reptile_predict_genome_wide: Predicting enhancer activity

Description Usage Arguments Value Author(s) See Also Examples

View source: R/reptile_predict_genome_wide.R

Description

Predicting enhancer activities of query regions based on the enhancer model from reptile_train in training step. This function calculates the enhancer scores of DMRs and query regions. It does not try to generate combined enhancer scores.

Usage

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reptile_predict_genome_wide(reptile_model,
                            epimark_region,
                            epimark_DMR = NULL,
                            family = "randomForest")

Arguments

reptile_model

Enhancer model from reptile_train. It is a list containing two objects of class randomForest or glm when family is set to be "Logistic"

epimark_region

data.frame instance from read_epigenomic_data, which containing intensity and intensity deviation values of each mark for each query region

epimark_DMR

data.frame instance from read_epigenomic_data, which containing intensity and intensity deviation values of each mark for each DMR

family

classifier family used in the enhancer model

Default: RandomForest

Classifiers available:

- RandomForest: random forest

- Logistic: logistic regression

Value

A list containing two vectors

R

Enhancer score of each query region

DMR

Enhancer score of each DMR

Author(s)

Yupeng He [email protected]

See Also

reptile_predict

reptile_train

read_epigenomic_data

read_label

Examples

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library("REPTILE")
data("rsd")

## Training
rsd_model <- reptile_train(rsd$training_data$region_epimark,
                           rsd$training_data$region_label,
                           rsd$training_data$DMR_epimark,
                           rsd$training_data$DMR_label,
                           ntree=50)

## Prediction
## - REPTILE
pred <- reptile_predict(rsd_model,
                        rsd$test_data$region_epimark,
                        rsd$test_data$DMR_epimark)
## - Random guessing
pred_guess = runif(length(pred$D))
names(pred_guess) = names(pred$D)

## Evaluation
res_reptile <- reptile_eval_prediction(pred$D,
                                       rsd$test_data$region_label)
res_guess <- reptile_eval_prediction(pred_guess,
                                     rsd$test_data$region_label)
## - Print AUROC and AUPR
cat(paste0("REPTILE\n",
           "  AUROC = ",round(res_reptile$AUROC,digit=3),
           "\n",
           "  AUPR  = ",round(res_reptile$AUPR,digit=3))
    ,"\n")
cat(paste0("Random guessing\n",
           "  AUROC = ",round(res_guess$AUROC,digit=3),
           "\n",
           "  AUPR  = ",round(res_guess$AUPR,digit=3))
   ,"\n")

REPTILE documentation built on May 29, 2017, 5:58 p.m.