The inflated vs deflated noise figure in `cashr`

Last updated: 2018-10-09

workflowr checks: (Click a bullet for more information)

✔ R Markdown file: up-to-date

Great! Since the R Markdown file has been committed to the Git repository, you know the exact version of the code that produced these results.
✔ Environment: empty

Great job! The global environment was empty. Objects defined in the global environment can affect the analysis in your R Markdown file in unknown ways. For reproduciblity it’s best to always run the code in an empty environment.
✔ Seed: set.seed(12345)

The command set.seed(12345) was run prior to running the code in the R Markdown file. Setting a seed ensures that any results that rely on randomness, e.g. subsampling or permutations, are reproducible.
✔ Session information: recorded

Great job! Recording the operating system, R version, and package versions is critical for reproducibility.
✔ Repository version: c469399
Great! You are using Git for version control. Tracking code development and connecting the code version to the results is critical for reproducibility. The version displayed above was the version of the Git repository at the time these results were generated.

Note that you need to be careful to ensure that all relevant files for the analysis have been committed to Git prior to generating the results (you can use wflow_publish or wflow_git_commit). workflowr only checks the R Markdown file, but you know if there are other scripts or data files that it depends on. Below is the status of the Git repository when the results were generated:
```
Ignored files:
    Ignored:    .DS_Store
    Ignored:    .Rhistory
    Ignored:    .Rproj.user/
    Ignored:    analysis/.DS_Store
    Ignored:    analysis/cash_paper_fig_leukemia_cache/
    Ignored:    data/LSI/
    Ignored:    docs/.DS_Store
    Ignored:    docs/figure/.DS_Store
    Ignored:    output/fig/
    Ignored:    output/paper/
```
Note that any generated files, e.g. HTML, png, CSS, etc., are not included in this status report because it is ok for generated content to have uncommitted changes.

Expand here to see past versions:

File	Version	Author	Date	Message
rmd	c469399	Lei Sun	2018-10-09	wflow_publish(c(“analysis/cash_paper_fig_g1sep.rmd”,
html	f7bde81	Lei Sun	2018-10-06	Build site.
rmd	3b81007	Lei Sun	2018-10-06	wflow_publish(c(“analysis/cash_paper_fig_g1sep.rmd”,
html	133541a	LSun	2018-10-05	Build site.
rmd	49f870a	LSun	2018-10-05	wflow_publish(c(“cash_paper_fig_leukemia.rmd”, “cash_paper_fig1.rmd”,

Introduction

Generate the inflated vs in-between vs deflated noise figure in the paper.

library(ggplot2)

FDP.list <- readRDS("../output/paper/simulation/FDP.list.rds")
TDP.list <- readRDS("../output/paper/simulation/TDP.list.rds")
z.list <- readRDS("../output/paper/simulation/z.list.rds")
pi0.list <- readRDS("../output/paper/simulation/pi0.list.rds")

pi0.vec <- c(0.5, 0.9, 0.99)
q.vec <- seq(0.001, 0.20, by = 0.001)
q <- 0.1
method.name.FDR <- c("cashr", "BH", "qvalue", "ashr", "locfdr")
method.col.FDR <- scales::hue_pal()(length(method.name.FDR))[c(5, 1, 2, 4, 3)]

#####################################

boxplot.quantile <- function(x) {
  r <- quantile(x, probs = c(0.10, 0.25, 0.5, 0.75, 0.90))
  names(r) <- c("ymin", "lower", "middle", "upper", "ymax")
  return(r)
}

boxplot.quantile.sq <- function (x) {
  r <- sqrt(quantile(x^2, probs = c(0.10, 0.25, 0.5, 0.75, 0.90)))
  names(r) <- c("ymin", "lower", "middle", "upper", "ymax")
  return(r)
}

mean.sq <- function (x) {
  r <- sqrt(mean(x^2))
  return(r)
}

mysqrt_trans <- function() {
  scales::trans_new("mysqrt", 
                    transform = base::sqrt,
                    inverse = function(x) ifelse(x<0, 0, x^2),
                    domain = c(0, Inf))
}

###############################

sd.z <- sapply(z.list, sd)
Noise <- cut(sd.z, breaks = c(0, quantile(sd.z, probs = 1 : 2 / 3), Inf), labels = c("Pseudo Deflation", "In-between", "Pseudo Inflation"))

###############################

pi0.0.9 <- which(pi0.list == 0.9)
sd.z.0.9 <- sd.z[pi0.0.9]
typical.noise <- pi0.0.9[order(sd.z.0.9)[floor(quantile(seq(sd.z.0.9), c(0.1, 0.5, 0.9)))]]

z.list.sel <- z.list[typical.noise]
names(z.list.sel) <- c("Pseudo Deflation", "In-between", "Pseudo Inflation")
z.sep.ggdata <- reshape2::melt(z.list.sel, value.name = "z")
z.sep.ggdata$L1 <- factor(z.sep.ggdata$L1, levels = c("Pseudo Deflation", "In-between", "Pseudo Inflation"))
z.sep.plot <- ggplot(data = z.sep.ggdata, aes(x = z)) +
  geom_histogram(aes(y = ..density..), binwidth = 0.2) +
  facet_wrap(~L1, nrow = 1) +
  stat_function(fun = dnorm, aes(color = "N(0, 1)"), lwd = 1.5, show.legend = TRUE) +
#  scale_color_manual(values = "blue") +
  theme(axis.title.x = element_text(size = 15),
        axis.text.x = element_text(size = 10),
        axis.title.y = element_text(size = 15),
        axis.text.y = element_text(size = 10),
        strip.text = element_text(size = 15),
      # strip.text = element_blank(),
        legend.position = "left",
      # legend.title = element_blank(),
        legend.text = element_text(size = 12),
        legend.key = element_blank()
        )

#########################################

FDP.q <- FDP.list[[which(q.vec == q)]]
FDP.q.noise.mat <- rbind.data.frame(
  cbind.data.frame(Noise = rep("All", length(Noise)),
                   pi0 = factor(do.call(rbind, pi0.list)),
                   FDP.q),
  cbind.data.frame(Noise,
                   pi0 = factor(do.call(rbind, pi0.list)),
                   FDP.q)
)
FDP.q.ggdata <- reshape2::melt(FDP.q.noise.mat, id.vars = c("Noise", "pi0"), variable.name = "Method", value.name = "FDP")

FDP.q.ggdata$Method <- factor(FDP.q.ggdata$Method, levels = c("CASH", "BHq", "qvalue", "ASH", "locfdr"))
FDP.q.ggdata$Method <- plyr::mapvalues(FDP.q.ggdata$Method, from = c("CASH", "BHq", "qvalue", "ASH", "locfdr"), to = c("cashr", "BH", "qvalue", "ashr", "locfdr"))

FDP.q.ggdata.0.9 <- FDP.q.ggdata[FDP.q.ggdata$pi0 == 0.9, ]

################################################

TDP.q <- TDP.list[[which(q.vec == q)]]
TDP.q.noise.mat <- rbind.data.frame(
  cbind.data.frame(Noise = rep("All", length(Noise)),
                   pi0 = factor(do.call(rbind, pi0.list)),
                   TDP.q),
  cbind.data.frame(Noise,
                   pi0 = factor(do.call(rbind, pi0.list)),
                   TDP.q)
)
TDP.q.ggdata <- reshape2::melt(TDP.q.noise.mat, id.vars = c("Noise", "pi0"), variable.name = "Method", value.name = "TDP")

TDP.q.ggdata$Method <- factor(TDP.q.ggdata$Method, levels = c("CASH", "BHq", "qvalue", "ASH", "locfdr"))
TDP.q.ggdata$Method <- plyr::mapvalues(TDP.q.ggdata$Method, from = c("CASH", "BHq", "qvalue", "ASH", "locfdr"), to = c("cashr", "BH", "qvalue", "ashr", "locfdr"))

TDP.q.ggdata.0.9 <- TDP.q.ggdata[TDP.q.ggdata$pi0 == 0.9, ]

##############################################################

# FDP.q.all.sep.plot <- ggplot(data = FDP.q.ggdata, aes(x = pi0, y = FDP, fill = Method, color = Method)) +
#   stat_summary(fun.data = boxplot.quantile, geom = "boxplot", position = "dodge") +
#   stat_summary(fun.y = mean, geom = "point", position = position_dodge(width = 0.9), show.legend = TRUE) +
#   scale_color_manual(labels = method.name.FDR, values = method.col.FDR) +
#   scale_fill_manual(labels = method.name.FDR, values = alpha(method.col.FDR, 0.35)) +
#   facet_wrap(~Noise, nrow = 1) +
#   geom_hline(yintercept = q, col = "black", linetype = "dashed", size = 1) +
#   labs(x = expression(pi[0]), y = "FDP", title = bquote(paste("Nominal FDR = ", .(q)))) +
#   theme(plot.title = element_text(size = 12, hjust = 0),
#         axis.title.x = element_text(size = 15),
#         axis.text.x = element_text(size = 10),
#         axis.title.y = element_text(size = 15),
#         axis.text.y = element_text(size = 10),
#         strip.text = element_text(size = 15),
#         legend.position = "bottom",
#         legend.background = element_rect(color = "grey"),
#         legend.text = element_text(size = 12)
#         )

FDP.q.all.sep.plot <- ggplot(data = FDP.q.ggdata.0.9, aes(x = Method, y = FDP, fill = Method, color = Method)) +
  stat_summary(fun.data = boxplot.quantile, geom = "boxplot", aes(width = 0.5), position = position_dodge(), show.legend = FALSE) +
  stat_summary(fun.y = mean, geom = "point", position = position_dodge(width = 0.9), show.legend = FALSE) +
  scale_x_discrete(limits = rev(levels(FDP.q.ggdata.0.9$Method))) +
  coord_flip() +
  scale_color_manual(labels = method.name.FDR, values = method.col.FDR) +
  scale_fill_manual(labels = method.name.FDR, values = alpha(method.col.FDR, 0.35)) +
  facet_wrap(~Noise, nrow = 1) +
  geom_hline(yintercept = q, col = "black", linetype = "dashed", size = 1) +
  labs(y = "FDP", title = bquote(paste("Nominal FDR = ", .(q), " (", g[1], " is Gaussian; ", pi[0] == 0.9, ")"))) +
  expand_limits(y = 0) +
  theme(plot.title = element_text(size = 12, hjust = 0),
        axis.title.y = element_blank(),
        axis.text.y = element_text(size = 15),
        axis.title.x = element_text(size = 15),
        axis.text.x = element_text(size = 10),
        strip.text = element_text(size = 15),
        legend.position = "bottom",
        legend.background = element_rect(color = "grey"),
        legend.text = element_text(size = 12)
        )

Warning: Ignoring unknown aesthetics: width

FDP.sqrt.q.all.sep.plot <- ggplot(data = FDP.q.ggdata.0.9, aes(x = Method, y = FDP, fill = Method, color = Method)) +
  stat_summary(fun.data = boxplot.quantile.sq, geom = "boxplot", aes(width = 0.5), position = position_dodge(), show.legend = FALSE) +
  stat_summary(fun.y = mean.sq, geom = "point", position = position_dodge(width = 0.9), show.legend = FALSE) +
  scale_x_discrete(limits = rev(levels(FDP.q.ggdata.0.9$Method))) +
  scale_y_continuous(trans = "mysqrt", breaks = c(0, 0.1, 0.2, 0.4, 0.6, 0.8)) +
  coord_flip() +
  scale_color_manual(labels = method.name.FDR, values = method.col.FDR) +
  scale_fill_manual(labels = method.name.FDR, values = alpha(method.col.FDR, 0.35)) +
  facet_wrap(~Noise, nrow = 1) +
  geom_hline(yintercept = q, col = "black", linetype = "dashed", size = 1) +
  labs(x = expression(pi[0]), y = "FDP", title = bquote(paste("Nominal FDR = ", .(q), " (", g[1], " is Gaussian; ", pi[0] == 0.9, ")"))) +
  expand_limits(y = 0) +
  theme(plot.title = element_text(size = 12, hjust = 0),
        axis.title.y = element_blank(),
        axis.text.y = element_text(size = 15),
        axis.title.x = element_text(size = 15),
        axis.text.x = element_text(size = 10),
        strip.text = element_text(size = 15),
        legend.position = "bottom",
        legend.background = element_rect(color = "grey"),
        legend.text = element_text(size = 12)
        )

Warning: Ignoring unknown aesthetics: width

###############################################

blank.ggdata <- data.frame()
blank.plot <- ggplot(data = blank.ggdata) +
  theme(panel.background = element_blank(),
        panel.border = element_blank(),
        panel.grid.major = element_blank(),
        panel.grid.minor = element_blank(),
        plot.background = element_blank()) +
  geom_blank()

z.sep.plot.save <- gridExtra::arrangeGrob(blank.plot, z.sep.plot, nrow = 1, widths = c(0.55, 3.5))

FDP.q.sep.plot.save <- gridExtra::arrangeGrob(z.sep.plot.save, FDP.q.all.sep.plot, heights = c(1, 1.2))

FDP.sqrt.q.sep.plot.save <- gridExtra::arrangeGrob(z.sep.plot.save, FDP.sqrt.q.all.sep.plot, heights = c(1, 1.2))

ggsave("../output/paper/FDP.q.sep.pdf", FDP.q.sep.plot.save, height = 4.5, width = 10)

ggsave("../output/paper/FDP.sqrt.q.sep.pdf", FDP.sqrt.q.sep.plot.save, height = 4.5, width = 10)

##############################################

TDP.q.all.sep.plot <- ggplot(data = TDP.q.ggdata.0.9, aes(x = Method, y = TDP, fill = Method, color = Method)) +
  stat_summary(fun.data = boxplot.quantile, geom = "boxplot", aes(width = 0.5), position = position_dodge(), show.legend = FALSE) +
  coord_flip() +
  stat_summary(fun.y = mean, geom = "point", position = position_dodge(width = 0.9), show.legend = FALSE) +
  scale_x_discrete(limits = rev(levels(FDP.q.ggdata.0.9$Method))) +
  scale_color_manual(labels = method.name.FDR, values = method.col.FDR) +
  scale_fill_manual(labels = method.name.FDR, values = alpha(method.col.FDR, 0.35)) +
  facet_wrap(~Noise, nrow = 1) +
  labs(x = expression(pi[0]), y = "TDP") +
  expand_limits(y = 0) +
  theme(axis.title.y = element_blank(),
        axis.text.y = element_text(size = 15),
        axis.title.x = element_text(size = 15),
        axis.text.x = element_text(size = 10),
        strip.text = element_text(size = 15),
        legend.position = "bottom",
        legend.background = element_rect(color = "grey"),
        legend.text = element_text(size = 12)
        )

Warning: Ignoring unknown aesthetics: width

FDP.TDP.q.sep.plot.save <- gridExtra::arrangeGrob(z.sep.plot.save, FDP.q.all.sep.plot + theme(plot.title = element_text(size = 15, hjust = 0)), TDP.q.all.sep.plot, heights = c(1, 1.2, 1.1))

ggsave("../output/paper/FDP.TDP.q.sep.pdf", FDP.TDP.q.sep.plot.save, height = 6.5, width = 10)

FDP.sqrt.TDP.q.sep.plot.save <- gridExtra::arrangeGrob(z.sep.plot.save, FDP.sqrt.q.all.sep.plot + theme(plot.title = element_text(size = 15, hjust = 0)), TDP.q.all.sep.plot, heights = c(1, 1.2, 1.1))

FDP.sqrt.TDP.q.sep.plot.save <- gridExtra::arrangeGrob(
  z.sep.plot +
    labs(title = "Typical Examples of Realized Correlated Noise") +
    scale_color_manual(values = "blue") +
    theme(axis.title.x = element_blank(),
          legend.title = element_blank(),
         # legend.title = element_text(size = 15),
          plot.margin = grid::unit(c(5.5, 5.5, 5.5, 70), "points"),
          plot.title = element_text(size = 15, hjust = 0.5)
    ),
  gridExtra::arrangeGrob(
  FDP.sqrt.q.all.sep.plot +
    labs(title = "FDP") +
    theme(plot.title = element_text(size = 15, hjust = 0.5),
          axis.title.x = element_blank(),
          plot.margin = grid::unit(c(5.5, 5.5, 5.5, 5.5), "points")
    ),
  TDP.q.all.sep.plot +
    labs(title = "TDP") +
    theme(plot.margin = grid::unit(c(5.5, 5.5, 5.5, 5.5), "points"),
          axis.title.x = element_blank(),
          plot.title = element_text(size = 15, hjust = 0.5)
    ),
  heights = c(1, 1),
  top = grid::textGrob(bquote(paste("Nominal FDR = ", .(q), " (", g[1], " is Gaussian; ", pi[0] == 0.9, ")")), gp = grid::gpar(fontsize = 12), hjust = 1)
  ),
  heights = c(1, 2)
)

ggsave("../output/paper/FDP.sqrt.TDP.q.sep.pdf", FDP.sqrt.TDP.q.sep.plot.save, height = 6, width = 8)

Session information

sessionInfo()

R version 3.4.3 (2017-11-30)
Platform: x86_64-apple-darwin15.6.0 (64-bit)
Running under: macOS High Sierra 10.13.6

Matrix products: default
BLAS: /Library/Frameworks/R.framework/Versions/3.4/Resources/lib/libRblas.0.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/3.4/Resources/lib/libRlapack.dylib

locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
[1] ggplot2_2.2.1

loaded via a namespace (and not attached):
 [1] Rcpp_0.12.18      knitr_1.20        whisker_0.3-2    
 [4] magrittr_1.5      workflowr_1.1.1   munsell_0.4.3    
 [7] colorspace_1.3-2  rlang_0.1.6       stringr_1.3.0    
[10] plyr_1.8.4        tools_3.4.3       grid_3.4.3       
[13] gtable_0.2.0      R.oo_1.22.0       git2r_0.21.0     
[16] htmltools_0.3.6   yaml_2.1.18       lazyeval_0.2.1   
[19] rprojroot_1.3-2   digest_0.6.15     tibble_1.4.2     
[22] gridExtra_2.3     reshape2_1.4.3    R.utils_2.7.0    
[25] evaluate_0.10.1   rmarkdown_1.9     labeling_0.3     
[28] stringi_1.1.6     pillar_1.1.0      compiler_3.4.3   
[31] scales_0.5.0      backports_1.1.2   R.methodsS3_1.7.1

This reproducible R Markdown analysis was created with workflowr 1.1.1

The inflated vs deflated noise figure in cashr

Lei Sun

2018-10-05

Introduction

Session information

The inflated vs deflated noise figure in `cashr`