install.packages("ggpubr")
library(ggpubr)
library(ggplot2)
install.packaes("ggpubr")
install.packages("ggpubr")
install.packages("ggpubr")
# There are binary versions available but the source versions are later:
binary    source needs_compilation
Matrix           1.3-4     1.5-3              TRUE
MatrixModels     0.5-0     0.5-1             FALSE
minqa            1.2.4     1.2.5              TRUE
nloptr         1.2.2.3     2.0.3              TRUE
RcppEigen    0.3.3.9.1 0.3.3.9.3              TRUE
quantreg          5.85      5.94              TRUE
lme4            1.1-28    1.1-31              TRUE
car             3.0-10     3.1-1             FALSE
rstatix          0.7.0     0.7.1             FALSE
ggpubr           0.4.0     0.5.0             FALSE
install.packages("Matrix")
save.image("~/Documents/Lowe Lab/Data/vertCons/figureDev.RData")
savehistory("~/Documents/Lowe Lab/Data/vertCons/figureDev.Rhistor")
savehistory("~/Documents/Lowe Lab/Data/vertCons/figureDev.Rhistory")
install.packages("ggplot2")
install.packages("ggplot2")
install.packages("ggplot2")
library(ggplot2)
library(tibble)
install.packages("ggpubr")
install.packages("SparseM")
library(ggplot2)
install.packages("tidyverse")
withr::with_makevars(c(OBJCXX = "gcc"), install.packages('systemfonts'))
install.packages("systemfonts")
remove.packages("systemfonts")
install.packages("systemfonts")
library(ggpubr)
library(tidyverse)
setwd("Documents/Lowe Lab/Data/vertCons/60way/rGraphs/")
neuroPlas <- read.csv("neuronPlasticitySubgroup.tsv", header=TRUE, sep="\t")
immPlas <- read.csv("innateImmPlasticitySubgroups.tsv", header=TRUE, sep="\t")
muscPlas <- read.csv("musclePlasticitySubgroups.tsv", header=TRUE, sep="\t")
immPlasGraph <- tibble(Type=as.factor(immPlas$CellType), MYA=as.numeric(as.character(factor(immPlas$MYA))), Enrichment=as.numeric(as.character(factor(immPlas$Z.Score)))) %>% ggplot(aes(x=MYA, y=Enrichment, group=Type, color=Type)) + geom_line() + geom_point() + geom_hline(yintercept=0, linetype="dotted", col="black") + theme_classic() + scale_x_reverse(limits=c(600,0)) + ylim=c(-4, 4)
immPlasGraph <- tibble(Type=as.factor(immPlas$CellType), MYA=as.numeric(as.character(factor(immPlas$MYA))), Enrichment=as.numeric(as.character(factor(immPlas$Z.Score)))) %>% ggplot(aes(x=MYA, y=Enrichment, group=Type, color=Type)) + geom_line() + geom_point() + geom_hline(yintercept=0, linetype="dotted", col="black") + theme_classic() + scale_x_reverse(limits=c(600,0)) + ylim=c(-4, 4)
immPlasGraph <- tibble(Type=as.factor(immPlas$CellType), MYA=as.numeric(as.character(factor(immPlas$MYA))), Enrichment=as.numeric(as.character(factor(immPlas$Z.Score)))) %>% ggplot(aes(x=MYA, y=Enrichment, group=Type, color=Type)) + geom_line() + geom_point() + geom_hline(yintercept=0, linetype="dotted", col="black") + theme_classic() + scale_x_reverse(limits=c(600,0))
ggpar(immPlasGraph, ylim = c(-4,4))
immPlasGraph <- tibble(Type=as.factor(immPlas$CellType), MYA=as.numeric(as.character(factor(immPlas$MYA))), Enrichment=as.numeric(as.character(factor(immPlas$Z.Score)))) %>% ggplot(aes(x=MYA, y=Enrichment, group=Type, color=Type)) + geom_line() + geom_point() + geom_hline(yintercept=0, linetype="dotted", col="black") + theme_classic() + scale_x_reverse(limits=c(600,0)) + eom_hline(yintercept=1.6, col="black")
immPlasGraph <- tibble(Type=as.factor(immPlas$CellType), MYA=as.numeric(as.character(factor(immPlas$MYA))), Enrichment=as.numeric(as.character(factor(immPlas$Z.Score)))) %>% ggplot(aes(x=MYA, y=Enrichment, group=Type, color=Type)) + geom_line() + geom_point() + geom_hline(yintercept=0, linetype="dotted", col="black") + theme_classic() + scale_x_reverse(limits=c(600,0)) + geom_hline(yintercept=1.6, col="black")
immPlasGraph <- tibble(Type=as.factor(immPlas$CellType), MYA=as.numeric(as.character(factor(immPlas$MYA))), Enrichment=as.numeric(as.character(factor(immPlas$Z.Score)))) %>% ggplot(aes(x=MYA, y=Enrichment, group=Type, color=Type)) + geom_line() + geom_point() + geom_hline(yintercept=0, linetype="dotted", col="black") + theme_classic() + scale_x_reverse(limits=c(600,0)) + geom_hline(yintercept=1.6, col="black") + geom_hline(yintercept=-1.6, col="black")
ggpar(immPlasGraph, ylim = c(-4,4))
muscPlasGraph <- tibble(Type=as.factor(muscPlas$CellType), MYA=as.numeric(as.character(factor(muscPlas$MYA))), Enrichment=as.numeric(as.character(factor(muscPlas$Z.Score)))) %>% ggplot(aes(x=MYA, y=Enrichment, group=Type, color=Type)) + geom_line() + geom_point() + geom_hline(yintercept=1, linetype="dotted", col="black") + theme_classic() + scale_x_reverse(limits=c(600,0)) + geom_hline(yintercept=1.6, col="black") + geom_hline(yintercept=-1.6, col="black")
ggpar(muscPlasGraph, ylim=c(-4,4))
neuroPlasGraph <- tibble(Type=as.factor(neuroPlas$CellType), MYA=as.numeric(as.character(factor(neuroPlas$MYA))), Enrichment=as.numeric(as.character(factor(neuroPlas$Z.Score)))) %>% ggplot(aes(x=MYA, y=Enrichment, group=Type, color=Type)) + geom_line() + geom_point() + geom_hline(yintercept=1, linetype="dotted", col="black") + theme_classic() + scale_x_reverse(limits=c(600,0)) + geom_hline(yintercept=1.6, col="black") + geom_hline(yintercept=-1.6, col="black")
ggpar(neuroPlasGraph, ylim=c(-4,4))
tissPlasticity <- read.csv("tissPlasticityUpdated.tsv", header=TRUE, sep="\t")
View(tissPlasticity)
deathNum <- transform(tissPlasticity, tiss=as.numeric(as.factor(CTissue)))
allTissues <- tibble(Type=as.factor(tissPlasticity$Tissue), Node=as.numeric(as.character(factor(tissPlasticity$MYA))), Plasticity=as.numeric(as.character(factor(tissPlasticity$Z.Score)))) %>% ggplot( aes(x=Node, y=Plasticity, group=Type, color=Type)) +
+     geom_line() + theme_classic() +
+     theme(legend.position="top", plot.title = element_text(size=16)) +
+     facet_wrap(~Type, scale="free_y") + geom_hline(yintercept=0, linetype="dotted", col="black") + scale_color_hue()
allTissues <- tibble(Type=as.factor(tissPlasticity$Tissue), Node=as.numeric(as.character(factor(tissPlasticity$MYA))), Plasticity=as.numeric(as.character(factor(tissPlasticity$Z.Score)))) %>% ggplot( aes(x=Node, y=Plasticity, group=Type, color=Type)) +     geom_line() + theme_classic() + theme(legend.position="top", plot.title = element_text(size=16)) +     facet_wrap(~Type, scale="free_y") + geom_hline(yintercept=0, linetype="dotted", col="black") + scale_color_hue()
ggpar(allTissues)
allTissues <- tibble(Type=as.factor(tissPlasticity$Tissue), Node=as.numeric(as.character(factor(tissPlasticity$MYA))), Plasticity=as.numeric(as.character(factor(tissPlasticity$Z.Score)))) %>% ggplot( aes(x=Node, y=Plasticity, group=Type, color=Type)) +     geom_line() + theme_classic() + theme(legend.position="top", plot.title = element_text(size=16)) +     facet_wrap(~Type, scale="free_y") + geom_hline(yintercept=0, linetype="dotted", col="black") + scale_color_hue() + scale_x_reverse(limits=c(600,0)) + geom_hline(yintercept=1.6, col="black") + geom_hline(yintercept=-1.6, col="black")
ggpar(allTissues)
ggpar(allTissues, ylim=c(-4,4))
ggpar(allTissues)
allTissues <- tibble(Type=as.factor(tissPlasticity$Tissue), Node=as.numeric(as.character(factor(tissPlasticity$MYA))), Plasticity=as.numeric(as.character(factor(tissPlasticity$Z.Score)))) %>% ggplot( aes(x=Node, y=Plasticity, group=Type, color=Type)) +     geom_line() + theme_classic() + theme(legend.position="top", plot.title = element_text(size=16)) +     facet_wrap(~Type, scale="free_y", ncol=1) + geom_hline(yintercept=0, linetype="dotted", col="black") + scale_color_hue() + scale_x_reverse(limits=c(600,0)) + geom_hline(yintercept=1.6, col="black") + geom_hline(yintercept=-1.6, col="black")
ggpar(allTissues)
savehistory("plasticitySubgroupAndAllTissues.Rhistory")