Recent changes to ClusterInvasion

ClusterInvasion modified by Robert Kofler

Robert Kofler — Sat, 28 Apr 2018 03:59:43 -0000

--- v9
+++ v10
@@ -6,7 +6,7 @@
 We simulate 4 chromosomes with a size of 1Mb. We use a recombination rate of 3cM/Mb for each. Every chromosmome has a piRNA cluster of size 30kb at the beginning. The transposition rate is 0.5 and the population size is 1000. We simulate the invasion for 10000 generations. The starting populatio has 300 insertions randomly distributed. We use 50 replicates and record the status of the invasion all 20 generations.

 ~~~~~~
-java -jar invade.jar cluster --genome "mb:1,1,1,1" --rr "cm_mb:3,3,3,3" --cluster "kb:30,30,30,30" --u 0.05 --N 1000 --gen 10000 --basepop "seg:300" --rep 50 --silent --steps 20
+java -jar invade.jar cluster --genome "mb:1,1,1,1" --rr "cm_mb:3,3,3,3" --cluster "kb:30,30,30,30" --u 0.05 --N 1000 --gen 10000 --basepop "seg:300" --rep 50 --silent --steps 20 > invasion.txt
 ~~~~~~

 ## Basic invasion visualized with ggplot2
@@ -44,7 +44,7 @@
 [[img src=invasion.png]]

 ## Add a mean to the graph
-In the previous example we have the invasion for 50 replicates. It could be helpful to add a mean value to the graph.
+The previous example shows TE  invasions for 50 replicates. It could be helpful to add a mean value to the graph.

 ### R-code
 ~~~~~~
@@ -83,7 +83,9 @@
 ### results
 [[img src=invasion-mean.png]]

-## Indicate whether at least one insertion in piRNA cluster got fixed
+## Indicate whether a piRNA cluster insertion got fixed
+
+Fixation of a piRNA cluster insertion is an important event, as this marks the death of the TE. It can not be active anymore in any individual. 

 ### R-code

ClusterInvasion modified by Robert Kofler

Robert Kofler — Fri, 27 Apr 2018 18:57:36 -0000

--- v8
+++ v9
@@ -121,6 +121,8 @@

 This is also interesting biologically! The fluctuation stops with a fixed cluster insertion

+Ha cool idea, add different color for first pirna cluster insertion, than for second etc etc etc
+
 [[img src=invasion-clufix.png]]

 ## Indicate the average population frequency

ClusterInvasion modified by Robert Kofler

Robert Kofler — Fri, 27 Apr 2018 15:51:21 -0000

--- v7
+++ v8
@@ -80,9 +80,48 @@
 plot(g)
 ~~~~~~

+### results
+[[img src=invasion-mean.png]]
+
+## Indicate whether at least one insertion in piRNA cluster got fixed
+
+### R-code
+
+~~~~~~
+library(ggplot2)
+library(RColorBrewer)
+library(plyr)
+theme_set(theme_bw())
+
+b<-brewer.pal(12,"Paired")
+cbbPalette<-c("#1f78b4","#e41a1c")
+
+t<-read.table("/Users/robertkofler/dev/invade/out/artifacts/invade_jar/invasion.txt")
+names(t)<-c("replicate","generation","tmp","fwt","w","diploidtes","popfreq","fixed","tmp2",
+            "fwcli","cluins","popfreqcluins","fixedcluins","tmp3","diedout","meannovel","sites","clusites","stdevins","stdevcluins","popsize")
+
+t$clufix=0
+t[t$fixedcluins>0,]$clufix=1
+t$clufix<-as.factor(t$clufix)
+
+g<-ggplot()+theme(legend.position="none")+
+  geom_line(data=t,aes(x=generation,y=diploidtes,group=replicate,color=clufix),alpha=1,size=0.7)+
+  ylab("insertions per diploid individual")+xlab("generations")+scale_colour_manual(values=cbbPalette)
+
+pdf(file="/Users/robertkofler/dev/invade/out/artifacts/invade_jar/invasion-clufix.pdf",width=8,height=5)
+plot(g)
+dev.off()
+~~~~~~
+

 ### results
-[[img src=invasion-mean.png]]
+
+blue: no cluster insertion is fixed
+red: at least one cluster insertion is fixed
+
+This is also interesting biologically! The fluctuation stops with a fixed cluster insertion
+
+[[img src=invasion-clufix.png]]

 ## Indicate the average population frequency

ClusterInvasion modified by Robert Kofler

Robert Kofler — Fri, 27 Apr 2018 15:43:26 -0000

--- v6
+++ v7
@@ -110,3 +110,7 @@
 plot(g)
 dev.off()
 ~~~~
+### results
+blue indicates a low population frequency and red that the TEs are mostly fixed
+
+[[img src=invasion-popfreq.png]]

ClusterInvasion modified by Robert Kofler

Robert Kofler — Fri, 27 Apr 2018 15:41:04 -0000

--- v5
+++ v6
@@ -83,3 +83,30 @@

 ### results
 [[img src=invasion-mean.png]]
+
+## Indicate the average population frequency
+
+### R code
+
+~~~~
+library(ggplot2)
+library(RColorBrewer)
+library(plyr)
+theme_set(theme_bw())
+
+b<-brewer.pal(12,"Paired")
+cbbPalette<-c("grey50")
+
+t<-read.table("/Users/robertkofler/dev/invade/out/artifacts/invade_jar/invasion.txt")
+names(t)<-c("replicate","generation","tmp","fwt","w","diploidtes","popfreq","fixed","tmp2",
+            "fwcli","cluins","popfreqcluins","fixedcluins","tmp3","diedout","meannovel","sites","clusites","stdevins","stdevcluins","popsize")
+
+g<-ggplot()+theme(legend.position="none")+
+  geom_line(data=t,aes(x=generation,y=diploidtes,group=replicate,color=popfreq),alpha=1,size=0.7)+
+  ylab("insertions per diploid individual")+xlab("generations")+
+ scale_color_gradient(low = "#1f78b4", high = "#e41a1c")
+
+pdf(file="/Users/robertkofler/dev/invade/out/artifacts/invade_jar/invasion-popfreq.pdf",width=8,height=5)
+plot(g)
+dev.off()
+~~~~

ClusterInvasion modified by Robert Kofler

Robert Kofler — Fri, 27 Apr 2018 15:24:32 -0000

--- v4
+++ v5
@@ -46,4 +46,40 @@
 ## Add a mean to the graph
 In the previous example we have the invasion for 50 replicates. It could be helpful to add a mean value to the graph.

-### R-code with mean
+### R-code
+~~~~~~
+library(ggplot2)
+library(RColorBrewer)
+library(plyr)
+theme_set(theme_bw())
+
+b<-brewer.pal(12,"Paired")
+cbbPalette<-c("grey50")
+
+# code used
+# java -jar invade.jar cluster --genome "mb:1,1,1,1" --rr "cm_mb:3,3,3,3" --cluster "kb:30,30,30,30" --u 0.05 --N 1000 --gen 10000 --basepop "seg:300" --rep 50 --silent --steps 20 > invasion.txt
+t<-read.table("/Users/robertkofler/dev/invade/out/artifacts/invade_jar/invasion.txt")
+names(t)<-c("replicate","generation","tmp","fwt","w","diploidtes","popfreq","fixed","tmp2",
+            "fwcli","cluins","popfreqcluins","fixedcluins","tmp3","diedout","meannovel","sites","clusites","stdevins","stdevcluins","popsize")
+
+
+ci<- ddply(.data=t, 
+           .(generation),
+           summarize, 
+           mean= mean(diploidtes),
+           var=sqrt(var(diploidtes))) 
+
+g<-ggplot()+theme(legend.position="none")+
+  scale_colour_manual(values=cbbPalette)+
+  geom_line(data=t,aes(x=generation,y=diploidtes,group=replicate),alpha=0.15,size=0.3)+
+  ylab("insertions per diploid individual")+xlab("generations")+
+  geom_line(data=ci,aes(x=generation,y=mean),size=1)
+
+
+pdf(file="/Users/robertkofler/dev/invade/out/artifacts/invade_jar/invasion-mean.pdf",width=8,height=5)
+plot(g)
+~~~~~~
+
+
+### results
+[[img src=invasion-mean.png]]

ClusterInvasion modified by Robert Kofler

Robert Kofler — Fri, 27 Apr 2018 15:16:42 -0000

--- v3
+++ v4
@@ -1,14 +1,49 @@
 ## TE abundance during an invasion (with piRNA clusters)

-##Run the simulations eg:
+We want to see TE abundance during an invasion, when piRNA clusters act to stop TE activity. We will use fifty replictes.
+
+#Run the simulations eg:
+We simulate 4 chromosomes with a size of 1Mb. We use a recombination rate of 3cM/Mb for each. Every chromosmome has a piRNA cluster of size 30kb at the beginning. The transposition rate is 0.5 and the population size is 1000. We simulate the invasion for 10000 generations. The starting populatio has 300 insertions randomly distributed. We use 50 replicates and record the status of the invasion all 20 generations.

 ~~~~~~
 java -jar invade.jar cluster --genome "mb:1,1,1,1" --rr "cm_mb:3,3,3,3" --cluster "kb:30,30,30,30" --u 0.05 --N 1000 --gen 10000 --basepop "seg:300" --rep 50 --silent --steps 20
 ~~~~~~

-##Visualize with ggplot2
+## Basic invasion visualized with ggplot2
+
+~~~~~~
+library(ggplot2)
+library(RColorBrewer)
+theme_set(theme_bw())
+
+b<-brewer.pal(12,"Paired")
+cbbPalette<-c("grey50")
+
+# code used
+# java -jar invade.jar cluster --genome "mb:1,1,1,1" --rr "cm_mb:3,3,3,3" --cluster "kb:30,30,30,30" --u 0.05 --N 1000 --gen 10000 --basepop "seg:300" --rep 50 --silent --steps 20 > invasion.txt
+t<-read.table("/Users/robertkofler/dev/invade/out/artifacts/invade_jar/invasion.txt")
+names(t)<-c("replicate","generation","tmp","fwt","w","diploidtes","popfreq","fixed","tmp2",
+            "fwcli","cluins","popfreqcluins","fixedcluins","tmp3","diedout","meannovel","sites","clusites","stdevins","stdevcluins","popsize")
+
+g<-ggplot()+theme(legend.position="none")+
+  scale_colour_manual(values=cbbPalette)+
+  geom_line(data=t,aes(x=generation,y=diploidtes,group=replicate),alpha=0.5,size=0.3)+
+  ylab("insertions per diploid individual")+xlab("generations")

-## Results
+pdf(file="/Users/robertkofler/dev/invade/out/artifacts/invade_jar/invasion.pdf",width=8,height=5)
+plot(g)
+dev.off()
+~~~~~~
+
+
+
+### Results
+Following we see a TE invasion when piRNA clusters account for 3% of the genome (as in Drosophila). On the y-axis we have the average number of insertions per diploid individual.

 [[img src=invasion.png]]
+
+## Add a mean to the graph
+In the previous example we have the invasion for 50 replicates. It could be helpful to add a mean value to the graph.
+
+### R-code with mean

ClusterInvasion modified by Robert Kofler

Robert Kofler — Fri, 27 Apr 2018 15:08:15 -0000

--- v2
+++ v3
@@ -1,9 +1,14 @@
-## Basic visualization of the TE abundance during the invasion
+## TE abundance during an invasion (with piRNA clusters)

-Run the simulations eg:
+##Run the simulations eg:

 ~~~~~~
 java -jar invade.jar cluster --genome "mb:1,1,1,1" --rr "cm_mb:3,3,3,3" --cluster "kb:30,30,30,30" --u 0.05 --N 1000 --gen 10000 --basepop "seg:300" --rep 50 --silent --steps 20
 ~~~~~~

-Visualize with ggplot2
+##Visualize with ggplot2
+
+
+## Results
+
+[[img src=invasion.png]]

ClusterInvasion modified by Robert Kofler

Robert Kofler — Fri, 27 Apr 2018 10:39:15 -0000

--- v1
+++ v2
@@ -5,3 +5,5 @@
 ~~~~~~
 java -jar invade.jar cluster --genome "mb:1,1,1,1" --rr "cm_mb:3,3,3,3" --cluster "kb:30,30,30,30" --u 0.05 --N 1000 --gen 10000 --basepop "seg:300" --rep 50 --silent --steps 20
 ~~~~~~
+
+Visualize with ggplot2

ClusterInvasion modified by Robert Kofler

Robert Kofler — Fri, 27 Apr 2018 10:38:02 -0000

Basic visualization of the TE abundance during the invasion

Run the simulations eg:

java -jar invade.jar cluster --genome "mb:1,1,1,1" --rr "cm_mb:3,3,3,3" --cluster "kb:30,30,30,30" --u 0.05 --N 1000 --gen 10000 --basepop "seg:300" --rep 50 --silent --steps 20