Skip to content
/ FFR Public

Function-on-function regression with the goal of identifying critical windows of susceptibility to environmental exposures.

Notifications You must be signed in to change notification settings

mzemplenyi/FFR

Repository files navigation

FFR

Function-on-Function Regression Matlab files for 'Function-on-Function Regression for the Identification of Epigenetic Regions Exhibiting Windows of Susceptibility to Environmental Exposures' by Zemplenyi, Meyer, Cardenas, et al. (pre-print available on arXiv: https://arxiv.org/abs/1912.07359. This code base builds upon the WFMM package created at MD Anderson, available here: https://biostatistics.mdanderson.org/SoftwareDownload/SingleSoftware/Index/70.

Files:

  • run_FFR.m: script to initiate a function-on-function regression analysis. You can use either the simulated exposure ("simX_N400_T90.csv") and response ("simY_N400_S100.csv") data provided or specify the exposure, response, and covariate data for your custom analysis.
  • generate_X.m: script used to generate the simulated exposure data contained in "simX_N400_T90.csv."
  • generate_Y.m: script used to generate the simulated response data contained in "simY_N400_S100.csv."
  • make_sim_heatmaps.m: function called by script "run_FFR.m" that creates three heatmaps (estimated beta surface, Bayesian false discovery rate, and simutaneous band scores) using the "results.mat" object from the FFR analysis.
  • The following outputs are sent to the "Results" folder after the script has finished:
    • "FFR_output.mat" raw results object
    • three heatmaps (estimated beta surface, Bayesian False Discovery Rate inferential procedure, and Simultaneous Band Score inferential procedure)

About

Function-on-function regression with the goal of identifying critical windows of susceptibility to environmental exposures.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages