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Check the data for a follow up experiment.

Source: R/follow_up.R
valid_followup.Rd

Sometimes some samples are collected and analyzed, later another batch of samples is analyzed. This function tries to detect if there are problems with the data or when the data is combined in a single analysis. To know specific problems with the data you need to use check_data()

Usage

valid_followup(
  old_data = NULL,
  new_data = NULL,
  all_data = NULL,
  omit = NULL,
  column = "batch"
)

Arguments

old_data, new_data

A data.frame with the old and new data respectively.

all_data

A data.frame with all the data about the samples. Each row is a sample.

omit

Name of the columns of the pheno that will be omitted.

column

The name of the column where the old data has the batch information, or whether the data is new or not (NA) in the case of all_data.

Value

Called by its side effects of warnings, but returns a logical value if there are some issues (FALSE) or not (TRUE)

See also

check_data()

Examples

data(survey, package = "MASS")
survey1 <- survey[1:118, ]
survey2 <- survey[119:nrow(survey), ]
valid_followup(survey1, survey2)
#> Warning: There are some problems with the data.
#> Warning: There are some problems with the new samples and the batches.
#> Warning: There are some problems with the new data.
#> Warning: There are some problems with the old data.
#> [1] FALSE
survey$batch <- NA
survey$batch[1:118]  <- "old"
valid_followup(all_data = survey)
#> Warning: There are some problems with the data.
#> Warning: There are some problems with the new samples and the batches.
#> Warning: There are some problems with the new data.
#> Warning: There are some problems with the old data.
#> [1] FALSE