This function allows people to have their data ready to be processed by gimap
setup_data(counts = NULL, pg_ids = NULL, sample_metadata = NULL)a matrix of data that contains the counts where rows are each paired_guide target and columns are each sample
the pgRNA IDs: metadata associated with the pgRNA constructs that correspond to the rows of the counts data
metadata associated with the samples of the dataset that correspond to the columns of the counts data. Should include a column that has replicate information as well as a column that contains timepoint information respectively (this will be used for log fold calculations). These columns should be factors.
A special gimap_dataset to be used with the other functions in this package.
counts <- get_example_data("count", data_dir = tempdir()) %>%
dplyr::select(c(
"Day00_RepA", "Day05_RepA", "Day22_RepA", "Day22_RepB",
"Day22_RepC"
)) %>%
as.matrix()
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pg_ids <- get_example_data("count", data_dir = tempdir()) %>%
dplyr::select("id")
sample_metadata <- data.frame(
col_names = c("Day00_RepA", "Day05_RepA", "Day22_RepA", "Day22_RepB", "Day22_RepC"),
day = as.numeric(c("0", "5", "22", "22", "22")),
rep = as.factor(c("RepA", "RepA", "RepA", "RepB", "RepC"))
)
gimap_dataset <- setup_data(
counts = counts,
pg_ids = pg_ids,
sample_metadata = sample_metadata
)