diff --git a/inst/analysis/compute_droplet_cellwise_logliks.R b/inst/analysis/compute_droplet_cellwise_logliks.R
new file mode 100644
index 0000000..52e8c62
--- /dev/null
+++ b/inst/analysis/compute_droplet_cellwise_logliks.R
@@ -0,0 +1,55 @@
+# sinteractive -p mstephens -c 4 --mem=16G --time=2:00:00
+# module load R/3.5.1
+library(Matrix)
+library(ggplot2)
+library(cowplot)
+source("../code/loglik.R")
+datadir <- "/project2/mstephens/eweine/fastglmpca_experiments"
+load(file.path(datadir,"droplet.RData"))
+counts <- t(counts)
+fit1 <- readRDS(file.path(datadir,
+                          paste("droplets_fastglmpca_fit_10_factors_5105",
+                                "iter_28_cores_dec_23.rds",sep = "_")))
+fit2 <- readRDS(file.path(datadir,
+                          paste("droplets_glmpca_fit_10_factors_10_hrs",
+                                "avagrad_optimizer_minibatch_stochastic",
+                                "dec_23.rds",sep = "_")))
+fit3 <- readRDS(file.path(datadir,
+                          paste("droplets_scGBM_fit_10_factors_no_beta",
+                                "infer_10_hrs.rds",sep = "_")))
+glmpca_pois_loglik <- function (Y, H)
+  Y*H - exp(H) - lfactorial(as.matrix(Y))
+H1 <- glmpca_pois_loglik(counts,logrates_fastglmpca(fit1))
+H2 <- glmpca_pois_loglik(counts,logrates_glmpca(fit2))
+H3 <- glmpca_pois_loglik(counts,logrates_scgbm(fit3))
+
+tissue_colors <- c("royalblue",   # basal
+                   "firebrick",   # ciliated
+                   "forestgreen", # club
+                   "gold",        # goblet
+                   "darkmagenta", # ionocyte
+                   "darkorange",  # neuroendocrine
+                   "skyblue")     # tuft
+
+# Compare the cell-wise logliks.
+pdat <- cbind(samples,
+              data.frame(fastglmpca = colSums(H1),
+                         glmpca     = colSums(H2),
+                         scgbm      = colSums(H3)))
+x <- with(pdat,c(scgbm,glmpca,fastglmpca))
+p1 <- ggplot(pdat,aes(x = glmpca,y = fastglmpca,color = tissue)) +
+  geom_point(show.legend = FALSE) +
+  geom_abline(intercept = 0,slope = 1,color = "black",linetype = "dotted") +
+  scale_color_manual(values = tissue_colors) +
+  xlim(min(x),max(x)) +
+  ylim(min(x),max(x)) +
+  theme_cowplot(font_size = 12)
+p2 <- ggplot(pdat,aes(x = scgbm,y = fastglmpca,color = tissue)) +
+  geom_point(show.legend = FALSE) +
+  geom_abline(intercept = 0,slope = 1,color = "black",linetype = "dotted") +
+  scale_color_manual(values = tissue_colors) +
+  xlim(min(x),max(x)) +
+  ylim(min(x),max(x)) +
+  theme_cowplot(font_size = 12)
+ggsave("droplet_loglik_cellwise1.eps",p1,height = 3,width = 3.25)
+ggsave("droplet_loglik_cellwise2.eps",p2,height = 3,width = 3.25)