Description Usage Arguments Details Value Examples
Make a nanodrop object
1 2 3 4 5 6 |
data |
a |
date |
an optional character vector or something coercible to a |
nucleotide |
a character vector to specifying the analyte in the nanodrop experiment. Must match one of the following: RNA, DNA, dsDNA, or dsRNA. |
is_tidy |
logical. Is the supplied data tidy? |
Making a nanodrop object 'by hand' (that is, not using
read_nanodrop
) is not recommended, since it is challenging to ensure a
given data.frame
is truly a valid nanodrop file. To increase reliability,
flexibility is reduced. As such, the supplied data.frame
must at least
have the following columns if is_tidy = TRUE
:
date
sample_name
conc
a260_280
a230_280
If is_tidy = FALSE
, at least the following columns must be provided:
Date
Sample.Name
Nucleic.Acid.ng.uL.
A260.A280
A260.A230
Note: technically, the given column names will be stripped of all
non-alphanumerics and forced tolower
, then compared against the following:
date
samplename
nucleicacidngul
a260a280
a260a230
In both cases, other columns allowed are those that appear in Example A and Example B below.
If there are additional columns provided, they will be silently dropped.
a nanodrop
object
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | # Example A: colnames allowed when is_tidy = FALSE
a <- system.file("extdata", "nanodrop.csv", package = "ragaki") |>
read_nanodrop()
colnames(a$data)
# Technically, these are the names that are checked for after the given names
# have alphanumerics removed and are converted to lowercase:
colnames(a$data) |> stringr::str_remove_all("[^[:alnum:]]") |> tolower()
# Example B: colnames allowed when is_tidy = TRUE
b <- a |> tidy_lab()
colnames(b$data)
|
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