Nothing

```
library(regsplice)
context("glmnet error example")
test_that("glmnet error example passes", {
# 'glmnet' version 2.0-2 introduced a bug in the cross validation step, which gives
# errors in the 'regsplice' lasso model fitting function '.fitRegSingle()' for some
# random seeds. Earlier versions of 'glmnet' (<= v. 1.9-8) did not have this problem.
# The 'glmnet' package authors have advised that the bug will be fixed in a future
# update. Until then, we have included checks in '.fitRegSingle()' to simply re-run
# the model fitting procedure if the error occurs. This unit test checks that the
# 'regsplice' functions pass for a specific example of the bug. For more details, see
# the GitHub repository at: https://github.com/lmweber/glmnet-error-example
# LOAD DATA
# Y: vector of response values
# X: design matrix of indicator variables and interaction terms
file <- system.file("extdata/data_glmnet_error_example.txt", package = "regsplice")
data <- read.table(file, header = TRUE, sep = "\t", check.names = FALSE)
Y <- data[, 1]
X <- as.matrix(data[, -1])
# PENALTY FACTOR
# penalize interaction terms only
penalty <- rep(c(0, 1), times = c(13, 8))
# SHOW ERROR BY RUNNING CV.GLMNET DIRECTLY (not run)
# cv.glmnet: cross validation for lambda
# The following code demonstrates the error.
# error message: 'Error in predmat[which, seq(nlami)] = preds : replacement has length zero'
#set.seed(1)
#glmnet::cv.glmnet(x = X, y = Y, family = "gaussian", penalty.factor = penalty)
# RUN REGSPLICE MODEL FITTING FUNCTION
# regsplice model fitting function checks for the error and should pass
counts <- matrix(Y, ncol = 6)
gene_IDs <- "gene1"
n_exons <- 9
condition <- rep(c(0, 1), each = 3)
rs_data <- RegspliceData(counts, gene_IDs, n_exons, condition)
# filtering low-count exons can also solve the problem
#rs_data <- filterZeros(rs_data)
#rs_data <- filterLowCounts(rs_data)
rs_results <- initializeResults(rs_data)
# error occurs for set.seed(1) if checks are not included in '.fitRegSingle()'
set.seed(1)
rs_results <- fitRegMultiple(rs_results, rs_data)
# no output object is returned if the error occurs
expect_is(rs_results, "RegspliceResults")
expect_length(rs_results@fit_reg_dev, 1)
expect_length(rs_results@fit_reg_df, 1)
})
```

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