GTEx V6
Yuxin Zou
2018-12-20
Last updated: 2019-01-29
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| html | 5d17b16 | zouyuxin | 2019-01-29 | Build site. |
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library(mashr)Loading required package: ashrlibrary(knitr)
library(kableExtra)
library(ggplot2)
library(gridExtra)gtex <- readRDS(gzcon(url("https://github.com/stephenslab/gtexresults/blob/master/data/MatrixEQTLSumStats.Portable.Z.rds?raw=TRUE")))
missing.tissues <- c(7, 8, 19, 20, 24, 25, 31, 34, 37)
gtex.colors <- read.table("https://github.com/stephenslab/gtexresults/blob/master/data/GTExColors.txt?raw=TRUE", sep = '\t', comment.char = '')[-missing.tissues, 2]
gtex.colors <- as.character(gtex.colors)
gene.names = as.character(read.table('data/gene_names.txt')[,1])The results are from mashr_flashr_pipeline. We include the data driven covariance matrices based on the first three principal components and factors from flash.
Flash model based on effects:
factors = readRDS('output/GTExV6pipeline/MatrixEQTLSumStats.Portable.Z.EE.flash.model.rds')$factors
par(mfrow = c(2, 3))
for(k in 1:13){
barplot(factors[,k], col=gtex.colors, names.arg = FALSE, axes = FALSE, main=paste0("Factor ", k))
}
Expand here to see past versions of flash EE factors plot-1.png:
| Version | Author | Date |
|---|---|---|
| 02da57c | zouyuxin | 2019-01-27 |
Expand here to see past versions of flash EE factors plot-2.png:
| Version | Author | Date |
|---|---|---|
| 02da57c | zouyuxin | 2019-01-27 |
Expand here to see past versions of flash EE factors plot-3.png:
| Version | Author | Date |
|---|---|---|
| 02da57c | zouyuxin | 2019-01-27 |
Flash model based on z scores:
factors = readRDS('output/GTExV6pipeline/MatrixEQTLSumStats.Portable.Z.EZ.flash.model.rds')$factors
par(mfrow = c(2, 3))
for(k in 1:18){
barplot(factors[,k], col=gtex.colors, names.arg = FALSE, axes = FALSE, main=paste0("Factor ", k))
}
Expand here to see past versions of flash EZ factors plot-1.png:
| Version | Author | Date |
|---|---|---|
| 02da57c | zouyuxin | 2019-01-27 |
Expand here to see past versions of flash EZ factors plot-2.png:
| Version | Author | Date |
|---|---|---|
| 02da57c | zouyuxin | 2019-01-27 |
Expand here to see past versions of flash EZ factors plot-3.png:
| Version | Author | Date |
|---|---|---|
| 02da57c | zouyuxin | 2019-01-27 |
# read model
m_simple_EE = readRDS('output/GTExV6pipeline/MatrixEQTLSumStats.Portable.Z.EE.FL_PC3.mash_model_V_simple.rds')
m_simple_EE$result = readRDS('output/GTExV6pipeline/MatrixEQTLSumStats.Portable.Z.EE.FL_PC3.mash_model_V_simple.posterior.rds')
m_simple_EZ = readRDS('output/GTExV6pipeline/MatrixEQTLSumStats.Portable.Z.EZ.FL_PC3.mash_model_V_simple.rds')
m_simple_EZ$result = readRDS('output/GTExV6pipeline/MatrixEQTLSumStats.Portable.Z.EZ.FL_PC3.mash_model_V_simple.posterior.rds')
m_mle_EE = readRDS('output/GTExV6pipeline/MatrixEQTLSumStats.Portable.Z.EE.FL_PC3.mash_model_V_mle.rds')
m_mle_EE$result = readRDS('output/GTExV6pipeline/MatrixEQTLSumStats.Portable.Z.EE.FL_PC3.mash_model_V_mle.posterior.rds')
m_mle_EZ = readRDS('output/GTExV6pipeline/MatrixEQTLSumStats.Portable.Z.EZ.FL_PC3.mash_model_V_mle.rds')
m_mle_EZ$result = readRDS('output/GTExV6pipeline/MatrixEQTLSumStats.Portable.Z.EZ.FL_PC3.mash_model_V_mle.posterior.rds')
m_Vgene_EE_kushal = readRDS('output/GTExV6pipeline/MatrixEQTLSumStats.Portable.Z.EE.FL_PC3.V_corshrink_xcondition_kushal.mash_model.rds')
m_Vgene_EE_kushal$result = readRDS('output/GTExV6pipeline/MatrixEQTLSumStats.Portable.Z.EE.FL_PC3.V_corshrink_xcondition_kushal.posterior.rds')
m_Vgene_EZ_kushal = readRDS('output/GTExV6pipeline/MatrixEQTLSumStats.Portable.Z.EZ.FL_PC3.V_corshrink_xcondition_kushal.mash_model.rds')
m_Vgene_EZ_kushal$result = readRDS('output/GTExV6pipeline/MatrixEQTLSumStats.Portable.Z.EZ.FL_PC3.V_corshrink_xcondition_kushal.posterior.rds')
m_Vgene_EE_nullz = readRDS('output/GTExV6pipeline/MatrixEQTLSumStats.Portable.Z.EE.FL_PC3.V_corshrink_xcondition_nullz.mash_model.rds')
m_Vgene_EE_nullz$result = readRDS('output/GTExV6pipeline/MatrixEQTLSumStats.Portable.Z.EE.FL_PC3.V_corshrink_xcondition_nullz.posterior.rds')
m_Vgene_EZ_nullz = readRDS('output/GTExV6pipeline/MatrixEQTLSumStats.Portable.Z.EZ.FL_PC3.V_corshrink_xcondition_nullz.mash_model.rds')
m_Vgene_EZ_nullz$result = readRDS('output/GTExV6pipeline/MatrixEQTLSumStats.Portable.Z.EZ.FL_PC3.V_corshrink_xcondition_nullz.posterior.rds')Estimated null cor V
V.simple = readRDS('output/GTExV6pipeline/MatrixEQTLSumStats.Portable.Z.EE.FL_PC3.V_simple.rds')
corrplot::corrplot(V.simple, method='color', type='upper', tl.col="black", tl.srt=45, tl.cex = 0.5, diag = FALSE, col=colorRampPalette(c("blue", "white", "red"))(200), cl.lim = c(-1,1), title = 'Simple', mar=c(0,0,5,0))
Expand here to see past versions of V-1.png:
| Version | Author | Date |
|---|---|---|
| 02da57c | zouyuxin | 2019-01-27 |
# dev.off()
V.mle.EE = readRDS('output/GTExV6pipeline/MatrixEQTLSumStats.Portable.Z.EE.FL_PC3.V_mle.rds')
corrplot::corrplot(V.mle.EE, method='color', type='upper', tl.col="black", tl.srt=45, tl.cex = 0.5, diag = FALSE, col=colorRampPalette(c("blue", "white", "red"))(200), cl.lim = c(-1,1), title = 'MLE EE', mar=c(0,0,5,0))
Expand here to see past versions of V-2.png:
| Version | Author | Date |
|---|---|---|
| 02da57c | zouyuxin | 2019-01-27 |
V.mle.EZ = readRDS('output/GTExV6pipeline/MatrixEQTLSumStats.Portable.Z.EZ.FL_PC3.V_mle.rds')
corrplot::corrplot(V.mle.EZ, method='color', type='upper', tl.col="black", tl.srt=45, tl.cex = 0.5, diag = FALSE, col=colorRampPalette(c("blue", "white", "red"))(200), cl.lim = c(-1,1), title = 'MLE EZ', mar=c(0,0,5,0))
Expand here to see past versions of V-3.png:
| Version | Author | Date |
|---|---|---|
| 02da57c | zouyuxin | 2019-01-27 |
Results
logliks = c(get_loglik(m_simple_EE), get_loglik(m_mle_EE), get_loglik(m_Vgene_EE_kushal), get_loglik(m_Vgene_EE_nullz))
logliks_EZ = c(get_loglik(m_simple_EZ), get_loglik(m_mle_EZ), get_loglik(m_Vgene_EZ_kushal), get_loglik(m_Vgene_EZ_nullz))
tmp = cbind(logliks, logliks_EZ)
row.names(tmp) = c('Simple', 'MLE', 'Vgene Kushal', 'Vgene null z')
colnames(tmp) = c('EE', 'EZ')
tmp %>% kable() %>% kable_styling()| EE | EZ | |
|---|---|---|
| Simple | 936478.4 | 937254.7 |
| MLE | 940058.8 | 940457.4 |
| Vgene Kushal | 886368.9 | 907004.4 |
| Vgene null z | 1021859.8 | 1036059.9 |
par(mfrow=c(1,2))
barplot(get_estimated_pi(m_simple_EE), las=2, cex.names = 0.7, main = 'Simple EE')
barplot(get_estimated_pi(m_mle_EE), las=2, cex.names = 0.7, main = 'MLE EE')
Expand here to see past versions of plot weights-1.png:
| Version | Author | Date |
|---|---|---|
| 02da57c | zouyuxin | 2019-01-27 |
barplot(get_estimated_pi(m_Vgene_EE_kushal), las=2, cex.names = 0.7, main = 'V gene specific EE Kushal')
barplot(get_estimated_pi(m_Vgene_EE_nullz), las=2, cex.names = 0.7, main = 'V gene specific EE null z')
Expand here to see past versions of plot weights-2.png:
| Version | Author | Date |
|---|---|---|
| 5d17b16 | zouyuxin | 2019-01-29 |
| 02da57c | zouyuxin | 2019-01-27 |
barplot(get_estimated_pi(m_simple_EZ), las=2, cex.names = 0.7, main = 'Simple EZ')
barplot(get_estimated_pi(m_mle_EZ), las=2, cex.names = 0.7, main = 'MLE EZ')
Expand here to see past versions of plot weights-3.png:
| Version | Author | Date |
|---|---|---|
| 5d17b16 | zouyuxin | 2019-01-29 |
barplot(get_estimated_pi(m_Vgene_EZ_kushal), las=2, cex.names = 0.7, main = 'V gene specific EZ Kushal')
barplot(get_estimated_pi(m_Vgene_EZ_nullz), las=2, cex.names = 0.7, main = 'V gene specific EZ null z')
Expand here to see past versions of plot weights-4.png:
| Version | Author | Date |
|---|---|---|
| 5d17b16 | zouyuxin | 2019-01-29 |
Number of significant:
numsig_EE = c(length(get_significant_results(m_simple_EE)),
length(get_significant_results(m_mle_EE)),
length(get_significant_results(m_Vgene_EE_kushal)),
length(get_significant_results(m_Vgene_EE_nullz)))
numsig_EZ = c(length(get_significant_results(m_simple_EZ)),
length(get_significant_results(m_mle_EZ)),
length(get_significant_results(m_Vgene_EZ_kushal)),
length(get_significant_results(m_Vgene_EZ_nullz)))
tmp = cbind(numsig_EE, numsig_EZ)
row.names(tmp) = c('Simple', 'MLE', 'Vgene Kushal', 'Vgene null z')
colnames(tmp) = c('EE', 'EZ')
tmp %>% kable() %>% kable_styling()| EE | EZ | |
|---|---|---|
| Simple | 13068 | 13519 |
| MLE | 12654 | 12986 |
| Vgene Kushal | 15767 | 16066 |
| Vgene null z | 15916 | 15967 |
The gene significant in Simple EZ, not in MLE EZ:
ind = setdiff(get_significant_results(m_simple_EZ), get_significant_results(m_mle_EZ))[9]
stronggene = data.frame(gtex$strong.b[ind,])
colnames(stronggene) = 'EffectSize'
stronggene$Group = row.names(stronggene)
stronggene$se = gtex$strong.s[ind,]
p1 = ggplot(stronggene, aes(y = EffectSize, x = Group)) +
geom_point(show.legend = FALSE, color=gtex.colors) + coord_flip() + ggtitle(paste0(gene.names[ind], ' raw')) + ylim(c(-1,1)) + geom_errorbar(aes(ymin=EffectSize-1.96*se, ymax=EffectSize+1.96*se), width=0.4, show.legend = FALSE, color=gtex.colors) +
theme_bw(base_size=12) + theme(axis.text.y = element_text(colour = gtex.colors, size = 6))
stronggeneSimple = data.frame(m_simple_EZ$result$PosteriorMean[ind,])
colnames(stronggeneSimple) = 'EffectSize'
stronggeneSimple$Group = row.names(stronggeneSimple)
stronggeneSimple$se = m_simple_EZ$result$PosteriorSD[ind,]
p2 = ggplot(stronggeneSimple, aes(y = EffectSize, x = Group)) +
geom_point(show.legend = FALSE, color=gtex.colors) + coord_flip() + ggtitle(paste0(gene.names[ind],' Simple EZ')) + ylim(c(-1,1)) +
geom_errorbar(aes(ymin=EffectSize-1.96*se, ymax=EffectSize+1.96*se), width=0.4, show.legend = FALSE, color=gtex.colors) +
theme_bw(base_size=12) + theme(axis.text.y = element_text(colour = gtex.colors, size = 6))
stronggeneMLE = data.frame(m_mle_EZ$result$PosteriorMean[ind,])
colnames(stronggeneMLE) = 'EffectSize'
stronggeneMLE$Group = row.names(stronggeneMLE)
stronggeneMLE$se = m_mle_EZ$result$PosteriorSD[ind,]
p3 = ggplot(stronggeneMLE, aes(y = EffectSize, x = Group)) +
geom_point(show.legend = FALSE, color=gtex.colors) + ylim(c(-1,1)) + coord_flip() + ggtitle(paste0(gene.names[ind],' MLE EZ')) +
geom_errorbar(aes(ymin=EffectSize-1.96*se, ymax=EffectSize+1.96*se), width=0.4, show.legend = FALSE, color=gtex.colors) +
theme_bw(base_size=12) + theme(axis.text.y = element_text(colour = gtex.colors, size = 6))
stronggeneVgeneKushal = data.frame(m_Vgene_EZ_kushal$result$PosteriorMean[ind,])
colnames(stronggeneVgeneKushal) = 'EffectSize'
stronggeneVgeneKushal$Group = row.names(stronggeneVgeneKushal)
stronggeneVgeneKushal$se = m_Vgene_EZ_kushal$result$PosteriorSD[ind,]
p4 = ggplot(stronggeneVgeneKushal, aes(y = EffectSize, x = Group)) +
geom_point(show.legend = FALSE, color=gtex.colors) + ylim(c(-1,1)) + coord_flip() + ggtitle(paste0(gene.names[ind],' V gene specific Kushal EZ')) +
geom_errorbar(aes(ymin=EffectSize-1.96*se, ymax=EffectSize+1.96*se), width=0.4, show.legend = FALSE, color=gtex.colors) +
theme_bw(base_size=12) + theme(axis.text.y = element_text(colour = gtex.colors, size = 6))
stronggeneVgeneNullZ = data.frame(m_Vgene_EZ_nullz$result$PosteriorMean[ind,])
colnames(stronggeneVgeneNullZ) = 'EffectSize'
stronggeneVgeneNullZ$Group = row.names(stronggeneVgeneNullZ)
stronggeneVgeneNullZ$se = m_Vgene_EZ_nullz$result$PosteriorSD[ind,]
p5 = ggplot(stronggeneVgeneNullZ, aes(y = EffectSize, x = Group)) +
geom_point(show.legend = FALSE, color=gtex.colors) + ylim(c(-1,1)) + coord_flip() + ggtitle(paste0(gene.names[ind],' V gene specific Null EZ')) +
geom_errorbar(aes(ymin=EffectSize-1.96*se, ymax=EffectSize+1.96*se), width=0.4, show.legend = FALSE, color=gtex.colors) +
theme_bw(base_size=12) + theme(axis.text.y = element_text(colour = gtex.colors, size = 6))
grid.arrange(p1, p2, p3, p4, p5, nrow = 2)
Expand here to see past versions of unnamed-chunk-3-1.png:
| Version | Author | Date |
|---|---|---|
| 5d17b16 | zouyuxin | 2019-01-29 |
| 02da57c | zouyuxin | 2019-01-27 |
The gene MCPH1:
ind = 13837
stronggene = data.frame(gtex$strong.b[13837,])
colnames(stronggene) = 'EffectSize'
stronggene$Group = row.names(stronggene)
stronggene$se = gtex$strong.s[13837,]
p1 = ggplot(stronggene, aes(y = EffectSize, x = Group)) +
geom_point(show.legend = FALSE, color=gtex.colors) + coord_flip() + ggtitle('ENSG00000249898 row') + ylim(c(-1.3,1.1)) + geom_errorbar(aes(ymin=EffectSize-1.96*se, ymax=EffectSize+1.96*se), width=0.4, show.legend = FALSE, color=gtex.colors) +
theme_bw(base_size=12) + theme(axis.text.y = element_text(colour = gtex.colors, size = 6))
stronggeneSimple = data.frame(m_simple_EZ$result$PosteriorMean[13837,])
colnames(stronggeneSimple) = 'EffectSize'
stronggeneSimple$Group = row.names(stronggeneSimple)
stronggeneSimple$se = m_simple_EZ$result$PosteriorSD[13837,]
p2 = ggplot(stronggeneSimple, aes(y = EffectSize, x = Group)) +
geom_point(show.legend = FALSE, color=gtex.colors) + ylim(c(-1.3,1.1)) + coord_flip() + ggtitle('ENSG00000249898 Simple EZ') +
geom_errorbar(aes(ymin=EffectSize-1.96*se, ymax=EffectSize+1.96*se), width=0.4, show.legend = FALSE, color=gtex.colors) +
theme_bw(base_size=12) + theme(axis.text.y = element_text(colour = gtex.colors, size = 6))
stronggeneMLE = data.frame(m_mle_EZ$result$PosteriorMean[13837,])
colnames(stronggeneMLE) = 'EffectSize'
stronggeneMLE$Group = row.names(stronggeneMLE)
stronggeneMLE$se = m_mle_EZ$result$PosteriorSD[13837,]
p3 = ggplot(stronggeneMLE, aes(y = EffectSize, x = Group)) +
geom_point(show.legend = FALSE, color=gtex.colors) + coord_flip() + ggtitle('ENSG00000249898 MLE EZ') + ylim(c(-1.3,1.1)) +
geom_errorbar(aes(ymin=EffectSize-1.96*se, ymax=EffectSize+1.96*se), width=0.4, show.legend = FALSE, color=gtex.colors) +
theme_bw(base_size=12) + theme(axis.text.y = element_text(colour = gtex.colors, size = 6))
stronggeneVgeneKushal = data.frame(m_Vgene_EZ_kushal$result$PosteriorMean[ind,])
colnames(stronggeneVgeneKushal) = 'EffectSize'
stronggeneVgeneKushal$Group = row.names(stronggeneVgeneKushal)
stronggeneVgeneKushal$se = m_Vgene_EZ_kushal$result$PosteriorSD[ind,]
p4 = ggplot(stronggeneVgeneKushal, aes(y = EffectSize, x = Group)) +
geom_point(show.legend = FALSE, color=gtex.colors) + ylim(c(-1.3,1.1)) + coord_flip() + ggtitle(paste0(gene.names[ind],' V gene specific Kushal EZ')) +
geom_errorbar(aes(ymin=EffectSize-1.96*se, ymax=EffectSize+1.96*se), width=0.4, show.legend = FALSE, color=gtex.colors) +
theme_bw(base_size=12) + theme(axis.text.y = element_text(colour = gtex.colors, size = 6))
stronggeneVgeneNullZ = data.frame(m_Vgene_EZ_nullz$result$PosteriorMean[ind,])
colnames(stronggeneVgeneNullZ) = 'EffectSize'
stronggeneVgeneNullZ$Group = row.names(stronggeneVgeneNullZ)
stronggeneVgeneNullZ$se = m_Vgene_EZ_nullz$result$PosteriorSD[ind,]
p5 = ggplot(stronggeneVgeneNullZ, aes(y = EffectSize, x = Group)) +
geom_point(show.legend = FALSE, color=gtex.colors) + ylim(c(-1.3,1.1)) + coord_flip() + ggtitle(paste0(gene.names[ind],' V gene specific Null EZ')) +
geom_errorbar(aes(ymin=EffectSize-1.96*se, ymax=EffectSize+1.96*se), width=0.4, show.legend = FALSE, color=gtex.colors) +
theme_bw(base_size=12) + theme(axis.text.y = element_text(colour = gtex.colors, size = 6))
grid.arrange(p1, p2, p3, p4, p5, nrow = 2)
Expand here to see past versions of unnamed-chunk-4-1.png:
| Version | Author | Date |
|---|---|---|
| 5d17b16 | zouyuxin | 2019-01-29 |
| 02da57c | zouyuxin | 2019-01-27 |
The gene significant in V gene specific EZ (null) tissuewide, not in mle EZ:
ind = setdiff(get_significant_results(m_Vgene_EZ_nullz), get_significant_results(m_mle_EZ))[10]
stronggene = data.frame(gtex$strong.b[ind,])
colnames(stronggene) = 'EffectSize'
stronggene$Group = row.names(stronggene)
stronggene$se = gtex$strong.s[ind,]
p1 = ggplot(stronggene, aes(y = EffectSize, x = Group)) +
geom_point(show.legend = FALSE, color=gtex.colors) + coord_flip() + ggtitle(paste0(gene.names[ind],' row')) + ylim(c(-1.3,1.4)) + geom_errorbar(aes(ymin=EffectSize-1.96*se, ymax=EffectSize+1.96*se), width=0.4, show.legend = FALSE, color=gtex.colors) +
theme_bw(base_size=12) + theme(axis.text.y = element_text(colour = gtex.colors, size = 6))
stronggeneSimple = data.frame(m_simple_EZ$result$PosteriorMean[ind,])
colnames(stronggeneSimple) = 'EffectSize'
stronggeneSimple$Group = row.names(stronggeneSimple)
stronggeneSimple$se = m_simple_EZ$result$PosteriorSD[ind,]
p2 = ggplot(stronggeneSimple, aes(y = EffectSize, x = Group)) +
geom_point(show.legend = FALSE, color=gtex.colors) + ylim(c(-1.3,1.4)) + coord_flip() + ggtitle(paste0(gene.names[ind],' Simple EZ')) +
geom_errorbar(aes(ymin=EffectSize-1.96*se, ymax=EffectSize+1.96*se), width=0.4, show.legend = FALSE, color=gtex.colors) +
theme_bw(base_size=12) + theme(axis.text.y = element_text(colour = gtex.colors, size = 6))
stronggeneMLE = data.frame(m_mle_EZ$result$PosteriorMean[ind,])
colnames(stronggeneMLE) = 'EffectSize'
stronggeneMLE$Group = row.names(stronggeneMLE)
stronggeneMLE$se = m_mle_EZ$result$PosteriorSD[ind,]
p3 = ggplot(stronggeneMLE, aes(y = EffectSize, x = Group)) +
geom_point(show.legend = FALSE, color=gtex.colors) + coord_flip() + ggtitle(paste0(gene.names[ind],' MLE EZ')) + ylim(c(-1.3,1.4)) +
geom_errorbar(aes(ymin=EffectSize-1.96*se, ymax=EffectSize+1.96*se), width=0.4, show.legend = FALSE, color=gtex.colors) +
theme_bw(base_size=12) + theme(axis.text.y = element_text(colour = gtex.colors, size = 6))
stronggeneVgeneKushal = data.frame(m_Vgene_EZ_kushal$result$PosteriorMean[ind,])
colnames(stronggeneVgeneKushal) = 'EffectSize'
stronggeneVgeneKushal$Group = row.names(stronggeneVgeneKushal)
stronggeneVgeneKushal$se = m_Vgene_EZ_kushal$result$PosteriorSD[ind,]
p4 = ggplot(stronggeneVgeneKushal, aes(y = EffectSize, x = Group)) +
geom_point(show.legend = FALSE, color=gtex.colors) + ylim(c(-1,1)) + coord_flip() + ggtitle(paste0(gene.names[ind],' V gene specific Kushal EZ')) +
geom_errorbar(aes(ymin=EffectSize-1.96*se, ymax=EffectSize+1.96*se), width=0.4, show.legend = FALSE, color=gtex.colors) +
theme_bw(base_size=12) + theme(axis.text.y = element_text(colour = gtex.colors, size = 6))
stronggeneVgeneNullZ = data.frame(m_Vgene_EZ_nullz$result$PosteriorMean[ind,])
colnames(stronggeneVgeneNullZ) = 'EffectSize'
stronggeneVgeneNullZ$Group = row.names(stronggeneVgeneNullZ)
stronggeneVgeneNullZ$se = m_Vgene_EZ_nullz$result$PosteriorSD[ind,]
p5 = ggplot(stronggeneVgeneNullZ, aes(y = EffectSize, x = Group)) +
geom_point(show.legend = FALSE, color=gtex.colors) + ylim(c(-1.3,1.4)) + coord_flip() + ggtitle(paste0(gene.names[ind],' V gene specific Null EZ')) +
geom_errorbar(aes(ymin=EffectSize-1.96*se, ymax=EffectSize+1.96*se), width=0.4, show.legend = FALSE, color=gtex.colors) +
theme_bw(base_size=12) + theme(axis.text.y = element_text(colour = gtex.colors, size = 6))
grid.arrange(p1, p2, p3, p4, p5, nrow = 2)
Expand here to see past versions of unnamed-chunk-5-1.png:
| Version | Author | Date |
|---|---|---|
| 5d17b16 | zouyuxin | 2019-01-29 |
| 02da57c | zouyuxin | 2019-01-27 |
The pairwise sharing by magnitude
par(mfrow = c(1,2))
clrs=colorRampPalette(rev(c('darkred', 'red','orange','yellow','cadetblue1', 'cyan', 'dodgerblue4', 'blue','darkorchid1','lightgreen','green', 'forestgreen','darkolivegreen')))(200)
x <- get_pairwise_sharing(m_simple_EZ)
colnames(x) <- colnames(get_lfsr(m_simple_EZ))
rownames(x) <- colnames(x)
corrplot::corrplot(x, method='color', type='upper', tl.col="black", tl.srt=45, tl.cex = 0.7, diag = FALSE, col=clrs, cl.lim = c(0,1), title = 'Simple EZ', mar=c(0,0,5,0))
x <- get_pairwise_sharing(m_mle_EZ)
colnames(x) <- colnames(get_lfsr(m_mle_EZ))
rownames(x) <- colnames(x)
corrplot::corrplot(x, method='color', type='upper', tl.col="black", tl.srt=45, tl.cex = 0.7, diag = FALSE, col=clrs, cl.lim = c(0,1), title = 'MLE EZ', mar=c(0,0,5,0))
Expand here to see past versions of unnamed-chunk-6-1.png:
| Version | Author | Date |
|---|---|---|
| 5d17b16 | zouyuxin | 2019-01-29 |
par(mfrow = c(1,2))
clrs=colorRampPalette(rev(c('darkred', 'red','orange','yellow','cadetblue1', 'cyan', 'dodgerblue4', 'blue','darkorchid1','lightgreen','green', 'forestgreen','darkolivegreen')))(200)
x <- get_pairwise_sharing(m_Vgene_EZ_kushal)
colnames(x) <- colnames(get_lfsr(m_Vgene_EZ_kushal))
rownames(x) <- colnames(x)
corrplot::corrplot(x, method='color', type='upper', tl.col="black", tl.srt=45, tl.cex = 0.7, diag = FALSE, col=clrs, cl.lim = c(0,1), title = 'V gene specific Kushal EZ', mar=c(0,0,5,0))
x <- get_pairwise_sharing(m_Vgene_EZ_nullz)
colnames(x) <- colnames(get_lfsr(m_Vgene_EZ_nullz))
rownames(x) <- colnames(x)
corrplot::corrplot(x, method='color', type='upper', tl.col="black", tl.srt=45, tl.cex = 0.7, diag = FALSE, col=clrs, cl.lim = c(0,1), title = 'V gene specific Null EZ', mar=c(0,0,5,0))
Expand here to see past versions of unnamed-chunk-7-1.png:
| Version | Author | Date |
|---|---|---|
| 5d17b16 | zouyuxin | 2019-01-29 |
Session information
sessionInfo()R version 3.5.1 (2018-07-02)
Platform: x86_64-apple-darwin15.6.0 (64-bit)
Running under: macOS 10.14.2
Matrix products: default
BLAS: /Library/Frameworks/R.framework/Versions/3.5/Resources/lib/libRblas.0.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/3.5/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] gridExtra_2.3 ggplot2_3.1.0 kableExtra_1.0.1 knitr_1.20
[5] mashr_0.2.19.0555 ashr_2.2-26
loaded via a namespace (and not attached):
[1] tidyselect_0.2.5 corrplot_0.84 purrr_0.2.5
[4] lattice_0.20-38 colorspace_1.4-0 htmltools_0.3.6
[7] viridisLite_0.3.0 yaml_2.2.0 rlang_0.3.1
[10] R.oo_1.22.0 mixsqp_0.1-93 pillar_1.3.1
[13] withr_2.1.2 glue_1.3.0 R.utils_2.7.0
[16] bindrcpp_0.2.2 bindr_0.1.1 foreach_1.4.4
[19] plyr_1.8.4 stringr_1.3.1 munsell_0.5.0
[22] gtable_0.2.0 workflowr_1.1.1 rvest_0.3.2
[25] R.methodsS3_1.7.1 mvtnorm_1.0-8 codetools_0.2-16
[28] evaluate_0.12 labeling_0.3 pscl_1.5.2
[31] doParallel_1.0.14 parallel_3.5.1 highr_0.7
[34] Rcpp_1.0.0 readr_1.3.1 backports_1.1.3
[37] scales_1.0.0 rmeta_3.0 webshot_0.5.1
[40] truncnorm_1.0-8 abind_1.4-5 hms_0.4.2
[43] digest_0.6.18 stringi_1.2.4 dplyr_0.7.8
[46] grid_3.5.1 rprojroot_1.3-2 tools_3.5.1
[49] magrittr_1.5 lazyeval_0.2.1 tibble_2.0.1
[52] crayon_1.3.4 whisker_0.3-2 pkgconfig_2.0.2
[55] MASS_7.3-51.1 Matrix_1.2-15 SQUAREM_2017.10-1
[58] xml2_1.2.0 assertthat_0.2.0 rmarkdown_1.11
[61] httr_1.4.0 rstudioapi_0.9.0 iterators_1.0.10
[64] R6_2.3.0 git2r_0.24.0 compiler_3.5.1 This reproducible R Markdown analysis was created with workflowr 1.1.1