8 Groups
Jupyter interactive version:
8.1 monocentrics
Adding the column group
Open your chromosome data - Chr. size - as data.frame and add column
# Example data.frame written in R, use
dfwithgroups<-read.table(text="
chrName shortArmSize longArmSize group
1 1 3 5 1
2 1 3.2 5.5 1
3 1 3.5 4.8 1
4 4 1 3 NA
5 5 3 5 NA
6 X 4 6 NA", header=TRUE, stringsAsFactors=F)| chrName | shortArmSize | longArmSize | group |
|---|---|---|---|
| 1 | 3.0 | 5.0 | 1 |
| 1 | 3.2 | 5.5 | 1 |
| 1 | 3.5 | 4.8 | 1 |
| 4 | 1.0 | 3.0 | NA |
| 5 | 3.0 | 5.0 | NA |
| X | 4.0 | 6.0 | NA |
Heteromorphic pairs
It can be used to plot heteromorphic pairs, see pair 1
dfwithHetero<-read.table(text="
chrName shortArmSize longArmSize group
1 1A 3 5 1
2 1B 3 5 1
4 2 1 3 NA
5 3 3 5 NA
6 4 4 6 NA", header=TRUE, stringsAsFactors=FALSE)| chrName | shortArmSize | longArmSize | group | |
|---|---|---|---|---|
| 1 | 1A | 3 | 5 | 1 |
| 2 | 1B | 3 | 5 | 1 |
| 4 | 2 | 1 | 3 | NA |
| 5 | 3 | 3 | 5 | NA |
| 6 | 4 | 4 | 6 | NA |
dfOfMarksHetero<-read.table(text=
" chrName markName chrRegion markSize markDistCen
1 1A 5S p 1 0.9
2 1B 45S p 1 0.9
3 2 CMA q 1 1.0
4 3 DAPI q 1 1.0", header=TRUE, stringsAsFactors=FALSE)| chrName | markName | chrRegion | markSize | markDistCen |
|---|---|---|---|---|
| 1A | 5S | p | 1 | 0.9 |
| 1B | 45S | p | 1 | 0.9 |
| 2 | CMA | q | 1 | 1.0 |
| 3 | DAPI | q | 1 | 1.0 |
Plot
require(idiogramFISH)
# svg("dfwithHetero.svg",width=13.5,height=8 )
par(mar=rep(0,4))
dfwithHetero$OTU<-"hetero"
dfwithgroups$OTU<-"first"
both<-plyr::rbind.fill(dfwithHetero,dfwithgroups)
dfOfMarksHetero$OTU<-"hetero"
plotIdiograms(dfChrSize=both, # chr. sizes
dfMarkPos=dfOfMarksHetero, # position of marks
karHeiSpace = 4,
chrId="original", # chr. name in df.
chrIndex = "", # do not add chr. indices
morpho="", # do not add chr. morphologies
karIndex = FALSE, # do not add karyotype indices
distTextChr = .8, # distance from text to chr.
markDistType="cen", # mark position measured to center of mark
orderChr = "name", # order chr. by name
ruler=FALSE # do not plot ruler
,ylimBotMod = 1 # modify ylim bottom argument
,legendWidth = 1 # width of legend
); # dev.off()
8.2 Holocentrics
Let’s modify some data.frames to add a group
data("dfChrSizeHolo")
data("dfMarkPosHolo")
dfMarkPosHoloHetero<-dfMarkPosHolo
dfMarkPosHoloHetero$chrName<-c(3,3,"1A",2,"1B","1B")
dfMarkPosHoloHetero$OTU<-"heteromorphic"
dfChrSizeHoloHetero<-dfChrSizeHolo
dfChrSizeHoloHetero$chrName<-c("1A","1B",2,3)
dfChrSizeHoloHetero$OTU<-"heteromorphic"
# Adding the group column
dfChrSizeHoloHetero$group<-c(1,1,NA,NA)Creating a new data.frame for holocentrics
dfChrSizeHoloGroup<-data.frame(OTU="Species name",
chrName=c(1,1,1,1,2,3,4),
chrSize=c(3.1,3.2,3.3,3.4,4,5,6),
group=c(1,1,1,1,NA,NA,NA)
)| OTU | chrName | chrSize | group |
|---|---|---|---|
| Species name | 1 | 3.1 | 1 |
| Species name | 1 | 3.2 | 1 |
| Species name | 1 | 3.3 | 1 |
| Species name | 1 | 3.4 | 1 |
| Species name | 2 | 4.0 | NA |
| Species name | 3 | 5.0 | NA |
| Species name | 4 | 6.0 | NA |
par(mar=rep(0,4))
mergedChrSize<-plyr::rbind.fill(dfChrSizeHoloGroup,dfChrSizeHoloHetero)
plotIdiograms(dfChrSize=mergedChrSize, # data.frame of chr. sizes
dfMarkPos=dfMarkPosHoloHetero,# d.f. of marks
orderChr = "name", # order chr. by name
karIndex = FALSE, # do not add karyotype indices
addOTUName = TRUE, # add OTU name
karHeiSpace = 4, # height of kar. with spacing
ruler=FALSE, # no ruler
xlimLeftMod=-1, # modify left argument of xlim
xlimRightMod=0, # modify right argument of xlim
ylimBotMod=1.3 # modify bottom argument of ylim
,xModifier = 100 # separ. among chromatids
)