cv.glmSparseNet.mclapply: Calculate cross validating GLM model with network-based...

Description Usage Arguments Details Value Examples

Description

network parameter accepts:

Usage

1
2
cv.glmSparseNet.mclapply(xdata, ydata, network,
  network.options = network.options.default(), ...)

Arguments

xdata

input data, can be a matrix or MultiAssayExperiment

ydata

response data compatible with glmnet

network

type of network, see below

network.options

options to calculate network

...

parameters that cv.glmnet accepts

Details

* string to calculate network based on data (correlation, covariance) * matrix representing the network * vector with already calculated penalty weights (can also be used directly with glmnet)

Value

an object just as cv.glmnet

Examples

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
xdata <- matrix(rnorm(100), ncol = 20)
cv.glmSparseNet(xdata, rnorm(nrow(xdata)), 'correlation', family = 'gaussian')
cv.glmSparseNet(xdata, rnorm(nrow(xdata)), 'covariance', family = 'gaussian')

#
#
# Using MultiAssayExperiment

# load data
xdata <- MultiAssayExperiment::miniACC
# build valid data with days of last follow up or to event
event.ix <- which(!is.na(xdata$days_to_death))
cens.ix <- which(!is.na(xdata$days_to_last_followup))
xdata$surv_event_time <- array(NA, nrow(xdata@colData))
xdata$surv_event_time[event.ix] <- xdata$days_to_death[event.ix]
xdata$surv_event_time[cens.ix] <- xdata$days_to_last_followup[cens.ix]
# Keep only valid individuals
valid.ix <- as.vector(!is.na(xdata$surv_event_time) &
                      !is.na(xdata$vital_status) &
                      xdata$surv_event_time > 0)
xdata.valid <- xdata[, rownames(xdata@colData)[valid.ix]]
ydata.valid <- xdata.valid@colData[,c('surv_event_time', 'vital_status')]
colnames(ydata.valid) <- c('time', 'status')
cv.glmSparseNet(xdata.valid,
                  ydata.valid,
                  family          = 'cox',
                  network         = 'correlation',
                  experiment.name = 'RNASeq2GeneNorm',
                  mc.cores = 10)

averissimo/glmSparseNetPaper documentation built on Jan. 25, 2021, 12:11 p.m.