This function merges MIF objects that were run separately so they can be used as a single MIF. MIF objects don't need but should have the same column names in the summary file and clinical data file. The MIF objects DO need to have the same patient_id and sample_id.
Value
Returns a new MIF object list
- clinical_data
clinical information from all
- sample
cell level summary data from all
- spatial
contains all spatial files from all MIFs
- derived
appended derived variables
- patient_id
patient_id from the first MIF - this is why it is important to have the same patient_id for all MIFs
- sample_id
sample_id from the first MIF - also important for all MIFs to have the same sample_id
Examples
#merge several MIF objects
library(dplyr)
x <- create_mif(clinical_data = example_clinical %>%
mutate(deidentified_id = as.character(deidentified_id)),
sample_data = example_summary %>%
mutate(deidentified_id = as.character(deidentified_id)),
spatial_list = example_spatial,
patient_id = "deidentified_id",
sample_id = "deidentified_sample")
x <- merge_mifs(mifs = list(x, x), check.names = FALSE)
#> No variables have been derived yet