devtools::load_all()
library(ggplot2)
library(magrittr)
library(dplyr)
list[geneDat, exp] = n_expressoExpr %>%
filter(!grepl(pattern='\\|',Gene.Symbol)) %>%
sepExpr
rownames(exp) = geneDat$Gene.Symbol
design = n_expressoSamples
design %<>% filter(PyramidalDeep %in% c('ForebrainCholin',
'ThalamusCholin')) %>%
mutate(PyramidalDeep = PyramidalDeep %>% factor(levels=c('ForebrainCholin',
'ThalamusCholin'))) %>%
arrange(PyramidalDeep)
cholinergic = exp[geneDat$Gene.Symbol %in% c('Gad1','Gad2','Slc32a1','Slc17a6','Slc18a3'),design$sampleName] %>%
as.matrix %>%
melt %>%
mutate(Var2 = design$ShinyNames[match(Var2,design$sampleName)],
Var1 = factor(Var1,levels = c('Slc18a3','Gad1','Gad2','Slc32a1','Slc17a6')))
(cholinergic %>% ggplot(aes(x = Var1, y= value, group = Var2, color=Var2)) +
geom_point(position=position_dodge(width = 0.4), size = 4,fill ='black') +
scale_x_discrete(name='') +
theme_cowplot(21) +
theme(legend.position="bottom",
legend.direction = 'vertical') +
geom_vline(xintercept = c(1.5,2.5,3.5,4.5), linetype='dotted') +
scale_y_continuous(name = bquote(log[2]~' expression')) +
scale_color_manual(name='Cell Type',values = c('darkorange','darkorange4'))) %>%
ggsave(plot = ., filename='analysis/07.GeneExpressionPlots/cholinergic.png', width=8,height = 4)
# gabaergic
design = n_expressoSamples
design %<>% filter(ShinyNames %in% c('FS Basket (G42)',
'Martinotti (GIN)',
'VIPReln (G30)')) %>%
mutate(ShinyNames = ShinyNames %>% factor(levels=c('FS Basket (G42)',
'Martinotti (GIN)',
'VIPReln (G30)'))) %>%
arrange(ShinyNames)
gabaergic = exp[geneDat$Gene.Symbol %in% c('Sst'),design$sampleName] %>%
as.matrix %>%
melt %>%
mutate(Var2 = design$ShinyNames[match(Var2,design$sampleName)])
(gabaergic %>% ggplot(aes(x= Var2, y = value, color = Var2)) +
geom_point(size = 4) + theme_cowplot(17) +
theme(legend.position="none",
axis.text.x = element_text(angle = 90, hjust = 1)) +
scale_color_manual(name='Cell Type',values = c('firebrick2','firebrick3','firebrick4')) +
xlab('') + ylab(bquote('Sst '~log[2]~' expression'))
) %>% ggsave(plot = ., filename='analysis/07.GeneExpressionPlots/gabaergic.png', width=3,height = 5)
# phani vs chung dopaminergic------------------
design = n_expressoSamples
design %<>% filter(Reference %in% c('Chung et al., 2005',
'Phani et al. 2015')) %>%
mutate(PyramidalDeep = PyramidalDeep %>% factor(levels=c('Phani et al. 2015',
'Chung et al., 2005'))) %>%
arrange(Reference)
dopaminergic = exp[geneDat$Gene.Symbol %in% c('Map2','Plcb4','Card10','Kifc2'),design$sampleName] %>%
as.matrix %>%
melt %>%
mutate(Var2 = design$Reference[match(Var2,design$sampleName)],
Var1 = factor(Var1,levels = c('Map2','Plcb4','Card10','Kifc2')))
(dopaminergic %>% ggplot(aes(x = Var1, y= value, group = Var2, color=Var2)) +
geom_point(position=position_dodge(width = 0.4), size = 4,fill ='black') +
scale_x_discrete(name='') +
theme_cowplot(21) +
theme(legend.position="bottom",
legend.direction = 'vertical') +
geom_vline(xintercept = c(1.5,2.5,3.5,4.5), linetype='dotted') +
scale_y_continuous(name = bquote(log[2]~' expression')) +
scale_color_manual(name='Cell Type',values = c('black','gray'), guide = guide_legend(title = ""))) %>%
ggsave(plot = ., filename='analysis/07.GeneExpressionPlots/dopaminergic.png', width=5,height = 4)
# Olig1 and Fam114a1 in cortex----------------
design = n_expressoSamples
regionSamples = memoReg(design = design,regionNames = 'Region',groupNames = 'CellTypes',regionHierarchy=regionHierarchy)
design %<>% filter(!is.na(regionSamples$Cortex_CellTypes)) %>%
arrange(MajorType,Neurotransmitter,CellTypes)
cortical = exp[geneDat$Gene.Symbol %in% c('Fam114a1'),design$sampleName] %>% as.matrix %>% melt %>%
mutate(Var2 = design$CellTypes[match(Var2,design$sampleName)] %>% translatePublishable #%>% factor(levels=design$CellTypes %>% unique)
)
cortical$source= 'Microarray'
design = meltedSingleCells
cortical2 = TasicPrimaryMeanLog[c('Fam114a1'),design$sampleName] %>% as.matrix %>% melt %>%
mutate(Var2 = design$CellTypes[match(Var2,design$sampleName)])
cortical2$source = 'RNAseq'
cortical2$Var2 %<>% translatePublishable
cortical2$Var2 %<>% replaceElement(c('Oligodendrocyte precursors' = 'Oligodendrocyte prec.')) %$% newVector
order = cellOrder %>% translatePublishable %>% replaceElement(c('Oligodendrocyte precursors' = 'Oligodendrocyte prec.')) %$% newVector
cortical = rbind(cortical,cortical2)
cortical %<>%
mutate(Var2 = Var2 %>%
factor(levels =cortical$Var2 %>% unique %>% {.[match(order,.)]} %>% trimNAs))
(cortical %>% ggplot(aes(x = Var2, y = value, color = Var2)) +
geom_point(size = 1) +
theme_cowplot(8) +
xlab('') +
ylab(bquote('Fam114a1 '~log[2]~' expression'))+
theme(axis.text.x = element_text(angle = 45, hjust = 1),
panel.background = element_rect(fill=NA, color="black",size=0.3,linetype='solid'))+
facet_wrap(~source,scales='free',nrow = 2) +
scale_color_manual(values = cellColors(),guide = FALSE)) %>%
ggsave(plot = .,filename = 'analysis/07.GeneExpressionPlots/olig1_Fam114a1.png', width = 4.1,height = 9.50,units='cm')
# Ddc in oligodendrocyte --------------
design = n_expressoSamples
regionSamples = memoReg(design = design,regionNames = 'Region',groupNames = 'ShinyNames',regionHierarchy=regionHierarchy)
design %<>% filter((!is.na(regionSamples$Cortex_ShinyNames))| design$ShinyNames %in% 'Dopaminergic') %>%
arrange(MajorType,Neurotransmitter,PyramidalDeep)
cortical = exp[geneDat$Gene.Symbol %in% c('Ddc'),design$sampleName] %>% as.matrix %>% melt %>%
mutate(Source = design$Reference[match(Var2,design$sampleName)],
Var2 = design$ShinyNames[match(Var2,design$sampleName)] %>% factor(levels=design$ShinyNames %>% unique))
cortical$Groups = cortical %>% apply(1,function(x){
if(x['Var2'] == 'Oligodendrocyte'){
return(x['Source'])
} else if(x['Var2'] == 'Dopaminergic'){
return('dopaminergic')
} else{
return('others')
}
})
cortical$Source = 'Microarray'
design = meltedSingleCells
regionSamples = memoReg(design = design,regionNames = 'Region',groupNames = 'ShinyNames',regionHierarchy=regionHierarchy)
design %<>% filter((!is.na(regionSamples$Cortex_ShinyNames))| design$ShinyNames %in% 'Dopaminergic') %>%
arrange(MajorType,Neurotransmitter,PyramidalDeep)
cortical2 = TasicPrimaryMeanLog['Ddc',design$sampleName] %>% as.matrix %>% melt %>%
mutate(Source = design$Reference[match(Var2,design$sampleName)],
Var2 = design$ShinyNames[match(Var2,design$sampleName)] %>% factor(levels=design$ShinyNames %>% unique))
cortical2$Groups = cortical2 %>% apply(1,function(x){
if(x['Var2'] == 'Oligodendrocyte' | x['Var2'] == 'Oligodendrocyte precursors' ){
return(x['Var2'])
} else{
return('others')
}
})
cortical2$Source = 'RNAseq'
cortical = rbind(cortical,cortical2)
cortical$Groups %<>% replaceElement(c('Oligodendrocyte precursors' = 'Oligodendrocyte prec')) %$% newVector
cortical$Groups %<>% factor(levels=c('Cahoy et al., 2008', 'Doyle et al., 2008', 'Fomchenko et al 2011', 'dopaminergic','Oligodendrocyte','Oligodendrocyte prec' ,'others'))
(cortical %>% ggplot(aes(x = Groups, y = value, color = Groups)) + facet_wrap(~Source,scales='free')+
geom_point(size = 4) +
theme_cowplot(21) +
xlab('') +
ylab(bquote('Ddc '~log[2]~' expression'))+
theme(axis.text.x = element_text(angle = 60, hjust = 1))+
scale_color_viridis(discrete = TRUE, guide=FALSE)) %>% ggsave(plot = .,filename = 'analysis/07.GeneExpressionPlots/Ddc.png', width = 4.5,height = 6)
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