypeString = "Skin Cutaneous Melanoma",
nlTissueComparison = "Primary Tumor",
tumorTissueComparison = "Metastatic",
flagForAlternativeNormal = FALSE,
cancerTypeStringAlternativeNormal = NULL,
caretModel = "gbm",
numResampleIter = 1,
numKFold = 2,
testSetProp = 0.7,
caretTuneGrid = defaultGBMGrid)
#---------- Predict tumor vs normal using cancer microbiome in Stomach Adenocarcinoma ----------#
# 862 T / 114 N
stomachPredTumorVsNormalTissue <- predTumorVsNormalFA_Patent(qcMLMetadata = metadataSamplesAllQC,
qcMLDataSNM = snmDataSampleType,
cancerTypeString = "Stomach Adenocarcinoma",
nlTissueComparison = "Solid Tissue Normal",
tumorTissueComparison = "Primary Tumor",
flagForAlternativeNormal = FALSE,
cancerTypeStringAlternativeNormal = NULL,
caretModel = "gbm",
numResampleIter = 1,
numKFold = 2,
testSetProp = 0.7,
caretTuneGrid = defaultGBMGrid)
# 862 T / 116 NB
stomachPredTumorVsNormalBlood <- predTumorVsNormalFA_Patent(qcMLMetadata = metadataSamplesAllQC,
qcMLDataSNM = snmDataSampleType,
cancerTypeString = "Stomach Adenocarcinoma",
nlTissueComparison = "Blood Derived Normal",
tumorTissueComparison = "Primary Tumor",
flagForAlternativeNormal = FALSE,
cancerTypeStringAlternativeNormal = NULL,
caretModel = "gbm",
numResampleIter = 1,
numKFold = 2,
testSetProp = 0.7,
caretTuneGrid = defaultGBMGrid)
#---------- Predict tumor vs normal using cancer microbiome in Testicular Germ Cell Tumors ----------#
# 150 T / 121 NB (Prostate Adeno)
testicularPredTumorVsProstateAdenoNormalBlood <- predTumorVsNormalFA_Patent(qcMLMetadata = metadataSamplesAllQC,
qcMLDataSNM = snmDataSampleType,
cancerTypeString = "Testicular Germ Cell Tumors",
nlTissueComparison = "Blood Derived Normal",
tumorTissueComparison = "Primary Tumor",
flagForAlternativeNormal = TRUE,
cancerTypeStringAlternativeNormal = "Prostate Adenocarcinoma",
caretModel = "gbm",
numResampleIter = 1,
numKFold = 2,
testSetProp = 0.7,
caretTuneGrid = defaultGBMGrid)
#---------- Predict tumor vs normal using cancer microbiome in Thymoma ----------#
# 120 T / 79 N (Thyroid Carcinoma)
thymomaPredTumorVsThyroidCarcinomaNormalTissue <- predTumorVsNormalFA_Patent(qcMLMetadata = metadataSamplesAllQC,
qcMLDataSNM = snmDataSampleType,
cancerTypeString = "Thymoma",
nlTissueComparison = "Solid Tissue Normal",
tumorTissueComparison = "Primary Tumor",
flagForAlternativeNormal = TRUE,
cancerTypeStringAlternativeNormal = "Thyroid Carcinoma",
caretModel = "gbm",
numResampleIter = 1,
numKFold = 2,
testSetProp = 0.7,
caretTuneGrid = defaultGBMGrid)
#---------- Predict tumor vs normal using cancer microbiome in Thyroid Carcinoma ----------#
# 655 T / 79 N
thyroidcarcinomaPredTumorVsNormalTissue <- predTumorVsNormalFA_Patent(qcMLMetadata = metadataSamplesAllQC,
qcMLDataSNM = snmDataSampleType,
cancerTypeString = "Thyroid Carcinoma",
nlTissueComparison = "Solid Tissue Normal",
tumorTissueComparison = "Primary Tumor",
flagForAlternativeNormal = FALSE,
cancerTypeStringAlternativeNormal = NULL,
caretModel = "gbm",
numResampleIter = 1,
numKFold = 2,
testSetProp = 0.7,
caretTuneGrid = defaultGBMGrid)
# 655 T / 137 NB
thyroidcarcinomaPredTumorVsNormalBlood <- predTumorVsNormalFA_Patent(qcMLMetadata = metadataSamplesAllQC,
qcMLDataSNM = snmDataSampleType,
cancerTypeString = "Thyroid Carcinoma",
nlTissueComparison = "Blood Derived Normal",
tumorTissueComparison = "Primary Tumor",
flagForAlternativeNormal = FALSE,
cancerTypeStringAlternativeNormal = NULL,
caretModel = "gbm",
numResampleIter = 1,
numKFold = 2,
testSetProp = 0.7,
caretTuneGrid = defaultGBMGrid)
#---------- Predict tumor vs normal using cancer microbiome in Uterine Carcinosarcoma ----------#
# 57 T / 45 N (Uterine Corpus Endometrial Carcinoma)
uterinecarcinosarcomaPredTumorVsEndometrialCarcinomaNormalTissue <- predTumorVsNormalFA_Patent(qcMLMetadata = metadataSamplesAllQC,
qcMLDataSNM = snmDataSampleType,
cancerTypeString = "Uterine Carcinosarcoma",
nlTissueComparison = "Solid Tissue Normal",
tumorTissueComparison = "Primary Tumor",
flagForAlternativeNormal = TRUE,
cancerTypeStringAlternativeNormal = "Uterine Corpus Endometrial Carcinoma",
caretModel = "gbm",
numResampleIter = 1,
numKFold = 2,
testSetProp = 0.7,
caretTuneGrid = defaultGBMGrid)
#---------- Predict tumor vs normal using cancer microbiome in Uterine Corpus Endometrial Carcinoma ----------#
# 1032 T / 45 N
endometrialcarcinomaPredTumorVsNormalTissue <- predTumorVsNormalFA_Patent(qcMLMetadata = metadataSamplesAllQC,
qcMLDataSNM = snmDataSampleType,
cancerTypeString = "Uterine Corpus Endometrial Carcinoma",
nlTissueComparison = "Solid Tissue Normal",
tumorTissueComparison = "Primary Tumor",
flagForAlternativeNormal = FALSE,
cancerTypeStringAlternativeNormal = NULL,
caretModel = "gbm",
numResampleIter = 1,
numKFold = 2,
testSetProp = 0.7,
caretTuneGrid = defaultGBMGrid)
# 1032 T / 161 NB
endometrialcarcinomaPredTumorVsNormalBlood <- predTumorVsNormalFA_Patent(qcMLMetadata = metadataSamplesAllQC,
qcMLDataSNM = snmDataSampleType,
cancerTypeString = "Uterine Corpus Endometrial Carcinoma",
nlTissueComparison = "Blood Derived Normal",
tumorTissueComparison = "Primary Tumor",
flagForAlternativeNormal = FALSE,
cancerTypeStringAlternativeNormal = NULL,
caretModel = "gbm",
numResampleIter = 1,
numKFold = 2,
testSetProp = 0.7,
caretTuneGrid = defaultGBMGrid)
#---------- Predict tumor vs normal using cancer microbiome in Uveal Melanoma ----------#
# 131 T / 51 NB
uvealmelanomaPredTumorVsNormalBlood <- predTumorVsNormalFA_Patent(qcMLMetadata = metadataSamplesAllQC,
qcMLDataSNM = snmDataSampleType,
cancerTypeString = "Uveal Melanoma",
nlTissueComparison = "Blood Derived Normal",
tumorTissueComparison = "Primary Tumor",
flagForAlternativeNormal = FALSE,
cancerTypeStringAlternativeNormal = NULL,
caretModel = "gbm",
numResampleIter = 1,
numKFold = 2,
testSetProp = 0.7,
caretTuneGrid = defaultGBMGrid)
# save.image(file = "mlPredTumorVsNormalAllTumors.RData")
mlModelListTumorVsNormalMicrobes <- list(
adrenocorticalcarcinomaPredTumorVsRCCNormalTissue = adrenocorticalcarcinomaPredTumorVsRCCNormalTissue,
bladderPredTumorVsNormalTissue = bladderPredTumorVsNormalTissue,
bladderPredTumorVsNormalBlood = bladderPredTumorVsNormalBlood,
blggPredTumorVsNormalBlood = blggPredTumorVsNormalBlood,
blggPredPrimaryTumorVsRecurrentTumor = blggPredPrimaryTumorVsRecurrentTumor,
bicPredTumorVsNormalTissue = bicPredTumorVsNormalTissue,
bicPredTumorVsNormalBlood = bicPredTumorVsNormalBlood,
bicPredPrimaryTumorVsMetastaticTumor = bicPredPrimaryTumorVsMetastaticTumor,
cervicalPredTumorVsNormalTissue = cervicalPredTumorVsNormalTissue,
cervicalPredTumorVsNormalBlood = cervicalPredTumorVsNormalBlood,
cholPredTumorVsNormalTissue = cholPredTumorVsNormalTissue,
colonPredTumorVsNormalTissue = colonPredTumorVsNormalTissue,
colonPredTumorVsNormalBlood = colonPredTumorVsNormalBlood,
esophagealcarcinomaPredTumorVsNormalTissue = esophagealcarcinomaPredTumorVsNormalTissue,
esophagealcarcinomaPredTumorVsNormalBlood = esophagealcarcinomaPredTumorVsNormalBlood,
# gbmPredTumorVsNormalTissue = gbmPredTumorVsNormalTissue, # too few normal tissue samples on which to use for ML
gbmPredTumorVsNormalBlood = gbmPredTumorVsNormalBlood,
hnsccPredTumorVsNormalTissue = hnsccPredTumorVsNormalTissue,
hnsccPredTumorVsNormalBlood = hnsccPredTumorVsNormalBlood,
kidneychromophobePredTumorVsNormalTissue = kidneychromophobePredTumorVsNormalTissue,
rccPredTumorVsNormalTissue = rccPredTumorVsNormalTissue,
rpccPredTumorVsNormalTissue = rpccPredTumorVsNormalTissue,
rpccPredTumorVsNormalBlood = rpccPredTumorVsNormalBlood,
hccPredTumorVsNormalTissue = hccPredTumorVsNormalTissue,
hccPredTumorVsNormalBlood = hccPredTumorVsNormalBlood,
ladPredTumorVsNormalTissue = ladPredTumorVsNormalTissue,
ladPredTumorVsNormalBlood = ladPredTumorVsNormalBlood,
lsccPredTumorVsNormalTissue = lsccPredTumorVsNormalTissue,
lsccPredTumorVsNormalBlood = lsccPredTumorVsNormalBlood,
dlbclPredTumorVsNormalBlood = dlbclPredTumorVsNormalBlood,
mesotheliomaPredTumorVsLADNormalTissue = mesotheliomaPredTumorVsLADNormalTissue,
ovarianPredTumorVsNormalTissue = ovarianPredTumorVsNormalTissue,
ovarianPredTumorVsNormalBlood = ovarianPredTumorVsNormalBlood,
padPredTumorVsNormalTissue = padPredTumorVsNormalTissue,
pheoPredTumorVsNormalTissue = pheoPredTumorVsNormalTissue,
prostatePredTumorVsNormalTissue = prostatePredTumorVsNormalTissue,
prostatePredTumorVsNormalBlood = prostatePredTumorVsNormalBlood,
rectumPredTumorVsNormalTissue = rectumPredTumorVsNormalTissue,