Skip to contents

Make mxFDA class object

Source: R/make_mxfda.R
make_mxfda.Rd

Used to create an object of class mxFDA that can be used with the mxfda package for functional data analysis.

Usage

make_mxfda(metadata, spatial = NULL, subject_key, sample_key)

Arguments

metadata

metadata with columns subject_key and sample_key

spatial

spatial information, either list or df, with column sample_key. Spatial can be empty if inputting data already derived. See add_summary_function() for more details.

subject_key

column name in Metadata for subject ID

sample_key

column linking Metadata to Spatial data

Value

S4 object of class mxFDA

Metadata

slot of class data.frame that contains sample and subject level information

Spatial

slot of class data.frame that contains point level information within samples. An example would be cells belonging to TMA cores

subject_key

slot of class character that corresponds to a column in the Metadata slot that groups samples at a subject level. An example would be "patient_id"

sample_key

slot of class character that corresponds to a column both in the Metadata and Spatial slots that links samples to characteristics

univariate_summaries

slot of class list where univariate summary functions calculated on Spatial would be stored

bivariate_summaries

slot of class list where bivariate summary functions calculated on Spatial would be stored

multiivariate_summaries

slot of class list where entropy summary functions calculated on Spatial would be stored

functional_pca

slot of class list where FPCA results are stored

functional_mpca

slot of class list where MFPCA results are stored

functional_cox

slot of class list where functional cox model results are stored

functional_mcox

slot of class list where mixed functional cox model results are stored

scalar_on_function

slot of class list where functional models are fit to scalar responses

Details

[Stable]

Author

Alex Soupir alex.soupir@moffitt.org

Examples

#select sample metadata
clinical = lung_df %>%
  dplyr::select(image_id, patient_id, patientImage_id,
                gender, age, survival_days, survival_status, stage) %>%
  dplyr::distinct()
#select the spatial information
spatial = lung_df %>%
  dplyr::select(-image_id, -gender, -age, -survival_days, -survival_status, -stage)
sample_id_column = "patientImage_id"
#create the mxFDA object
mxFDAobject = make_mxfda(metadata = clinical,
                         spatial = spatial,
                         subject_key = "patient_id",
                         sample_key = sample_id_column)