In neurodata/r-mgc: Multiscale Graph Correlation

require(ggplot2)
require(scales)
require(lme4)
require(reshape2)
require(dplyr)
library(tidyr)
require(ggbeeswarm)
require(latex2exp)
require(ggExtra)
require(ggpubr)
require(grid)
require(gridExtra)
require(stringr)
require(data.table)

fmri.results <- readRDS('../data/real/discr_fmri_results.rds')
dmri.results <- readRDS('../data/real/discr_dmri_results.rds')

fMRI Multiplot

reg_opts <- c("A", "F")
names(reg_opts) <- c("ANTs", "FSL")
freq_opts <- c("F", "N")
names(freq_opts) <- c(TRUE, FALSE)
scrub_opts <- c("S", "X")
names(scrub_opts) <- c(TRUE, FALSE)
gsr_opts <- c("G", "X")
names(gsr_opts) <- c(TRUE, FALSE)
atlas_opts <- c("A", "C", "D", "H")
names(atlas_opts) <- c("AAL", "CC200", "Desikan", "HO")
dsets <- unique(fmri.results$Dataset)

fmri.results <- do.call(rbind, lapply(1:dim(fmri.results)[1], function(i) {
  dat <- fmri.results[i,]
  name <- paste(reg_opts[as.character(dat$Reg)], 
                freq_opts[abs(as.numeric(dat$FF) - 1) + 1],
                scrub_opts[abs(as.numeric(dat$Scr) - 1) + 1],
                gsr_opts[abs(as.numeric(dat$GSR) - 1) + 1],
                atlas_opts[as.character(dat$Parcellation)], sep="")
  return(cbind(data.frame(Name=name), dat))
}))

nan.mean <- function(x) {
  mean(x, na.rm=TRUE)
}
fmri.summarized <- aggregate(list(me.discr=fmri.results$discr), 
                             by=list(Name=fmri.results$Name), FUN=nan.mean)
fmri.results$Name <- factor(fmri.results$Name, 
                                levels=as.character(fmri.summarized$Name[order(fmri.summarized$me.discr, decreasing = TRUE)]),
                                ordered=TRUE)

ggplot(fmri.results, aes(x=Name, y=discr, color=Dataset, size=nscans)) +
  geom_point() +
  xlab("Preprocessing Strategy") +
  ylab("Discriminability") +
  theme_bw() +
  ggtitle("Comparing Discriminability Across 64 Preprocessing Strategies") +
  theme(axis.text.x=element_text(angle=90)) +
  scale_size_continuous(name="#Scans") +
  stat_summary(fun.y="mean", color="black", geom="point", shape="triangle", size=2) +
  guides(color=guide_legend(ncol=2))

fMRI Option-Wise plots

for (col in c("Reg", "FF", "Scr", "GSR", "Parcellation")) {

}

neurodata/r-mgc documentation built on March 12, 2021, 9:45 a.m.