From e45fe67069edc340a536826dc606433ffe9a8c24 Mon Sep 17 00:00:00 2001
From: Sean Maden <metamaden@users.noreply.github.com>
Date: Tue, 16 Jan 2024 06:32:13 -0800
Subject: [PATCH] saves Tran et al 2021 k nuclei summaries

---
 cohort1/.Rhistory                             | 100 ++-
 .../02_summaries/cohort2_nuclei_summaries.csv |  10 +-
 cohort2/scripts/02_summaries/03_nuclei.R      |  16 +-
 software/.Rhistory                            | 642 +++++++++---------
 4 files changed, 374 insertions(+), 394 deletions(-)

diff --git a/cohort1/.Rhistory b/cohort1/.Rhistory
index d667902..30486cf 100644
--- a/cohort1/.Rhistory
+++ b/cohort1/.Rhistory
@@ -63,6 +63,20 @@ p_size=15, s_x=1, s_y=.8, s_width=.5,
 filename="cellScaleFactors.png",
 h_fill="#FCFCFC", p_color = "#111111", h_color = "#FF674F")
 setwd("C:/Users/User/Documents/GitHub/deconvo_method-paper/cohort1")
+setwd("..")
+setwd("..")
+load("./env/05_bulk/02_crossvalidate_script.RData")
+# Filter results to within-reference condition only
+dfp <- df.k2[df.k2$experiment.type=="shared.reference",]
+dfp$preparation.type <- gsub(".*_", "", dfp$bulk.sample.condition)
+dfp <- na.omit(dfp)
+# new plot
+new.plot.scatter <-
+ggplot(dfp, aes(x = true.neuron, y = neuron, color = bulk.scale.type)) +
+theme_bw() + geom_point(alpha = 0.5) + geom_abline(slope = 1, intercept = 0) +
+facet_grid(experiment.type~assay.name.lutearg+s.set.label) +
+xlab("Known") + ylab("Predicted") + xlim(0, 1) + ylim(0, 1) +
+theme(axis.text.x = element_text(angle = 45, hjust = 1))
 knitr::opts_chunk$set(fig.width=10, fig.height=10, echo = F)
 libv <- c("ggplot2")
 sapply(libv, library, character.only = T)
@@ -104,79 +118,55 @@ knitr::kable(data.dict)
 new.plot.scatter <-
 ggplot(dfp, aes(x = true.neuron, y = neuron, color = bulk.scale.type)) +
 theme_bw() + geom_point(alpha = 0.5) + geom_abline(slope = 1, intercept = 0) +
-facet_wrap(experiment.type*assay.name.lutearg~s.set.label) +
+facet_grid(experiment.type~assay.name.lutearg+s.set.label) +
 xlab("Known") + ylab("Predicted") + xlim(0, 1) + ylim(0, 1) +
 theme(axis.text.x = element_text(angle = 45, hjust = 1))
 new.plot.scatter
-# new plot
-new.plot.scatter <-
-ggplot(dfp, aes(x = true.neuron, y = neuron, color = bulk.scale.type)) +
-theme_bw() + geom_point(alpha = 0.5) + geom_abline(slope = 1, intercept = 0) +
-facet_wrap(experiment.type+assay.name.lutearg~s.set.label) +
-xlab("Known") + ylab("Predicted") + xlim(0, 1) + ylim(0, 1) +
-theme(axis.text.x = element_text(angle = 45, hjust = 1))
+setwd("..")
+setwd("..")
+new.plot.path <- "./figures/05_bulk/figs3a_scatter.jpg"
+jpeg(new.plot.path, width = 7.5, height = 7, res = 400, units = "in")
 new.plot.scatter
-# new plot
-new.plot.scatter <-
-ggplot(dfp, aes(x = true.neuron, y = neuron, color = bulk.scale.type)) +
-theme_bw() + geom_point(alpha = 0.5) + geom_abline(slope = 1, intercept = 0) +
-facet_grid(experiment.type+assay.name.lutearg~s.set.label) +
-xlab("Known") + ylab("Predicted") + xlim(0, 1) + ylim(0, 1) +
-theme(axis.text.x = element_text(angle = 45, hjust = 1))
+dev.off()
+setwd("..")
+setwd("..")
+new.plot.path <- "./figures/05_bulk/figs3a_scatter.jpg"
+jpeg(new.plot.path, width = 6, height = 6, res = 400, units = "in")
 new.plot.scatter
-# new plot
-new.plot.scatter <-
-ggplot(dfp, aes(x = true.neuron, y = neuron, color = bulk.scale.type)) +
-theme_bw() + geom_point(alpha = 0.5) + geom_abline(slope = 1, intercept = 0) +
-facet_grid(experiment.type~assay.name.lutearg+s.set.label) +
-xlab("Known") + ylab("Predicted") + xlim(0, 1) + ylim(0, 1) +
-theme(axis.text.x = element_text(angle = 45, hjust = 1))
+dev.off()
+setwd("..")
+setwd("..")
+new.plot.path <- "./figures/05_bulk/figs3a_scatter.jpg"
+jpeg(new.plot.path, width = 7, height = 5.5, res = 400, units = "in")
 new.plot.scatter
+dev.off()
 setwd("..")
 setwd("..")
 new.plot.path <- "./figures/05_bulk/figs3a_scatter.jpg"
-jpeg(new.plot.path, width = 7.5, height = 7, res = 400, units = "in")
+jpeg(new.plot.path, width = 8, height = 5.5, res = 400, units = "in")
 new.plot.scatter
 dev.off()
 setwd("..")
 setwd("..")
-load("./env/05_bulk/02_crossvalidate_script.RData")
-knitr::opts_chunk$set(fig.width=10, fig.height=10, echo = F)
-libv <- c("ggplot2")
-sapply(libv, library, character.only = T)
+new.plot.path <- "./figures/05_bulk/figs3a_scatter.jpg"
+jpeg(new.plot.path, width = 8, height = 5, res = 400, units = "in")
+new.plot.scatter
+dev.off()
 setwd("..")
 setwd("..")
-load("./env/05_bulk/02_crossvalidate_script.RData")
-dfp <- df.k2
-# format plot data
-dfp <- dfp[dfp$crossvalidation=="validation",]
-dfp[dfp$s.set.label=="s.null",]$s.set.label <- "unscaled"
-dfp[dfp$s.set.label=="s.manual",]$s.set.label <- "scaled"
-dfp$experiment.type <- paste0("z_type : ", dfp$experiment.type)
-dfp$bulk.sample.id <- gsub("c1", "c", dfp$bulk.sample.id)
-dfp$bulk.sample.id <- gsub("k1", "k", dfp$bulk.sample.id)
-dfp$bulk.sample.id <- gsub("o1", "o", dfp$bulk.sample.id)
-# experiment conditions
-dfp$bulk.sample.condition <- cd[dfp$bulk.sample.id,]$expt_condition
-table(dfp$bulk.sample.condition)
-dfp <- na.omit(dfp)
-new.plot.scatter <- ggplot(dfp, aes(x = true.neuron, y = neuron)) +
-theme_bw() + geom_point(alpha = 0.5) +
-geom_abline(slope = 1, intercept = 0) +
-facet_wrap(~s.set.label*experiment.type) + xlab("Known") +
-ylab("Predicted") + xlim(0, 1) + ylim(0, 1) +
-theme(axis.text.x = element_text(angle = 45, hjust = 1))
+new.plot.path <- "./figures/05_bulk/figs3a_scatter.jpg"
+jpeg(new.plot.path, width = 8, height = 4.5, res = 400, units = "in")
 new.plot.scatter
-new.plot.scatter <- ggplot(dfp, aes(x = true.neuron, y = neuron)) +
-theme_bw() + geom_point(alpha = 0.5) +
-geom_abline(slope = 1, intercept = 0) +
-facet_grid(s.set.label~experiment.type) + xlab("Known") +
-ylab("Predicted") + xlim(0, 1) + ylim(0, 1) +
-theme(axis.text.x = element_text(angle = 45, hjust = 1))
+dev.off()
+setwd("..")
+setwd("..")
+new.plot.path <- "./figures/05_bulk/figs3a_scatter.jpg"
+jpeg(new.plot.path, width = 8, height = 4, res = 400, units = "in")
 new.plot.scatter
+dev.off()
 setwd("..")
 setwd("..")
-new.plot.path <- "./figures/05_bulk/figs2b_validate.jpg"
-jpeg(new.plot.path, width = 4.5, height = 5, units = "in", res = 400)
+new.plot.path <- "./figures/05_bulk/figs3a_scatter.jpg"
+jpeg(new.plot.path, width = 8, height = 4.2, res = 400, units = "in")
 new.plot.scatter
 dev.off()
diff --git a/cohort2/outputs/02_summaries/cohort2_nuclei_summaries.csv b/cohort2/outputs/02_summaries/cohort2_nuclei_summaries.csv
index 27ec3a6..9a43ab4 100644
--- a/cohort2/outputs/02_summaries/cohort2_nuclei_summaries.csv
+++ b/cohort2/outputs/02_summaries/cohort2_nuclei_summaries.csv
@@ -1,6 +1,6 @@
 k,cellType,median_nuclei_per_sample,mean_nuclei_per_sample,sd_nuclei_per_sample,median_proportion_nuclei_per_sample,mean_proportion_nuclei_per_sample,sd_proportion_nuclei_per_sample,median_marker_library_size,mean_marker_library_size,sd_marker_library_size
-k2,neuron,2176.5,2078.75,922.920180238199,0.665874128565984,0.627831690999206,0.164627022800621,186.275005011024,129,192.069766282185
-k2,glial,1067.5,1128.66666666667,419.576048656332,0.334125871434016,0.372168309000794,0.164627022800621,107.204075605434,77,101.892617186566
-k3,Inhib,558,554.090909090909,451.741176902317,0.125752364574377,0.168093277786039,0.146388486906233,308.952255947498,261,217.308741475141
-k3,Excit,1819,1659.72727272727,791.794176653136,0.494908350305499,0.493756240943012,0.158568135189935,232.023114421866,195,193.732105594974
-k3,glial,977,1072.63636363636,390.139019511577,0.305217119650109,0.338150481270949,0.120569714000566,141.515043647767,104,128.84792068759
+k2,neuron,849,1322.667,920.012,0.452,0.377,0.177,324.413,296,164.115
+k2,glial,2887,2399,1384.1,0.548,0.623,0.177,269.877,263,151.807
+k3,Inhib,332,526.667,360.808,0.179,0.149,0.067,336.114,313,168.653
+k3,Excit,517,796,559.376,0.273,0.227,0.11,316.671,286,160.61
+k3,glial,2887,2399,1384.1,0.548,0.623,0.177,269.877,263,151.807
diff --git a/cohort2/scripts/02_summaries/03_nuclei.R b/cohort2/scripts/02_summaries/03_nuclei.R
index 64f9f37..1a936f1 100644
--- a/cohort2/scripts/02_summaries/03_nuclei.R
+++ b/cohort2/scripts/02_summaries/03_nuclei.R
@@ -14,9 +14,7 @@
 #------
 # load marker data
 load("env/01_pseudobulk/01_k2_mrb_script.RData")
-
-sceK2 <- list.sce.markers[["k2"]]
-sceK3 <- list.sce.markers[["k3"]]
+load("env/01_pseudobulk/01_k3_mrb_script.RData")
 
 dfSummary <- function(sce, 
                       sampleIdVariable = "donor",
@@ -78,18 +76,10 @@ dfSummary <- function(sce,
   return(dfSummaries)
 }
 
-summaryK2 <- dfSummary(sceK2, "Sample", "k2", c("neuron", "glial"))
-summaryK3 <- dfSummary(sceK3, "Sample", "k3", c("Inhib", "Excit", "glial"))
+summaryK2 <- dfSummary(sce.k2, "donor", "k2", c("neuron", "glial"))
+summaryK3 <- dfSummary(sce.k3, "donor", "k3", c("Inhib", "Excit", "glial"))
 summaryTable <- rbind(summaryK2, summaryK3)
 
-sce.mrb$Sample <- sce.mrb$donor
-summaryK2 <- dfSummary(sce.mrb, "Sample", "k2", c("neuron", "glial"))
-summaryK3 <- dfSummary(sce.mrb, "Sample", "k3", c("Inhib", "Excit", "glial"))
-
-summaryK3 <- dfSummary(sceK3, "Sample", "k3", c("Inhib", "Excit", "glial"))
-summaryTable <- rbind(summaryK2, summaryK3)
-
-
 #-----
 # save
 #-----
diff --git a/software/.Rhistory b/software/.Rhistory
index 149cd55..363856f 100644
--- a/software/.Rhistory
+++ b/software/.Rhistory
@@ -1,92 +1,288 @@
-plotK2.c2box.glial,
-layout_matrix = layoutMatrix)
-jpeg("./figures/01_multipanel/pseudobulk-k2-2cohort_multi.jpg", width = 10, height = 4, units = "in", res = 400)
-jpeg("./figures/01_multipanel/pseudobulk-k2-2cohort_multi.jpg", width = 10, height = 4, units = "in", res = 400)
-grid.arrange(plotK2.c1Scatter.neuron,
-plotK2.c1box.neuron,
-plotK2.c2Scatter.neuron,
-plotK2.c2box.neuron,
-plotK2.c1Scatter.glial,
-plotK2.c1box.glial,
-plotK2.c2Scatter.glial,
-plotK2.c2box.glial,
-layout_matrix = layoutMatrix)
+geom_text(data = dfLabelNeuron, aes(x = true, y = value),
+label = sample.id, nudge_x = 0.1, nudge_y = 0.1) +
+geom_text(data = dfLabelGlial, aes(x = true, y = value),
+label = sample.id, nudge_x = 0.1, nudge_y = 0.1)
+}
+jitterbox <- ggplot(dfp[dfp$cell.type == "neuron",], aes(x = scale, y = error)) +
+geom_jitter(alpha = 0.5, width = 0.5, height = 0) + theme_bw() +
+geom_boxplot(alpha = 0, color = "cyan") +
+xlab("Scale") + ylab("Error") + ylim(0, 0.5) +
+theme(axis.text.x = element_text(angle = 45, hjust = 1),
+axis.title.x = element_blank())
+return(list(
+newPlot, jitterbox
+))
+}
+plotsListNNLS <- plotsList(dfp.tall[dfp.tall$algorithm=="nnls",])
+plotsListMUSIC <- plotsList(dfp.tall[dfp.tall$algorithm=="music",])
+plotsListBISQUE <- plotsList(dfp.tall[dfp.tall$algorithm=="bisque",], outlier = FALSE)
+setwd("..")
+setwd("..")
+jpeg("./figures/07_adjustment/fig3_bulk-results_nnls.jpg",
+width = 6, height = 4, units = "in", res = 400)
+grid.arrange(plotsListNNLS[[1]], plotsListNNLS[[2]],
+layout_matrix = matrix(c(1,1,2), byrow=TRUE, nrow = 1))
 dev.off()
-head(dfp.tall.c1.k2)
-dfp.c1 <- rbind(data.frame(true = dfp.tall.c1.k2$glial.true,
-pred = dfp.tall.c1.k2$glial.pred,
-cell.type = rep("glial", nrow(dfp.tall.c1.k2))),
-data.frame(true = dfp.tall.c1.k2$neuron.true,
-pred = dfp.tall.c1.k2$neuron.pred,
-cell.type = rep("neuron", nrow(dfp.tall.c1.k2)))) |>
-as.data.frame()
-ggplot(dfp.c1, aes(x = glial.true, y = glial.pred)) +
-geom_point() + theme_bw() + theme(axis.text.x = element_text(angle = 45,hjust=1)) +
-facet_wrap(~type) + geom_abline(slope = 1) +
-xlab("Known") + ylab("Predicted") + ggtitle("") + xlim(0,1) + ylim(0,1) +
-facet_wrap(cell.type)
-ggplot(dfp.c1, aes(x = true, y = pred)) +
-geom_point() + theme_bw() + theme(axis.text.x = element_text(angle = 45,hjust=1)) +
-facet_wrap(~type) + geom_abline(slope = 1) +
-xlab("Known") + ylab("Predicted") + ggtitle("") + xlim(0,1) + ylim(0,1) +
-facet_wrap(cell.type)
-head(dfp.c1)
-ggplot(dfp.c1, aes(x = true, y = pred)) +
-geom_point() + theme_bw() +
-theme(axis.text.x = element_text(angle = 45, hjust=1)) +
-facet_wrap(~type) + geom_abline(slope = 1) +
-xlab("Known") + ylab("Predicted") + ggtitle("") + xlim(0,1) + ylim(0,1) +
-facet_wrap(cell.type)
-ggplot(dfp.c1, aes(x = true, y = pred)) +
-geom_point() + theme_bw() +
-theme(axis.text.x = element_text(angle = 45, hjust=1)) +
-facet_wrap(~type) + geom_abline(slope = 1) +
-xlab("Known") + ylab("Predicted") + ggtitle("") + xlim(0,1) + ylim(0,1) +
-facet_wrap(~cell.type)
-ggplot(dfp.c1, aes(x = true, y = pred)) +
-geom_point() + theme_bw() +
-theme(axis.text.x = element_text(angle = 45, hjust=1)) +
-facet_wrap(~type) + geom_abline(slope = 1) +
-xlab("Known") + ylab("Predicted") + ggtitle("") + xlim(0,1) + ylim(0,1) +
-facet_wrap(~cell.type)
-head(dfp.c1)
-head(dfp.tall.c1.k2)
-ggplot(dfp.c1, aes(x = true, y = pred)) +
-geom_point() + theme_bw() +
-theme(axis.text.x = element_text(angle = 45, hjust=1)) +
-geom_abline(slope = 1) +
-xlab("Known") + ylab("Predicted") + ggtitle("") + xlim(0,1) + ylim(0,1) +
-facet_wrap(~cell.type*type)
-ggplot(dfp.c1, aes(x = true, y = pred)) +
-geom_point() + theme_bw() + geom_abline(slope = 1) +
-theme(axis.text.x = element_text(angle = 45, hjust=1)) +
-xlab("Known") + ylab("Predicted") + ggtitle("") + xlim(0,1) + ylim(0,1) +
-facet_wrap(~cell.type*type)
-dfp.c1 <- rbind(data.frame(true = dfp.tall.c1.k2$glial.true,
-pred = dfp.tall.c1.k2$glial.pred,
-cell.type = rep("glial", nrow(dfp.tall.c1.k2)),
-type = dfp.tall.c1.k2$type),
-data.frame(true = dfp.tall.c1.k2$neuron.true,
-pred = dfp.tall.c1.k2$neuron.pred,
-cell.type = rep("neuron", nrow(dfp.tall.c1.k2)),
-type = dfp.tall.c1.k2$type)) |>
-as.data.frame()
-ggplot(dfp.c1, aes(x = true, y = pred)) +
-geom_point() + theme_bw() + geom_abline(slope = 1) +
-theme(axis.text.x = element_text(angle = 45, hjust=1)) +
-xlab("Known") + ylab("Predicted") + ggtitle("") + xlim(0,1) + ylim(0,1) +
-facet_wrap(~cell.type*type)
+setwd("..")
+setwd("..")
+jpeg("./figures/07_adjustment/fig3_bulk-results_music-bisque.jpg",
+width = 5.5, height = 8, units = "in", res = 400)
+grid.arrange(plotsListMUSIC[[1]] + ggtitle("MuSiC"), plotsListMUSIC[[2]] + ggtitle(""),
+plotsListBISQUE[[1]] + ggtitle("Bisque"), plotsListBISQUE[[2]] + ggtitle(""),
+layout_matrix = matrix(c(1,1,2,3,3,4), byrow = TRUE, nrow = 2))
+dev.off()
+# append glial
+dfp.tall2 <- dfp.tall
+dfp.tall2$cell.type <- "glial"
+dfp.tall2$value <- 1-dfp.tall2$value
+dfp.tall2$true <- 1-dfp.tall2$true
+dfp.tall <- rbind(dfp.tall, dfp.tall2) |> as.data.frame()
+plotsList <- function(dfp, outlier = TRUE){
+# plotsList
+#
+# scatterplot and jitterbox plot of results data, with outlier label.
+#
+# dfp.tall results data.frame
+#
+#
+#
+#
+dfp$scale <- ifelse(dfp$scale, "withscale", "noscale")
+newPlot <- ggplot(dfp, aes(x = true, y = value)) +
+geom_point(size = 4, alpha = 0.5) +
+geom_abline(slope = 1, intercept = 0) +
+facet_grid(cell.type~scale, nrow = 2) + xlab("Known") +
+ylab("Predicted") + theme_bw() + xlim(0, 1) + ylim(0, 1) +
+theme(axis.text.x = element_text(angle = 45, hjust = 1))
+if(outlier){
+dfLabelGlial <- dfp[dfp$value > 0.75 & dfp$cell.type == "glial",]
+dfLabelNeuron <- dfp[dfp$value < 0.25 &
+dfp$true < 0.75 & dfp$cell.type == "neuron",]
+newPlot <- newPlot +
+geom_text(data = dfLabelNeuron, aes(x = true, y = value),
+label = sample.id, nudge_x = 0.1, nudge_y = 0.1) +
+geom_text(data = dfLabelGlial, aes(x = true, y = value),
+label = sample.id, nudge_x = 0.1, nudge_y = 0.1)
+}
+jitterbox <- ggplot(dfp[dfp$cell.type == "neuron",], aes(x = scale, y = error)) +
+geom_jitter(alpha = 0.5, width = 0.5, height = 0) + theme_bw() +
+geom_boxplot(alpha = 0, color = "cyan") +
+xlab("Scale") + ylab("Error") + ylim(0, 0.5) +
+theme(axis.text.x = element_text(angle = 45, hjust = 1),
+axis.title.x = element_blank())
+return(list(
+newPlot, jitterbox
+))
+}
+plotsListNNLS <- plotsList(dfp.tall[dfp.tall$algorithm=="nnls",])
+setwd("..")
+setwd("..")
+jpeg("./figures/07_adjustment/fig3_bulk-results_nnls.jpg",
+width = 6, height = 4, units = "in", res = 400)
+grid.arrange(plotsListNNLS[[1]], plotsListNNLS[[2]],
+layout_matrix = matrix(c(1,1,2), byrow=TRUE, nrow = 1))
+dev.off()
+setwd("..")
+setwd("..")
+jpeg("./figures/07_adjustment/fig3_bulk-results_music-bisque.jpg",
+width = 5.5, height = 8, units = "in", res = 400)
+grid.arrange(plotsListMUSIC[[1]] + ggtitle("MuSiC"), plotsListMUSIC[[2]] + ggtitle(""),
+plotsListBISQUE[[1]] + ggtitle("Bisque"), plotsListBISQUE[[2]] + ggtitle(""),
+layout_matrix = matrix(c(1,1,2,3,3,4), byrow = TRUE, nrow = 2))
+dev.off()
+plotsListNNLS[[1]]
+plotsListNNLS <- plotsList(dfp.tall[dfp.tall$algorithm=="nnls",])
+plotsList <- function(dfp, outlier = TRUE){
+# plotsList
+#
+# scatterplot and jitterbox plot of results data, with outlier label.
+#
+# dfp.tall results data.frame
+#
+#
+#
+#
+dfp$scale <- ifelse(dfp$scale, "withscale", "noscale")
+newPlot <- ggplot(dfp, aes(x = true, y = value)) +
+geom_point(size = 4, alpha = 0.5) +
+geom_abline(slope = 1, intercept = 0) +
+facet_grid(cell.type~scale) + xlab("Known") +
+ylab("Predicted") + theme_bw() + xlim(0, 1) + ylim(0, 1) +
+theme(axis.text.x = element_text(angle = 45, hjust = 1))
+if(outlier){
+dfLabelGlial <- dfp[dfp$value > 0.75 & dfp$cell.type == "glial",]
+dfLabelNeuron <- dfp[dfp$value < 0.25 &
+dfp$true < 0.75 & dfp$cell.type == "neuron",]
+newPlot <- newPlot +
+geom_text(data = dfLabelNeuron, aes(x = true, y = value),
+label = sample.id, nudge_x = 0.1, nudge_y = 0.1) +
+geom_text(data = dfLabelGlial, aes(x = true, y = value),
+label = sample.id, nudge_x = 0.1, nudge_y = 0.1)
+}
+jitterbox <- ggplot(dfp[dfp$cell.type == "neuron",], aes(x = scale, y = error)) +
+geom_jitter(alpha = 0.5, width = 0.5, height = 0) + theme_bw() +
+geom_boxplot(alpha = 0, color = "cyan") +
+xlab("Scale") + ylab("Error") + ylim(0, 0.5) +
+theme(axis.text.x = element_text(angle = 45, hjust = 1),
+axis.title.x = element_blank())
+return(list(
+newPlot, jitterbox
+))
+}
+plotsListNNLS <- plotsList(dfp.tall[dfp.tall$algorithm=="nnls",])
+plotsListMUSIC <- plotsList(dfp.tall[dfp.tall$algorithm=="music",])
+plotsListBISQUE <- plotsList(dfp.tall[dfp.tall$algorithm=="bisque",], outlier = FALSE)
+grid.arrange(plotsListNNLS[[1]], plotsListNNLS[[2]],
+layout_matrix = matrix(c(1,1,2), byrow=TRUE, nrow = 1))
+gc()
+gc()
+knitr::opts_chunk$set(echo = TRUE)
+libv <- c("dplyr", "ggplot2", "GGally", "gridExtra")
+sapply(libv, library, character.only = TRUE)
+setwd("..")
+setwd("..")
+load("./env/07_adjustment/03_run_adjustment_realbulk_all_script.RData")
+list.df.true <- metadata(sce)[["list.df.true.k2"]]
+plotsList <- function(dfp){
+# plotsList
+#
+# scatterplot and jitterbox plot of results data, with outlier label.
+#
+# dfp.tall results data.frame
+#
+#
+dfp$scale <- ifelse(dfp$scale, "withscale", "noscale")
+dfLabel <- dfp[dfp$true < 0.75 & dfp$value < 0.25,]
+new.plot.tall <- ggplot(dfp, aes(x = true, y = value)) +
+geom_point(size = 4, alpha = 0.5) + geom_abline(slope = 1, intercept = 0) + facet_wrap(~scale) +
+xlab("Known") + ylab("Predicted") + xlim(0.1,0.9) + ylim(0.1,0.9) + theme_bw() +
+theme(axis.text.x = element_text(angle = 45, hjust = 1)) +
+geom_text(data = dfLabel, aes(x = true, y = value),
+label = sample.id, nudge_x = 0.1, nudge_y = 0.1)
+new.plot.tall
+new.plot.tall.jitterbox <- ggplot(dfp, aes(x = scale, y = error)) +
+geom_jitter(alpha = 0.5, width = 0.5, height = 0) + theme_bw() +
+geom_boxplot(alpha = 0, color = "cyan") +
+xlab("Scale") + ylab("Error (neuron)") + ylim(0, 0.5) +
+theme(axis.text.x = element_text(angle = 45, hjust = 1),
+axis.title.x = element_blank())
+new.plot.tall.jitterbox
+return(list(
+new.plot.tall, new.plot.tall.jitterbox
+))
+}
+list.df.true <- metadata(sce)[["list.df.true.k2"]]
+for(sample.id in unique(dfp.tall$sample.id)){
+message(sample.id)
+message(identical(dfp.tall[dfp.tall$sample.id==sample.id,]$true[1],
+as.numeric(list.df.true[[sample.id]]["neuron"])))
+}
+for(sample.id in unique(dfp.tall$sample.id)){
+filter.dfp.tall <- dfp.tall$sample.id==sample.id
+filter.dfp.wide <- rownames(dfp.wide)==sample.id
+true.neuron.value <- as.numeric(df.true.list[[sample.id]]["neuron"])
+dfp.tall[filter.dfp.tall,]$true <- true.neuron.value
+dfp.wide[filter.dfp.wide,]$neuron.true <- true.neuron.value
+}
+dfp.tall$error <- abs(dfp.tall$true-dfp.tall$value)
+new.plot.tall.jitterbox <- ggplot(dfp.tall,
+aes(x = scale, y = error)) +
+geom_jitter(alpha = 0.5, width = 0.5, height = 0) + geom_boxplot(alpha = 0, color = "cyan") +
+facet_wrap(~algorithm) + xlab("Scale") +
+ylab("Error (neuron)") + ylim(0, 0.5) +
+theme(axis.text.x = element_text(angle = 45, hjust = 1))
+new.plot.tall.jitterbox
+# append glial
+dfp.tall2 <- dfp.tall
+dfp.tall2$cell.type <- "glial"
+dfp.tall2$value <- 1-dfp.tall2$value
+dfp.tall2$true <- 1-dfp.tall2$true
+dfp.tall <- rbind(dfp.tall, dfp.tall2) |> as.data.frame()
+plotsList <- function(dfp, outlier = TRUE){
+# plotsList
+#
+# scatterplot and jitterbox plot of results data, with outlier label.
+#
+# dfp.tall results data.frame
+#
+#
+#
+#
+dfp$scale <- ifelse(dfp$scale, "withscale", "noscale")
+newPlot <- ggplot(dfp, aes(x = true, y = value)) +
+geom_point(size = 4, alpha = 0.5) +
+geom_abline(slope = 1, intercept = 0) +
+facet_grid(cell.type~scale) + xlab("Known") +
+ylab("Predicted") + theme_bw() + xlim(0, 1) + ylim(0, 1) +
+theme(axis.text.x = element_text(angle = 45, hjust = 1))
+if(outlier){
+dfLabelGlial <- dfp[dfp$value > 0.75 & dfp$cell.type == "glial",]
+dfLabelNeuron <- dfp[dfp$value < 0.25 &
+dfp$true < 0.75 & dfp$cell.type == "neuron",]
+newPlot <- newPlot +
+geom_text(data = dfLabelNeuron, aes(x = true, y = value),
+label = sample.id, nudge_x = 0.1, nudge_y = 0.1) +
+geom_text(data = dfLabelGlial, aes(x = true, y = value),
+label = sample.id, nudge_x = 0.1, nudge_y = 0.1)
+}
+jitterbox <- ggplot(dfp[dfp$cell.type == "neuron",], aes(x = scale, y = error)) +
+geom_jitter(alpha = 0.5, width = 0.5, height = 0) + theme_bw() +
+geom_boxplot(alpha = 0, color = "cyan") +
+xlab("Scale") + ylab("Error") + ylim(0, 0.5) +
+theme(axis.text.x = element_text(angle = 45, hjust = 1),
+axis.title.x = element_blank())
+return(list(
+newPlot, jitterbox
+))
+}
+plotsListNNLS <- plotsList(dfp.tall[dfp.tall$algorithm=="nnls",])
+plotsListMUSIC <- plotsList(dfp.tall[dfp.tall$algorithm=="music",])
+plotsListBISQUE <- plotsList(dfp.tall[dfp.tall$algorithm=="bisque",], outlier = FALSE)
+setwd("..")
+setwd("..")
+jpeg("./figures/07_adjustment/fig3_bulk-results_nnls.jpg",
+width = 6, height = 4, units = "in", res = 400)
+grid.arrange(plotsListNNLS[[1]], plotsListNNLS[[2]],
+layout_matrix = matrix(c(1,1,2), byrow=TRUE, nrow = 1))
+dev.off()
+setwd("..")
+setwd("..")
+jpeg("./figures/07_adjustment/fig3_bulk-results_music-bisque.jpg",
+width = 5.5, height = 8, units = "in", res = 400)
+grid.arrange(plotsListMUSIC[[1]] + ggtitle("MuSiC"), plotsListMUSIC[[2]] + ggtitle(""),
+plotsListBISQUE[[1]] + ggtitle("Bisque"), plotsListBISQUE[[2]] + ggtitle(""),
+layout_matrix = matrix(c(1,1,2,3,3,4), byrow = TRUE, nrow = 2))
+dev.off()
+setwd("C:/Users/User/Documents/GitHub/deconvo_method-paper/software")
+libv <- c("here", "nlme", "lute", "ggplot2", "gridExtra",
+"dplyr", "ggforce", "MultiAssayExperiment", "SingleCellExperiment")
+sapply(libv, library, character.only = TRUE)
+knitr::opts_chunk$set(echo = TRUE)
+setwd("..")
+setwd("..")
+list.files()
+load("env/01_multipanel/01_pseudobulk_script.RData")
+# cohort 1
+# scatter with facet
 dfp.c1 <- rbind(data.frame(true = dfp.tall.c1.k2$glial.true,
 pred = dfp.tall.c1.k2$glial.pred,
 cell.type = rep("glial", nrow(dfp.tall.c1.k2)),
 type = dfp.tall.c1.k2$type,
-error = dpf.tall.c1.k2$glial.abs.error),
+error = dfp.tall.c1.k2$glial.abs.error),
 data.frame(true = dfp.tall.c1.k2$neuron.true,
 pred = dfp.tall.c1.k2$neuron.pred,
 cell.type = rep("neuron", nrow(dfp.tall.c1.k2)),
 type = dfp.tall.c1.k2$type,
 error = dfp.tall.c1.k2$neuron.abs.error)) |>
 as.data.frame()
+plotK2.scatter.c1 <- ggplot(dfp.c1, aes(x = true, y = pred)) +
+geom_point() + theme_bw() + geom_abline(slope = 1) +
+theme(axis.text.x = element_text(angle = 45, hjust=1)) +
+xlab("Known") + ylab("Predicted") + ggtitle("Huuki-Meyers et. al. 2023") +
+xlim(0,1) + ylim(0,1) +
+facet_grid(type+cell.type)
+# cohort 1
+# scatter with facet
 dfp.c1 <- rbind(data.frame(true = dfp.tall.c1.k2$glial.true,
 pred = dfp.tall.c1.k2$glial.pred,
 cell.type = rep("glial", nrow(dfp.tall.c1.k2)),
@@ -98,82 +294,18 @@ cell.type = rep("neuron", nrow(dfp.tall.c1.k2)),
 type = dfp.tall.c1.k2$type,
 error = dfp.tall.c1.k2$neuron.abs.error)) |>
 as.data.frame()
-ggplot(dfp.c1, aes(x = type, y = neuron.abs.error)) +
-geom_boxplot(color="cyan") + geom_jitter(alpha = 0.5) + theme_bw() + theme(axis.text.x = element_text(angle = 45,hjust=1), axis.title.x = element_blank()) +
-ylab("Error") + ggtitle("\n") + ylim(0, 0.3)
-ggplot(dfp.c1, aes(x = type, y = neuron.abs.error)) +
-geom_boxplot(color="cyan") + geom_jitter(alpha = 0.5) + theme_bw() +
-theme(axis.text.x = element_text(angle = 45,hjust=1), axis.title.x = element_blank()) +
-ylab("Error") + ggtitle("\n") + ylim(0, 0.3)
-ggplot(dfp.c1, aes(x = type, y = error)) +
-geom_boxplot(color="cyan") + geom_jitter(alpha = 0.5) + theme_bw() +
-theme(axis.text.x = element_text(angle = 45,hjust=1), axis.title.x = element_blank()) +
-ylab("Error") + ggtitle("\n") + ylim(0, 0.3)
-ggplot(dfp.c1, aes(x = type, y = error)) +
-geom_boxplot(color="cyan") + geom_jitter(alpha = 0.5) + theme_bw() +
-theme(axis.text.x = element_text(angle = 45,hjust=1), axis.title.x = element_blank()) +
-ylab("Error") + ggtitle("\n") + ylim(0, 0.3) + facet_wrap(~cell.type)
-ggplot(dfp.c1, aes(x = type, y = error)) +
-geom_boxplot(color="cyan") + geom_jitter(alpha = 0.5) + theme_bw() +
-theme(axis.text.x = element_text(angle = 45,hjust=1), axis.title.x = element_blank()) +
-ylab("Error") + ggtitle("\n") + ylim(0, 0.3) + facet_wrap(~cell.type, nrow = 2)
-ggplot(dfp.c1, aes(x = true, y = pred)) +
-geom_point() + theme_bw() + geom_abline(slope = 1) +
-theme(axis.text.x = element_text(angle = 45, hjust=1)) +
-xlab("Known") + ylab("Predicted") + ggtitle("") + xlim(0,1) + ylim(0,1) +
-facet_wrap(~cell.type*type)
-dfp.c2 <- rbind(data.frame(true = dfp.tall.c2.k2$glial.true,
-pred = dfp.tall.c2.k2$glial.pred,
-cell.type = rep("glial", nrow(dfp.tall.c2.k2)),
-type = dfp.tall.c2.k2$type,
-error = dfp.tall.c2.k2$glial.abs.error),
-data.frame(true = dfp.tall.c2.k2$neuron.true,
-pred = dfp.tall.c2.k2$neuron.pred,
-cell.type = rep("neuron", nrow(dfp.tall.c2.k2)),
-type = dfp.tall.c2.k2$type,
-error = dfp.tall.c2.k2$neuron.abs.error)) |>
-as.data.frame()
-dfp.c2 <- ggplot(dfp.c2, aes(x = true, y = pred)) +
-geom_point() + theme_bw() + geom_abline(slope = 1) +
-theme(axis.text.x = element_text(angle = 45, hjust=1)) +
-xlab("Known") + ylab("Predicted") + ggtitle("Tran et. al. 2021") +
-xlim(0,1) + ylim(0,1) +
-facet_wrap(~cell.type*type)
-plotK2.box.c2 <- ggplot(dfp.c2, aes(x = type, y = error)) +
-geom_boxplot(color="cyan") + geom_jitter(alpha = 0.5) + theme_bw() +
-theme(axis.text.x = element_text(angle = 45,hjust=1), axis.title.x = element_blank()) +
-ylab("Error") + ggtitle("\n") + ylim(0, 0.3) + facet_wrap(~cell.type, nrow = 2)
-dfp.c2 <- rbind(data.frame(true = dfp.tall.c2.k2$glial.true,
-pred = dfp.tall.c2.k2$glial.pred,
-cell.type = rep("glial", nrow(dfp.tall.c2.k2)),
-type = dfp.tall.c2.k2$type,
-error = dfp.tall.c2.k2$glial.abs.error),
-data.frame(true = dfp.tall.c2.k2$neuron.true,
-pred = dfp.tall.c2.k2$neuron.pred,
-cell.type = rep("neuron", nrow(dfp.tall.c2.k2)),
-type = dfp.tall.c2.k2$type,
-error = dfp.tall.c2.k2$neuron.abs.error)) |>
-as.data.frame()
-dfp.c2
-dfp.c2 <- ggplot(dfp.c2, aes(x = true, y = pred)) +
+plotK2.scatter.c1 <- ggplot(dfp.c1, aes(x = true, y = pred)) +
 geom_point() + theme_bw() + geom_abline(slope = 1) +
 theme(axis.text.x = element_text(angle = 45, hjust=1)) +
-xlab("Known") + ylab("Predicted") + ggtitle("Tran et. al. 2021") +
+xlab("Known") + ylab("Predicted") + ggtitle("Huuki-Meyers et. al. 2023") +
 xlim(0,1) + ylim(0,1) +
-facet_wrap(~cell.type*type)
-dfp.c2
-plotK2.box.c2 <- ggplot(dfp.c2, aes(x = type, y = error)) +
+facet_grid(type~cell.type)
+plotK2.box.c1 <- ggplot(dfp.c1, aes(x = type, y = error)) +
 geom_boxplot(color="cyan") + geom_jitter(alpha = 0.5) + theme_bw() +
 theme(axis.text.x = element_text(angle = 45,hjust=1), axis.title.x = element_blank()) +
 ylab("Error") + ggtitle("\n") + ylim(0, 0.3) + facet_wrap(~cell.type, nrow = 2)
-head(dfp.c2)
-class(dfp.c2)
-plotK2.scatter.c2 <- ggplot(dfp.c2, aes(x = true, y = pred)) +
-geom_point() + theme_bw() + geom_abline(slope = 1) +
-theme(axis.text.x = element_text(angle = 45, hjust=1)) +
-xlab("Known") + ylab("Predicted") + ggtitle("Tran et. al. 2021") +
-xlim(0,1) + ylim(0,1) +
-facet_wrap(~cell.type*type)
+# cohort 2
+# scatter with facet
 dfp.c2 <- rbind(data.frame(true = dfp.tall.c2.k2$glial.true,
 pred = dfp.tall.c2.k2$glial.pred,
 cell.type = rep("glial", nrow(dfp.tall.c2.k2)),
@@ -190,51 +322,11 @@ geom_point() + theme_bw() + geom_abline(slope = 1) +
 theme(axis.text.x = element_text(angle = 45, hjust=1)) +
 xlab("Known") + ylab("Predicted") + ggtitle("Tran et. al. 2021") +
 xlim(0,1) + ylim(0,1) +
-facet_wrap(~cell.type*type)
+facet_grid(type~cell.type)
 plotK2.box.c2 <- ggplot(dfp.c2, aes(x = type, y = error)) +
 geom_boxplot(color="cyan") + geom_jitter(alpha = 0.5) + theme_bw() +
 theme(axis.text.x = element_text(angle = 45,hjust=1), axis.title.x = element_blank()) +
 ylab("Error") + ggtitle("\n") + ylim(0, 0.3) + facet_wrap(~cell.type, nrow = 2)
-matrix(c(rep(seq(4), each = 2)), nrow = 2, byrow=T)
-matrix(rep(c(1,1,2,3,3,4), 2), nrow=2)
-matrix(rep(c(1,1,2,3,3,4), 2), byrow=T, nrow=2)
-layoutMatrix <- matrix(rep(c(1,1,2,3,3,4), 2), byrow=T, nrow=2)
-grid.arrange(plotK2.scatter.c1,
-plotK2.box.c1,
-plotK2.scatter.c2,
-plotK2.box.c2)
-grid.arrange(plotK2.scatter.c1,
-plotK2.box.c1,
-plotK2.scatter.c2,
-plotK2.box.c2,
-layout_matrix = layoutMatrix)
-dfp.c1 <- rbind(data.frame(true = dfp.tall.c1.k2$glial.true,
-pred = dfp.tall.c1.k2$glial.pred,
-cell.type = rep("glial", nrow(dfp.tall.c1.k2)),
-type = dfp.tall.c1.k2$type,
-error = dfp.tall.c1.k2$glial.abs.error),
-data.frame(true = dfp.tall.c1.k2$neuron.true,
-pred = dfp.tall.c1.k2$neuron.pred,
-cell.type = rep("neuron", nrow(dfp.tall.c1.k2)),
-type = dfp.tall.c1.k2$type,
-error = dfp.tall.c1.k2$neuron.abs.error)) |>
-as.data.frame()
-plotK2.scatter.c1 <- ggplot(dfp.c1, aes(x = true, y = pred)) +
-geom_point() + theme_bw() + geom_abline(slope = 1) +
-theme(axis.text.x = element_text(angle = 45, hjust=1)) +
-xlab("Known") + ylab("Predicted") + ggtitle("Huuki-Meyers et. al. 2023") +
-xlim(0,1) + ylim(0,1) +
-facet_wrap(~cell.type*type)
-plotK2.box.c1 <- ggplot(dfp.c1, aes(x = type, y = error)) +
-geom_boxplot(color="cyan") + geom_jitter(alpha = 0.5) + theme_bw() +
-theme(axis.text.x = element_text(angle = 45,hjust=1), axis.title.x = element_blank()) +
-ylab("Error") + ggtitle("\n") + ylim(0, 0.3) + facet_wrap(~cell.type, nrow = 2)
-layoutMatrix <- matrix(rep(c(1,1,2,3,3,4), 2), byrow=T, nrow=2)
-grid.arrange(plotK2.scatter.c1,
-plotK2.box.c1,
-plotK2.scatter.c2,
-plotK2.box.c2,
-layout_matrix = layoutMatrix)
 setwd("..")
 setwd("..")
 jpeg("./figures/01_multipanel/pseudobulk-k2-2cohort_multi.jpg", width = 10, height = 4, units = "in", res = 400)
@@ -245,9 +337,6 @@ plotK2.scatter.c2,
 plotK2.box.c2,
 layout_matrix = layoutMatrix)
 dev.off()
-gc()
-gc()
-gc()
 libv <- c("here", "nlme", "lute", "ggplot2", "gridExtra",
 "dplyr", "ggforce", "MultiAssayExperiment", "SingleCellExperiment")
 sapply(libv, library, character.only = TRUE)
@@ -256,57 +345,6 @@ setwd("..")
 setwd("..")
 list.files()
 load("env/01_multipanel/01_pseudobulk_script.RData")
-head(dfp.tall.c1.k3)
-dfp.c1 <- rbind(data.frame(true = dfp.tall.c1.k3$glial.true,
-pred = dfp.tall.c1.k3$glial.pred,
-cell.type = rep("glial", nrow(dfp.tall.c1.k3)),
-type = dfp.tall.c1.k3$type,
-error = dfp.tall.c1.32$glial.abs.error),
-data.frame(true = dfp.tall.c1.k3$Excit.true,
-pred = dfp.tall.c1.k3$Excit.pred,
-cell.type = rep("Excit", nrow(dfp.tall.c1.k3)),
-type = dfp.tall.c1.k3$type,
-error = dfp.tall.c1.k3$Excit.abs.error),
-data.frame(true = dfp.tall.c1.k3$Inhib.true,
-pred = dfp.tall.c1.k3$Inhib.pred,
-cell.type = rep("Inhib", nrow(dfp.tall.c1.k3)),
-type = dfp.tall.c1.k3$type,
-error = dfp.tall.c1.k3$Inhib.abs.error)) |>
-as.data.frame()
-dfp.tall.c1.k3$# cohort 1
-dfp.c1 <- rbind(data.frame(true = dfp.tall.c1.k3$glial.true,
-pred = dfp.tall.c1.k3$glial.pred,
-cell.type = rep("glial", nrow(dfp.tall.c1.k3)),
-type = dfp.tall.c1.k3$type,
-error = dfp.tall.c1.3$glial.abs.error),
-data.frame(true = dfp.tall.c1.k3$Excit.true,
-pred = dfp.tall.c1.k3$Excit.pred,
-cell.type = rep("Excit", nrow(dfp.tall.c1.k3)),
-type = dfp.tall.c1.k3$type,
-error = dfp.tall.c1.k3$Excit.abs.error),
-data.frame(true = dfp.tall.c1.k3$Inhib.true,
-pred = dfp.tall.c1.k3$Inhib.pred,
-cell.type = rep("Inhib", nrow(dfp.tall.c1.k3)),
-type = dfp.tall.c1.k3$type,
-error = dfp.tall.c1.k3$Inhib.abs.error)) |>
-as.data.frame()
-# cohort 1
-dfp.c1 <- rbind(data.frame(true = dfp.tall.c1.k3$glial.true,
-pred = dfp.tall.c1.k3$glial.pred,
-cell.type = rep("glial", nrow(dfp.tall.c1.k3)),
-type = dfp.tall.c1.k3$type,
-error = dfp.tall.c1.3$glial.abs.error),
-data.frame(true = dfp.tall.c1.k3$Excit.true,
-pred = dfp.tall.c1.k3$Excit.pred,
-cell.type = rep("Excit", nrow(dfp.tall.c1.k3)),
-type = dfp.tall.c1.k3$type,
-error = dfp.tall.c1.k3$Excit.abs.error),
-data.frame(true = dfp.tall.c1.k3$Inhib.true,
-pred = dfp.tall.c1.k3$Inhib.pred,
-cell.type = rep("Inhib", nrow(dfp.tall.c1.k3)),
-type = dfp.tall.c1.k3$type,
-error = dfp.tall.c1.k3$Inhib.abs.error)) |>
-as.data.frame()
 # cohort 1
 dfp.c1 <- rbind(data.frame(true = dfp.tall.c1.k3$glial.true,
 pred = dfp.tall.c1.k3$glial.pred,
@@ -324,56 +362,14 @@ cell.type = rep("Inhib", nrow(dfp.tall.c1.k3)),
 type = dfp.tall.c1.k3$type,
 error = dfp.tall.c1.k3$Inhib.abs.error)) |>
 as.data.frame()
-dfp.c2 <- rbind(data.frame(true = dfp.tall.c2.k3$glial.true,
-pred = dfp.tall.c2.k3$glial.pred,
-cell.type = rep("glial", nrow(dfp.tall.c2.k3)),
-type = dfp.tall.c2.k3$type,
-error = dfp.tall.c2.k3$glial.abs.error),
-data.frame(true = dfp.tall.c2.k3$Excit.true,
-pred = dfp.tall.c2.k3$Excit.pred,
-cell.type = rep("Excit", nrow(dfp.tall.c2.k3)),
-type = dfp.tall.c2.k3$type,
-error = dfp.tall.c2.k3$Excit.abs.error),
-data.frame(true = dfp.tall.c2.k3$Inhib.true,
-pred = dfp.tall.c2.k3$Inhib.pred,
-cell.type = rep("Inhib", nrow(dfp.tall.c2.k3)),
-type = dfp.tall.c2.k3$type,
-error = dfp.tall.c2.k3$Inhib.abs.error)) |>
-as.data.frame()
-plotK3.scatter.c1 <- ggplot(dfp.c1, aes(x = true, y = pred)) +
-geom_point() + theme_bw() + geom_abline(slope = 1) +
-theme(axis.text.x = element_text(angle = 45, hjust=1)) +
-xlab("Known") + ylab("Predicted") + ggtitle("Huuki-Meyers et. al. 2023") +
-xlim(0,1) + ylim(0,1) +
-facet_wrap(~cell.type*type)
-plotK3.scatter.c1
-ggplot(dfp.c1, aes(x = true, y = pred)) +
-geom_point() + theme_bw() + geom_abline(slope = 1) +
-theme(axis.text.x = element_text(angle = 45, hjust=1)) +
-xlab("Known") + ylab("Predicted") + ggtitle("Huuki-Meyers et. al. 2023") +
-xlim(0,1) + ylim(0,1) +
-facet_wrap(~type*cell.type)
-ggplot(dfp.c1, aes(x = true, y = pred)) +
-geom_point() + theme_bw() + geom_abline(slope = 1) +
-theme(axis.text.x = element_text(angle = 45, hjust=1)) +
-xlab("Known") + ylab("Predicted") + ggtitle("Huuki-Meyers et. al. 2023") +
-xlim(0,1) + ylim(0,1) +
-facet_wrap(~type*cell.type, ncol = 2)
-ggplot(dfp.c1, aes(x = true, y = pred)) +
-geom_point() + theme_bw() + geom_abline(slope = 1) +
-theme(axis.text.x = element_text(angle = 45, hjust=1)) +
-xlab("Known") + ylab("Predicted") + ggtitle("Huuki-Meyers et. al. 2023") +
-xlim(0,1) + ylim(0,1) +
-facet_wrap(~cell.type*type, ncol = 2)
-dfp.c1$cell.type <- factor(dfp.c1$cell.type, levels = c("glial", "Excit", "Inhib"))
+dfp.c1$cell.type <- factor(dfp.c1$cell.type, levels = c("Excit", "Inhib", "glial"))
 plotK3.scatter.c1 <- ggplot(dfp.c1, aes(x = true, y = pred)) +
 geom_point() + theme_bw() + geom_abline(slope = 1) +
 theme(axis.text.x = element_text(angle = 45, hjust=1)) +
 xlab("Known") + ylab("Predicted") + ggtitle("Huuki-Meyers et. al. 2023") +
 xlim(0,1) + ylim(0,1) +
-facet_wrap(~cell.type*type, ncol = 2)
-plotK3.scatter.c1
-ggplot(dfp.c1, aes(x = type, y = error)) +
+facet_wrap(type~cell.type)
+plotK3.box.c1 <- ggplot(dfp.c1, aes(x = type, y = error)) +
 geom_boxplot(color="cyan") + geom_jitter(alpha = 0.5) + theme_bw() +
 theme(axis.text.x = element_text(angle = 45,hjust=1), axis.title.x = element_blank()) +
 ylab("Error") + ggtitle("\n") + ylim(0, 0.3) + facet_wrap(~cell.type, nrow = 3)
@@ -394,24 +390,26 @@ cell.type = rep("Inhib", nrow(dfp.tall.c2.k3)),
 type = dfp.tall.c2.k3$type,
 error = dfp.tall.c2.k3$Inhib.abs.error)) |>
 as.data.frame()
-dfp.c2$cell.type <- factor(dfp.c2$cell.type, levels = c("glial", "Excit", "Inhib"))
+dfp.c2$cell.type <- factor(dfp.c2$cell.type, levels = c("Excit", "Inhib", "glial"))
 plotK3.scatter.c2 <- ggplot(dfp.c2, aes(x = true, y = pred)) +
 geom_point() + theme_bw() + geom_abline(slope = 1) +
 theme(axis.text.x = element_text(angle = 45, hjust=1)) +
-xlab("Known") + ylab("Predicted") + ggtitle("Huuki-Meyers et. al. 2023") +
-xlim(0,1) + ylim(0,1) + facet_wrap(~cell.type*type, ncol = 2)
+xlab("Known") + ylab("Predicted") + ggtitle("Tran et. al. 2021") +
+xlim(0,1) + ylim(0,1) + facet_wrap(type~cell.type)
 plotK3.box.c2 <- ggplot(dfp.c2, aes(x = type, y = error)) +
 geom_boxplot(color="cyan") + geom_jitter(alpha = 0.5) + theme_bw() +
 theme(axis.text.x = element_text(angle = 45,hjust=1), axis.title.x = element_blank()) +
 ylab("Error") + ggtitle("\n") + ylim(0, 0.3) + facet_wrap(~cell.type, nrow = 3)
-plotK3.scatter.c2
-plotK3.box.c2
+setwd("..")
+setwd("..")
+jpeg("./figures/01_multipanel/pseudobulk-k3-2cohort_multi.jpg", width = 10, height = 4, units = "in", res = 400)
 layoutMatrix <- matrix(rep(c(1,1,2,3,3,4), 2), byrow=T, nrow=2)
 grid.arrange(plotK3.scatter.c1,
 plotK3.box.c1,
 plotK3.scatter.c2,
 plotK3.box.c2,
 layout_matrix = layoutMatrix)
+dev.off()
 # cohort 1
 dfp.c1 <- rbind(data.frame(true = dfp.tall.c1.k3$glial.true,
 pred = dfp.tall.c1.k3$glial.pred,
@@ -435,44 +433,46 @@ geom_point() + theme_bw() + geom_abline(slope = 1) +
 theme(axis.text.x = element_text(angle = 45, hjust=1)) +
 xlab("Known") + ylab("Predicted") + ggtitle("Huuki-Meyers et. al. 2023") +
 xlim(0,1) + ylim(0,1) +
-facet_wrap(~cell.type*type, ncol = 2)
+facet_grid(type~cell.type)
 plotK3.box.c1 <- ggplot(dfp.c1, aes(x = type, y = error)) +
 geom_boxplot(color="cyan") + geom_jitter(alpha = 0.5) + theme_bw() +
 theme(axis.text.x = element_text(angle = 45,hjust=1), axis.title.x = element_blank()) +
 ylab("Error") + ggtitle("\n") + ylim(0, 0.3) + facet_wrap(~cell.type, nrow = 3)
-# cohort 2
-dfp.c2 <- rbind(data.frame(true = dfp.tall.c2.k3$glial.true,
-pred = dfp.tall.c2.k3$glial.pred,
-cell.type = rep("glial", nrow(dfp.tall.c2.k3)),
-type = dfp.tall.c2.k3$type,
-error = dfp.tall.c2.k3$glial.abs.error),
-data.frame(true = dfp.tall.c2.k3$Excit.true,
-pred = dfp.tall.c2.k3$Excit.pred,
-cell.type = rep("Excit", nrow(dfp.tall.c2.k3)),
-type = dfp.tall.c2.k3$type,
-error = dfp.tall.c2.k3$Excit.abs.error),
-data.frame(true = dfp.tall.c2.k3$Inhib.true,
-pred = dfp.tall.c2.k3$Inhib.pred,
-cell.type = rep("Inhib", nrow(dfp.tall.c2.k3)),
-type = dfp.tall.c2.k3$type,
-error = dfp.tall.c2.k3$Inhib.abs.error)) |>
+plotK3.scatter.c1
+ggplot(dfp.c1, aes(x = true, y = pred)) +
+geom_point() + theme_bw() + geom_abline(slope = 1) +
+theme(axis.text.x = element_text(angle = 45, hjust=1)) +
+xlab("Known") + ylab("Predicted") + ggtitle("Huuki-Meyers et. al. 2023") +
+xlim(0,1) + ylim(0,1) +
+facet_grid(cell.type~type)
+# cohort 1
+dfp.c1 <- rbind(data.frame(true = dfp.tall.c1.k3$glial.true,
+pred = dfp.tall.c1.k3$glial.pred,
+cell.type = rep("glial", nrow(dfp.tall.c1.k3)),
+type = dfp.tall.c1.k3$type,
+error = dfp.tall.c1.k3$glial.abs.error),
+data.frame(true = dfp.tall.c1.k3$Excit.true,
+pred = dfp.tall.c1.k3$Excit.pred,
+cell.type = rep("Excit", nrow(dfp.tall.c1.k3)),
+type = dfp.tall.c1.k3$type,
+error = dfp.tall.c1.k3$Excit.abs.error),
+data.frame(true = dfp.tall.c1.k3$Inhib.true,
+pred = dfp.tall.c1.k3$Inhib.pred,
+cell.type = rep("Inhib", nrow(dfp.tall.c1.k3)),
+type = dfp.tall.c1.k3$type,
+error = dfp.tall.c1.k3$Inhib.abs.error)) |>
 as.data.frame()
-dfp.c2$cell.type <- factor(dfp.c2$cell.type, levels = c("Excit", "Inhib", "glial"))
-plotK3.scatter.c2 <- ggplot(dfp.c2, aes(x = true, y = pred)) +
+dfp.c1$cell.type <- factor(dfp.c1$cell.type, levels = c("Excit", "Inhib", "glial"))
+plotK3.scatter.c1 <- ggplot(dfp.c1, aes(x = true, y = pred)) +
 geom_point() + theme_bw() + geom_abline(slope = 1) +
 theme(axis.text.x = element_text(angle = 45, hjust=1)) +
 xlab("Known") + ylab("Predicted") + ggtitle("Huuki-Meyers et. al. 2023") +
-xlim(0,1) + ylim(0,1) + facet_wrap(~cell.type*type, ncol = 2)
-plotK3.box.c2 <- ggplot(dfp.c2, aes(x = type, y = error)) +
+xlim(0,1) + ylim(0,1) +
+facet_grid(cell.type~type)
+plotK3.box.c1 <- ggplot(dfp.c1, aes(x = type, y = error)) +
 geom_boxplot(color="cyan") + geom_jitter(alpha = 0.5) + theme_bw() +
 theme(axis.text.x = element_text(angle = 45,hjust=1), axis.title.x = element_blank()) +
 ylab("Error") + ggtitle("\n") + ylim(0, 0.3) + facet_wrap(~cell.type, nrow = 3)
-layoutMatrix <- matrix(rep(c(1,1,2,3,3,4), 2), byrow=T, nrow=2)
-grid.arrange(plotK3.scatter.c1,
-plotK3.box.c1,
-plotK3.scatter.c2,
-plotK3.box.c2,
-layout_matrix = layoutMatrix)
 # cohort 2
 dfp.c2 <- rbind(data.frame(true = dfp.tall.c2.k3$glial.true,
 pred = dfp.tall.c2.k3$glial.pred,
@@ -495,7 +495,7 @@ plotK3.scatter.c2 <- ggplot(dfp.c2, aes(x = true, y = pred)) +
 geom_point() + theme_bw() + geom_abline(slope = 1) +
 theme(axis.text.x = element_text(angle = 45, hjust=1)) +
 xlab("Known") + ylab("Predicted") + ggtitle("Tran et. al. 2021") +
-xlim(0,1) + ylim(0,1) + facet_wrap(~cell.type*type, ncol = 2)
+xlim(0,1) + ylim(0,1) + facet_grid(cell.type~type)
 plotK3.box.c2 <- ggplot(dfp.c2, aes(x = type, y = error)) +
 geom_boxplot(color="cyan") + geom_jitter(alpha = 0.5) + theme_bw() +
 theme(axis.text.x = element_text(angle = 45,hjust=1), axis.title.x = element_blank()) +