VEP annotations for variants/neoag

R/neoantigens/analysis/neoag_depletion_hla_count.r

@@ -36,10 +36,10 @@ res <- dbGetQuery(con,q)
 
 res[,"hla_num"] <- as.numeric(res[,"hla_num"])
 
-cor.test(res[,"rneo"],res[,"hla_num"],method="s")		#R = 0.29	P = 5.1e-10
+cor.test(res[,"rneo"],res[,"hla_num"],method="s")		#R = 0.29	P = 2.1e-9
 
 pri <- res[grep("-TP-",res[,1]),]
 rec <- res[grep("-R1-|-R2-|-R3-|-R4-",res[,1]),]
 
-cor.test(pri[,"rneo"],pri[,"hla_num"],method="s")		#R = 0.24	P = 4e-4
-cor.test(rec[,"rneo"],rec[,"hla_num"],method="s")		#R = 0.34	P = 1.3e-7
+cor.test(pri[,"rneo"],pri[,"hla_num"],method="s")		#R = 0.23	P = 5e-4
+cor.test(rec[,"rneo"],rec[,"hla_num"],method="s")		#R = 0.32	P = 5.6-7

R/neoantigens/analysis/neoantigen_depletion_subclonal_selection.r

@@ -36,10 +36,10 @@ for(i in 1:length(subtypes))
 	rec_s <- sub_res[which(sub_res[,"neut2"]=="S"),"nd_b"]
 	rec_n <- sub_res[which(sub_res[,"neut2"]=="N"),"nd_b"]
 
-	wilcox.test(pri_s,pri_n)
-	wilcox.test(rec_s,rec_n)
+	t.test(pri_s,pri_n)
+	t.test(rec_s,rec_n)
 
 	s1 <- c(pri_s,rec_s)
 	n1 <- c(pri_n,rec_n)
-	wilcox.test(s1,n1)	
+	t.test(s1,n1)	
 }

R/neoantigens/figures/ExtendedDataFig_neoag_ccf_shared.r

@@ -9,7 +9,7 @@ library(ggplot2)
 library(RColorBrewer)
 
 con <- DBI::dbConnect(odbc::odbc(), "VerhaakDB")  
-res <- dbGetQuery(con, read_file("/projects/varnf/GLASS/GLASS/sql/neoag_ccf_shared.sql"))
+res <- dbGetQuery(con, read_file("/projects/varnf/GLASS/GLASS/sql/neoag/neoag_ccf_shared.sql"))
 
 ############################################################################################################################################
 ## Plot ladder plot comparing initial and recurrence CCF

R/neoantigens/figures/Fig4_neoag_depletion_clonality_timepoint.r

@@ -31,12 +31,12 @@ tmp <- tmp[order(tmp)]
 rle(tmp)
 
 #Clonal vs subclonal in each tumor
-wilcox.test(res[,"nd_a_c"],res[,"nd_a_s"],paired=TRUE)
-wilcox.test(res[,"nd_b_c"],res[,"nd_b_s"],paired=TRUE)
+t.test(res[,"nd_a_c"],res[,"nd_a_s"],paired=TRUE)		#0.59
+t.test(res[,"nd_b_c"],res[,"nd_b_s"],paired=TRUE)		#0.55
 
 #Clonality status by timepoint
-wilcox.test(res[,"nd_a_c"],res[,"nd_b_c"],paired=TRUE)
-wilcox.test(res[,"nd_a_s"],res[,"nd_b_s"],paired=TRUE)
+t.test(res[,"nd_a_c"],res[,"nd_b_c"],paired=TRUE)		#0.52
+t.test(res[,"nd_a_s"],res[,"nd_b_s"],paired=TRUE)		#0.75
 
 subtypes <- unique(res[,"subtype"])
 pvals <- matrix(0, ncol=4,nrow=3)
@@ -47,12 +47,12 @@ for(i in 1:length(subtypes))
 	sub_res <- res[which(res[,"subtype"]==subtypes[i]),]
 
 	#Clonal vs subclonal in each tumor
-	pvals[i,1] <- wilcox.test(sub_res[,"nd_a_c"],sub_res[,"nd_a_s"],paired=TRUE)$p.value
-	pvals[i,2] <- wilcox.test(sub_res[,"nd_b_c"],sub_res[,"nd_b_s"],paired=TRUE)$p.value
+	pvals[i,1] <- t.test(sub_res[,"nd_a_c"],sub_res[,"nd_a_s"],paired=TRUE)$p.value
+	pvals[i,2] <- t.test(sub_res[,"nd_b_c"],sub_res[,"nd_b_s"],paired=TRUE)$p.value
 
 	#Clonality status by timepoint
-	pvals[i,3] <- wilcox.test(sub_res[,"nd_a_c"],sub_res[,"nd_b_c"],paired=TRUE)$p.value
-	pvals[i,4] <- wilcox.test(sub_res[,"nd_a_s"],sub_res[,"nd_b_s"],paired=TRUE)$p.value	
+	pvals[i,3] <- t.test(sub_res[,"nd_a_c"],sub_res[,"nd_b_c"],paired=TRUE)$p.value
+	pvals[i,4] <- t.test(sub_res[,"nd_a_s"],sub_res[,"nd_b_s"],paired=TRUE)$p.value	
 
 }
 
@@ -65,13 +65,13 @@ clonality <- c(rep("Clonal",nrow(res)*2),rep("Subclonal",nrow(res)*2))
 plot_res <- data.frame(pair,samp,rneo,subtype,timepoint,clonality)
 
 pval <- rep("",nrow(plot_res))
-pval[which(plot_res[,"timepoint"]=="Initial")] <- "P = 0.44"
-pval[which(plot_res[,"timepoint"]=="Recurrent")] <- "P = 0.81"
+pval[which(plot_res[,"timepoint"]=="Initial")] <- "P = 0.59"
+pval[which(plot_res[,"timepoint"]=="Recurrent")] <- "P = 0.55"
 p_text <- cbind(plot_res,pval)
 
 gtsize = 7/(14/5)
 
-pdf("/projects/varnf/GLASS/Figures/resubmission/clonality_ladderplot.pdf",width=3.25,height=2)
+pdf("/projects/varnf/GLASS/Figures/resubmission/Figure4D.pdf",width=3.25,height=2)
 ggplot(plot_res, aes(y = rneo, x = clonality, group=pair, colour=subtype)) + 
 	geom_line(size=0.45,alpha=0.4) +
 	geom_point(size=1,colour="black") +

R/neoantigens/figures/Fig4_neoag_depletion_subtype_timepoint_hm.r

@@ -32,16 +32,19 @@ tmp <- tmp[order(tmp)]
 rle(tmp)
 #Scatterplot of primary vs recurrent correlations with depletion
 cor.test(res[,"nd_a"],res[,"nd_b"])
+cor.test(res[,"nd_a"],res[,"nd_b"])$p.value
+
+summary(aov(c(res[,"nd_a"],res[,"nd_b"])~rep(res[,"subtype"],2))) #P = 0.09
 
 #******************************
 #Figure 4C
 #******************************
 gtsize = 7/(14/5)
-pdf("/projects/varnf/GLASS/Figures/resubmission/depletion_correlation_scatterplot.pdf",width=2,height=2)
+pdf("/projects/varnf/GLASS/Figures/resubmission/Figure4C.pdf",width=2,height=2)
 ggplot(res, aes(x = nd_a, y = nd_b,colour=subtype)) + 
 	geom_point(size=1.5,alpha=0.4) +
 	geom_abline(intercept=0, slope=1, color = "gray50", size=0.5) +
- 	geom_text(aes(x=1.75, y=0, label = "R = 0.72"), size=gtsize, group = NA, colour = "black") +
+ 	geom_text(aes(x=1.75, y=0, label = "R = 0.73"), size=gtsize, group = NA, colour = "black") +
 	labs(x="Observed/expected neoantigens\n(initial)", y="Observed/expected neoantigens\n(recurrent)") +
 	theme_classic() +
 	theme(axis.title=element_text(size=7),
@@ -50,6 +53,20 @@ ggplot(res, aes(x = nd_a, y = nd_b,colour=subtype)) +
 	coord_cartesian(ylim=c(0,2),xlim=c(0,2))
 dev.off()
 
+gtsize = 7/(14/5)
+pdf("/projects/varnf/GLASS/Figures/resubmission/Figure4C_bigger.pdf",width=2,height=2)
+ggplot(res, aes(x = nd_a, y = nd_b,colour=subtype)) + 
+	geom_point(size=1.5,alpha=0.4) +
+	geom_abline(intercept=0, slope=1, color = "gray50", size=0.5) +
+ 	geom_text(aes(x=1.75, y=0, label = "R = 0.73"), size=gtsize, group = NA, colour = "black") +
+	labs(x="Observed/expected neoantigens (initial)", y="Observed/expected neoantigens (recurrent)") +
+	theme_classic() +
+	theme(axis.title=element_text(size=7),
+	axis.text=element_text(colour="black",size=7),
+	legend.position="none") +
+	coord_cartesian(ylim=c(0,2),xlim=c(0,2))
+dev.off()
+
 #Examine differences in the residuals
 difs <- res[,"nd_b"] - res[,"nd_a"]
 wilcox.test(difs[which(res[,"subtype"]=="IDHwt")],difs[which(res[,"subtype"]=="IDHmut-noncodel")])
@@ -61,61 +78,62 @@ wilcox.test(difs[which(res[,"subtype"]!="IDHwt")],difs[which(res[,"subtype"]!="I
 
 
 #Compare primary vs recurrent irrespective of subtype:
-wilcox.test(res[,"nd_a"],res[,"nd_b"],paired=TRUE)		#Initial vs recurrent:	0.49
-wilcox.test(res[,"nd_a"], mu=1)							#Initial: 				0.34
-wilcox.test(res[,"nd_b"], mu=1)							#Recurrent:				0.49
+t.test(res[,"nd_a"],res[,"nd_b"],paired=TRUE)		#Initial vs recurrent:	0.77
+t.test(res[,"nd_a"], mu=1)							#Initial: 				0.47
+t.test(res[,"nd_b"], mu=1)							#Recurrent:				0.59
 
 #Compare subtypes irrespective of timepoint:
 idhwt <- res[which(res[,"subtype"]=="IDHwt"),]
 idhmutnoncodel <- res[which(res[,"subtype"]=="IDHmut-noncodel"),]
 idhmutcodel <- res[which(res[,"subtype"]=="IDHmut-codel"),]
 idhmut <- res[which(res[,"subtype"]!="IDHwt"),]
 
-wilcox.test(c(idhwt[,"nd_a"],idhwt[,"nd_b"]),c(idhmutnoncodel[,"nd_a"],idhmutnoncodel[,"nd_b"]))						#0.02
-wilcox.test(c(idhwt[,"nd_a"],idhwt[,"nd_b"]),c(idhmutcodel[,"nd_a"],idhmutcodel[,"nd_b"]))								#0.63
-wilcox.test(c(idhmutnoncodel[,"nd_a"],idhmutnoncodel[,"nd_b"]),c(idhmutcodel[,"nd_a"],idhmutcodel[,"nd_b"]))			#0.35
-wilcox.test(c(idhwt[,"nd_a"],idhwt[,"nd_b"]),c(idhmut[,"nd_a"],idhmut[,"nd_b"]))										#0.04
+t.test(c(idhwt[,"nd_a"],idhwt[,"nd_b"]),c(idhmutnoncodel[,"nd_a"],idhmutnoncodel[,"nd_b"]))						#0.04
+t.test(c(idhwt[,"nd_a"],idhwt[,"nd_b"]),c(idhmutcodel[,"nd_a"],idhmutcodel[,"nd_b"]))							#0.39
+t.test(c(idhmutnoncodel[,"nd_a"],idhmutnoncodel[,"nd_b"]),c(idhmutcodel[,"nd_a"],idhmutcodel[,"nd_b"]))			#0.61
+t.test(c(idhwt[,"nd_a"],idhwt[,"nd_b"]),c(idhmut[,"nd_a"],idhmut[,"nd_b"]))										#0.04
 
 #Compare primary depletion in each subtype:
 g1 <- res[which(res[,"subtype"]=="IDHwt"),"nd_a"]
 g2 <- res[which(res[,"subtype"]=="IDHmut-noncodel"),"nd_a"]
 g3 <- res[which(res[,"subtype"]=="IDHmut-codel"),"nd_a"]
 
-wilcox.test(g1, mu=1)					#IDHwt:									0.79
-wilcox.test(g2, mu=1)					#IDHmut-noncodel:						0.15
-wilcox.test(g3, mu=1)					#IDHmut-codel:							0.32
-wilcox.test(c(g2,g3), mu=1)				#IDHmut:								0.07
 
-wilcox.test(g1,g2)						#IDHwt vs IDHmut-noncodel:				0.11
-wilcox.test(g1,g3)						#IDHwt vs IDHmut-codel:					0.32
-wilcox.test(g2,g3)						#IDHmut-noncodel vs IDHmut-codel:		0.91
-wilcox.test(g1,c(g2,g3))				#IDHwt vs IDHmut:						0.09
+t.test(g1, mu=1)					#IDHwt:									0.66
+t.test(g2, mu=1)					#IDHmut-noncodel:						0.22
+t.test(g3, mu=1)					#IDHmut-codel:							0.32
+t.test(c(g2,g3), mu=1)				#IDHmut:								0.12
+
+t.test(g1,g2)						#IDHwt vs IDHmut-noncodel:				0.20
+t.test(g1,g3)						#IDHwt vs IDHmut-codel:					0.28
+t.test(g2,g3)						#IDHmut-noncodel vs IDHmut-codel:		0.89
+t.test(g1,c(g2,g3))				#IDHwt vs IDHmut:							0.13
 
 
 #Compare recurrent depletion in each subtype:
 g4 <- res[which(res[,"subtype"]=="IDHwt"),"nd_b"]
 g5 <- res[which(res[,"subtype"]=="IDHmut-noncodel"),"nd_b"]
 g6 <- res[which(res[,"subtype"]=="IDHmut-codel"),"nd_b"]
 
-wilcox.test(g4, mu=1)					#IDHwt:									0.86
-wilcox.test(g5, mu=1)					#IDHmut-noncodel:						0.08
-wilcox.test(g6, mu=1)					#IDHmut-codel:							0.73
-wilcox.test(c(g5,g6), mu=1)				#IDHmut:								0.23
+t.test(g4, mu=1)					#IDHwt:									0.62
+t.test(g5, mu=1)					#IDHmut-noncodel:						0.09
+t.test(g6, mu=1)					#IDHmut-codel:							0.98
+t.test(c(g5,g6), mu=1)				#IDHmut:								0.17
 
-wilcox.test(g4,g5)						#IDHwt vs IDHmut-noncodel:				0.10
-wilcox.test(g4,g6)						#IDHwt vs IDHmut-codel:					0.75
-wilcox.test(g5,g6)						#IDHmut-noncodel vs IDHmut-codel:		0.22
-wilcox.test(g4,c(g5,g6))				#IDHwt vs IDHmut:						0.24
+t.test(g4,g5)						#IDHwt vs IDHmut-noncodel:				0.09
+t.test(g4,g6)						#IDHwt vs IDHmut-codel:					0.88
+t.test(g5,g6)						#IDHmut-noncodel vs IDHmut-codel:		0.41
+t.test(g4,c(g5,g6))				#IDHwt vs IDHmut:							0.16
 
 
 #Compare primary vs recurrent depletion in each subtype
-wilcox.test(g1,g4,paired=TRUE)				#IDHwt:								0.70
-wilcox.test(g2,g5,paired=TRUE)				#IDHmut-noncodel:					0.77
-wilcox.test(g3,g6,paired=TRUE)				#IDHmut-codel:						0.14
-wilcox.test(c(g2,g3),c(g5,g6),paired=TRUE)	#IDHmut:							0.68
+t.test(g1,g4,paired=TRUE)				#IDHwt:								0.92
+t.test(g2,g5,paired=TRUE)				#IDHmut-noncodel:					0.75
+t.test(g3,g6,paired=TRUE)				#IDHmut-codel:						0.09
+t.test(c(g2,g3),c(g5,g6),paired=TRUE)	#IDHmut:							0.77
 
 #Compare hypermutators at recurrence vs non-hypermutators at recurrence
-wilcox.test(res[which(res[,"hm_b"]==1),"nd_b"],res[which(res[,"hm_b"]==0),"nd_b"])	#0.67
+t.test(res[which(res[,"hm_b"]==1),"nd_b"],res[which(res[,"hm_b"]==0),"nd_b"])	#0.54
 
 
 #Subtype and timepoint figures
@@ -144,19 +162,19 @@ dev.off()
 #******************************
 #Figure 4B
 #******************************
-wilcox.test(plot_res[which(plot_res[,"subtype"]=="IDHwt"),"rneo"],plot_res[which(plot_res[,"subtype"]=="IDHmut-noncodel"),"rneo"]) #0.67
-pdf("/projects/varnf/GLASS/Figures/resubmission/depletion_subtype_box.pdf",width=3.25,height=2)
+t.test(plot_res[which(plot_res[,"subtype"]=="IDHwt"),"rneo"],plot_res[which(plot_res[,"subtype"]=="IDHmut-noncodel"),"rneo"]) #0.04
+pdf("/projects/varnf/GLASS/Figures/resubmission/Figure4B.pdf",width=3.75,height=2)
 ggplot(plot_res, aes(y = rneo, x = subtype,colour=subtype)) + 
 	geom_boxplot(lwd=0.5,outlier.size=0.1,fatten=2,colour="black",fill="white") +
 	geom_jitter(size=1,width=0.05) +	
 	labs(y="Observed/expected neoantigens") +
- 	geom_text(aes(x=2.5, y=1.8, label = "P = 0.02"), size=gtsize, group = NA, color = "black") +
+ 	geom_text(aes(x=2.5, y=1.8, label = "P = 0.04"), size=gtsize, group = NA, color = "black") +
 	theme_classic() + 
 	theme(strip.text.x = element_text(size=7),strip.background = element_blank(),
 	axis.title.x=element_text(size=7),axis.title.y=element_blank(),
 	axis.text=element_text(colour="black",size=7), axis.text.x=element_text(hjust=0.5,size=7),
 	legend.position="none") + 
-	coord_flip()
+	coord_flip(ylim=c(0,2.5))
 dev.off()
 
 #Old figure, replaced with correlation plot
@@ -188,15 +206,15 @@ rneo <- res[,"nd_b"]
 subtype <- res[,"subtype"]
 hm <- as.factor(res[,"hm_b"])
 plot_res_hm <- data.frame(samp,rneo,subtype,hm)
-wilcox.test(plot_res_hm[which(plot_res_hm[,"hm"]==1),"rneo"],plot_res_hm[which(plot_res_hm[,"hm"]==0),"rneo"]) #0.67
+t.test(plot_res_hm[which(plot_res_hm[,"hm"]==1),"rneo"],plot_res_hm[which(plot_res_hm[,"hm"]==0),"rneo"]) #0.54
 
 
 pdf("/projects/varnf/GLASS/Figures/resubmission/EDF12_depletion_hypermutator_recur_box.pdf",width=2,height=2)
 ggplot(plot_res_hm, aes(y = rneo, x = hm, colour=hm)) + 
 	geom_boxplot(lwd=0.5,outlier.size=0.1,fatten=2,colour="black",fill="white") +
 	geom_jitter(size=1,width=0.05) +	
 	labs(y="Observed/expected neoantigens") +
- 	geom_text(aes(x=1.5, y=2, label = "P = 0.67"), size=gtsize, group = NA, color = "black") +
+ 	geom_text(aes(x=1.5, y=2, label = "P = 0.54"), size=gtsize, group = NA, color = "black") +
 	scale_colour_manual(values=c("royalblue4","tomato3")) +
 	theme_classic() +
 	theme(strip.text.x = element_text(size=7),strip.background = element_blank(),
@@ -215,15 +233,15 @@ hm <-  c(tmp[,"hm_a"],tmp[,"hm_b"])
 timepoint <- c(rep("Initial",nrow(tmp)),rep("Recurrent",nrow(tmp)))
 plot_res_hmtp <- data.frame(pair,samp,rneo,hm,subtype,timepoint)
 
-wilcox.test(plot_res_hmtp[which(plot_res_hmtp[,"timepoint"]=="Initial"),"rneo"],plot_res_hmtp[which(plot_res_hmtp[,"timepoint"]=="Recurrent"),"rneo"],paired=TRUE)
+t.test(plot_res_hmtp[which(plot_res_hmtp[,"timepoint"]=="Initial"),"rneo"],plot_res_hmtp[which(plot_res_hmtp[,"timepoint"]=="Recurrent"),"rneo"],paired=TRUE) #P = 0.32
 #P = 0.24
 
 pdf("/projects/varnf/GLASS/Figures/resubmission/EDF12_depletion_hypermutator_timepoint_box.pdf",width=2,height=2)
 ggplot(plot_res_hmtp, aes(y = rneo, x = timepoint, group=pair, colour=subtype)) + 
 	geom_line(size=0.45) +
 	geom_point(size=1,colour="black") +
 	labs(y="Observed/expected neoantigens") +
- 	geom_text(aes(x=1.5, y=2, label = "P = 0.24"), size=gtsize, group = NA, color = "black") +
+ 	geom_text(aes(x=1.5, y=2, label = "P = 0.32"), size=gtsize, group = NA, color = "black") +
 	theme_classic() +
 	theme(strip.text.x = element_text(size=7),strip.background = element_blank(),
 	axis.title.y=element_text(size=7),axis.title.x=element_blank(),

R/neoantigens/figures/Fig4_neoag_nonsyn_rate.r

@@ -36,7 +36,7 @@ tmp <- tmp[order(tmp)]
 rle(tmp)
 
 #get average proportion of mutations giving rise to neoantigens
-mean(c(neo[,"prop_immunogenic_a"],neo[,"prop_immunogenic_b"]))		#43%
+mean(c(neo[,"prop_immunogenic_a"],neo[,"prop_immunogenic_b"]))		#42%
 
 #get correlation between mutation and neoantigen load
 cor(c(neo[,"neoag_count_a"],neo[,"neoag_count_b"]),c(neo[,"mt_count_a"],neo[,"mt_count_b"]),method="s")	#0.89
@@ -69,17 +69,17 @@ g4 <- res[which(res[,"timepoint"]=="Recurrent" & res[,"subtype"] == "IDHmut-code
 g5 <- res[which(res[,"timepoint"]=="Recurrent" & res[,"subtype"] == "IDHmut-noncodel"),"prop"]
 g6 <- res[which(res[,"timepoint"]=="Recurrent" & res[,"subtype"] == "IDHwt"),"prop"]
 
-wilcox.test(g1,g4)		#0.52
-wilcox.test(g2,g5)		#0.64
-wilcox.test(g3,g6)		#0.92
+wilcox.test(g1,g4)		#0.35
+wilcox.test(g2,g5)		#0.82
+wilcox.test(g3,g6)		#0.90
 
-wilcox.test(g1,g2)		#0.27
-wilcox.test(g1,g3)		#0.41
-wilcox.test(g2,g3)		#0.56
+wilcox.test(g1,g2)		#0.19
+wilcox.test(g1,g3)		#0.38
+wilcox.test(g2,g3)		#0.61
 
-wilcox.test(g4,g5)		#0.45
-wilcox.test(g4,g6)		#0.97
-wilcox.test(g5,g6)		#0.21
+wilcox.test(g4,g5)		#0.66
+wilcox.test(g4,g6)		#0.92
+wilcox.test(g5,g6)		#0.26
 
 #Plot A
 plot_res <- data.frame(c(prop_pri,prop_rec),

R/neoantigens/upload/combine_neoag_tables.r

@@ -1,6 +1,6 @@
 #This script takes the output of the Snakemake pvacseq module for each patient and combines it into one large table to upload to the db (analysis.neoantigens_by_patient table)
 #Additionally generates a .txt file for backup
-#First it labels each sample's table with the proper case barcode, then it combines the labelled tables into one large table and uplaods 
+#First it labels each sample's table with the proper case barcode, then it combines the labelled tables into one large table and uploads 
 #-----------------------------------------------------
 library(DBI)
 library(odbc)

Snakefile

@@ -59,8 +59,8 @@ include: "snakemake/mutect2-post.smk"
 # include: "snakemake/manta.smk"
 #include: "snakemake/cnv.smk"
 #include: "snakemake/sequenza.smk"
-include: "snakemake/optitype.smk"
-include: "snakemake/pvacseq.smk"
+#include: "snakemake/optitype.smk"
+#include: "snakemake/pvacseq.smk"
 #include: "snakemake/cnv-post.smk"
 include: "snakemake/titan.smk"
 include: "snakemake/pyclone.smk"
@@ -178,6 +178,7 @@ rule ssmutect2:
 rule m2db:
     input:
         #"results/mutect2/consensusvcf/consensus.normalized.sorted.funcotated.tsv",
+        "results/mutect2/consensusvcf/consensus.normalized.sorted.vep.vcf",
         expand("results/mutect2/geno2db/{case_barcode}.info.tsv", case_barcode = manifest.getSelectedCases()),
         expand("results/mutect2/geno2db/{case_barcode}.geno.tsv", case_barcode = manifest.getSelectedCases())
 

conf/cluster.json

@@ -271,7 +271,25 @@
         "name" : "{rule}",
         "stdout" : "logs/drmaa/{rule}.out",
         "stderr" : "logs/drmaa/{rule}.err"
+    },    
+	"annotate_vep" :
+    {
+        "ppn" : 12,
+        "mem" : 72,
+        "walltime" : "72:00:00",
+        "name" : "{rule}",
+        "stdout" : "logs/drmaa/{rule}.out",
+        "stderr" : "logs/drmaa/{rule}.err"
     },
+    "vep2db" :
+    {
+        "ppn" : 2,
+        "mem" : 12,
+        "walltime" : "72:00:00",
+        "name" : "{rule}",
+        "stdout" : "logs/drmaa/{rule}.out",
+        "stderr" : "logs/drmaa/{rule}.err"
+	},
     "genotypesample" :
     {
         "ppn" : 1,

conf/config.yaml

@@ -130,11 +130,11 @@ hla_ref:   "/projects/verhaak-lab/verhaak_ref/hla_ref/optitype/hla_reference_dna
 vcf2maf:          "/projects/verhaak-lab/mskcc-vcf2maf-747a1bb/vcf2maf.pl"
 
 ## VEP installation
-veppath:          "/projects/barthf/opt/ensembl-vep"
+veppath:          "/projects/varnf/SofWar/ensembl-vep"        #"/projects/barthf/opt/ensembl-vep"
 
 ## VEP cache directory
-vepdata:          "/projects/verhaak-lab/verhaak_ref/vep" #"/projects/barthf/opt/.vep"
-vepplugindata:    "/projects/varnf/SofWar/ensembl-vep/reference/"   #need to reconcile
+#vepdata:          "/projects/verhaak-lab/verhaak_ref/vep" #"/projects/barthf/opt/.vep"
+vepdata:    "/projects/varnf/SofWar/ensembl-vep/reference/"   #need to reconcile
 
 ## VEP plugin directory
 vepplugins:       "/projects/varnf/SofWar/VEP_plugins/"