6 Changing Units
Jupyter interactive version:
6.1 Using bases instead of micrometers - no. cen.
Create some data in millions of bases:
require(idiogramFISH)
# transform data.frames for simplicity
bigdfChrSizeHoloMb <- bigdfChrSizeHolo # included in idiogramFISH
bigdfChrSizeHoloMb$chrSize <- bigdfChrSizeHoloMb$chrSize * 98000000
bigdfMarkPosHoloMb <- bigdfMarkPosHolo
bigdfMarkPosHoloMb$markPos <- bigdfMarkPosHoloMb$markPos * 98000000
bigdfMarkPosHoloMb$markSize<- bigdfMarkPosHoloMb$markSize * 98000000Plotting
In the plot length is shown in Mb
png("bigdfChrSizeHolo2.png", width=700, height=600)
# par(mar=c(1,1,1,1))
par(mar=rep(0,4))
plotIdiograms(dfChrSize=bigdfChrSizeHoloMb, # chr. size data.frame
dfMarkColor=dfMarkColor, # df of mark style
dfMarkPos=bigdfMarkPosHoloMb, # df of mark positions
markDistType="cen", # distance to mark is to its center
squareness=4, # vertices squareness of chr. and marks
distTextChr = .5, # separ. chr. to text
karHeight = 2, # rel. karyotype height
karHeiSpace = 4, # karyotype height including spacing
karSepar=TRUE, # reduce spacing among karyotypes
amoSepar = 1, # depends on karSepar, amount of sep.
chrId="simple", # chr. names not "original"
chrSize=TRUE, # show chr. size under chr.
indexIdTextSize=.9, # font size of chr names and indices
karIndex = FALSE, # do not add karyotype asymmetry index
rulerNumberSize=.9, # font size of ruler
rulerPos = 0, # position of ruler
ruler.tck= -.004, # ruler tick length and orient.
xPosRulerTitle = 3.5, # modifies position of ruler title (Mb)
markLabelSize=.9, # font size of legend
legendWidth = 1.2, # width of legends
xlimLeftMod = 1, # modify left argument of xlim
ylimBotMod=.4 # modify bottom argument of ylim
,chromatids=FALSE # do not show chromatids
,OTUfont = 3 # italics
)
dev.off()
For another example see: https://stackoverflow.com/questions/33727432/how-to-plot-positions-along-a-chromosome-graphic/57153497#57153497
6.2 Using threshold to fix scale
The default value of 35 for threshold may shrink one of the OTUs of this example more than expected. In this case threshold must be bigger.
# fig.width=7, fig.height=7
bigdfOfChrSize3_100Mb<-bigdfOfChrSize3Mb
bigdfOfChrSize3_100Mb$chrSize<-bigdfOfChrSize3Mb$chrSize*33
bigdfOfMarks3_100Mb<-bigdfOfMarks3Mb
bigdfOfMarks3_100Mb$markPos<-bigdfOfMarks3_100Mb$markPos*33
bigdfOfMarks3_100Mb$markSize<-bigdfOfMarks3_100Mb$markSize*33
par(mar=rep(0,4))
plotIdiograms(dfChrSize = bigdfOfChrSize3_100Mb, # chr. size data.frame
dfMarkPos = bigdfOfMarks3_100Mb, # mark position df
chrWidth=.6, # width of chr.
chrSpacing = .6, # space among chr.
karHeight = 3, # kar. height without interspace
karHeiSpace = 5, # vertical size of karyotype including spacer
amoSepar =2, # separ. among kar.
indexIdTextSize=.6, # font size of chr. name and indices
markLabelSize=.7, # font size of mark legends
distTextChr = .65, # separation among chr. names and indices
fixCenBorder = TRUE # use chrColor as border color of cen. or cen. marks
,legendWidth = 1.5 # legend items width
,xPosRulerTitle = 3.5 # position of Mb (title) in ruler
,rulerPos= 0, # ruler position
ruler.tck=-0.005, # ticks of ruler size and orientation
rulerNumberPos =.7, # position of numbers in ruler
rulerNumberSize=.7, # font size of ruler numbers
rulerInterval = 1.5, # ruler interval for micrometeres
rulerIntervalMb = 50, # ruler interval for Mb
ylimBotMod = 0.4, # modify ylim bottom argument
ylimTopMod = 0 # modify ylim top argument
,chromatids=FALSE # do not show chromatids
#### NEW #####
,threshold = 90 # this will allow to not to shrink data greater than 350 Mb
)
6.3 Plot data in micrometers and bases
Info in number of bases can be combined in the same plot with info. in micrometers.
Here the new mark style cenStyle is used to add centromeres to “holocen.” (genomes).
To make the rules fit better, having less excess of length over chr., use ceilingFactor.
#fig.width=10, fig.height=10
# modify data in millions to hundreds of millions of Mb
bigdfOfChrSize3_100Mb<-bigdfOfChrSize3Mb[1:8,]
bigdfOfChrSize3_100Mb$chrSize<-bigdfOfChrSize3_100Mb$chrSize*100
bigdfOfMarks3_100Mb<-bigdfOfMarks3Mb
bigdfOfMarks3_100Mb$markPos <-bigdfOfMarks3_100Mb$markPos *100
bigdfOfMarks3_100Mb$markSize<-bigdfOfMarks3_100Mb$markSize*100
# merge data.frames in micrometers and number of bases
mixedThreeSpChrSize <- plyr::rbind.fill(bigdfOfChrSize[1:8,], bigdfOfChrSize3_100Mb)
# sort by OTU name
mixedThreeSpChrSize <- mixedThreeSpChrSize[order(mixedThreeSpChrSize$OTU),]
# add cenStyle marks to simulate centromeres in karyo. in Mb (holocen.)
# compare rulers
bigdfSimCenMarks<- bigdfOfChrSize3_100Mb
bigdfSimCenMarks$markPos<-bigdfSimCenMarks$chrSize/2
bigdfSimCenMarks$markName<-"sim. cen."
bigdfSimCenMarks$chrSize<-NULL
# merge marks in micrometers and bases
mixedThreeSpMarks <- plyr::rbind.fill(bigdfOfMarks , bigdfOfMarks3_100Mb,bigdfSimCenMarks)
# remove cenStyle mark info.
mixedThreeSpMarks<-mixedThreeSpMarks[which(!( mixedThreeSpMarks$OTU %in% "Species 2 genome" &
mixedThreeSpMarks$chrName %in% c(1,4) &
mixedThreeSpMarks$markName %in% "sim. cen.") ),]
# constric. marks
mixedThreeSpMarks[which(mixedThreeSpMarks$OTU %in% "Species 2 genome" &
mixedThreeSpMarks$chrName %in% c(1,4) ),]$markName<-c("cDAPI","cCMA")
# add arrow mark
mixedThreeSpMarks <- dplyr::bind_rows(mixedThreeSpMarks , mixedThreeSpMarks[nrow(mixedThreeSpMarks),] )
mixedThreeSpMarks[nrow(mixedThreeSpMarks),]$markName<-"S58A"
mixedThreeSpMarks[nrow(mixedThreeSpMarks),]$markPos<-.7e+08
mixedThreeSpMarks[nrow(mixedThreeSpMarks),]$markSize<-.7e+08
dfMarkColorAndStyle<-makedfMarkColorMycolors(unique(mixedThreeSpMarks$markName),
c("red","chartreuse3","dodgerblue","darkgoldenrod1","dodgerblue","darkgoldenrod1","black")
)
# d.f. of marks'styles
dfMarkColorAndStyle$style[5:7]<-"cenStyle"
dfMarkColorAndStyle$markColor[7]<-NA
dfMarkColorAndStyle$style[8]<-"upArrow"
dfMarkColorAndStyle
# markName markColor style
# 1 5S red dots
# 2 45S chartreuse3 square
# 3 DAPI dodgerblue square
# 4 CMA darkgoldenrod1 square
# 5 cDAPI dodgerblue cenStyle
# 6 cCMA darkgoldenrod1 cenStyle
# 7 sim. cen. <NA> cenStyle
# 8 S58A red upArrow
par(mar=rep(0,4))
plotIdiograms(dfChrSize = mixedThreeSpChrSize, # chr. size data.frame
dfMarkPos = mixedThreeSpMarks, # mark position df
dfMarkColor = dfMarkColorAndStyle,
chrWidth=.6, # width of chr.
chrSpacing = .6, # space among chr.
karHeight = 3, # kar. height without interspace
karHeiSpace = 5, # vertical size of karyotype including spacer
amoSepar =2, # separ. among kar.
indexIdTextSize=.6, # font size of chr. name and indices
markLabelSize=.7, # font size of mark legends
distTextChr = .65, # separation among chr. names and indices
lwd.mimicCen = 1.5, # constric. line width
legendWidth = 1.5, # legend items width
fixCenBorder = TRUE, # use chrColor as border color of cen. or cen. marks
xPosRulerTitle = 3.7, # position of Mb (title) in ruler
rulerPos= 0, # ruler position
ruler.tck=-0.005, # ticks of ruler size and orientation
rulerNumberPos =.7, # position of numbers in ruler
rulerNumberSize=.7, # font size of ruler numbers
rulerInterval = 1.5, # ruler interval for micrometeres
rulerIntervalMb = 150, # ruler interval for Mb
ceilingFactor = 1, # affects rounding for ruler max. value
ylimBotMod = 0.4, # modify ylim bottom argument
ylimTopMod = 0 # modify ylim top argument
,holocenNotAsChromatids = TRUE # do not use chromatids in holocen.
,pattern="^c" # regex pattern to remove from mark names
,remSimiMarkLeg = TRUE # remove pseudoduplicate names arising from pattern removal
)
Let’s explore those data.frames
head(mixedThreeSpChrSize,6)| OTU | chrName | shortArmSize | longArmSize | chrSize | |
|---|---|---|---|---|---|
| 1 | Species 1 | 1 | 1.5 | 2.0 | NA |
| 2 | Species 1 | 2 | 2.0 | 2.5 | NA |
| 3 | Species 1 | 3 | 1.0 | 2.0 | NA |
| 9 | Species 1 genome | 1 | NA | NA | 350000000 |
| 10 | Species 1 genome | 2 | NA | NA | 450000000 |
| 11 | Species 1 genome | 3 | NA | NA | 250000000 |
mixedThreeSpMarks[which(mixedThreeSpMarks$OTU %in% c("Species 1","Species 1 genome") ),] | OTU | chrName | markName | chrRegion | markDistCen | markSize | markPos | |
|---|---|---|---|---|---|---|---|
| 1 | Species 1 | 1 | 5S | p | 0.5 | 1 | NA |
| 2 | Species 1 | 1 | 45S | q | 0.5 | 1 | NA |
| 3 | Species 1 | 2 | 45S | p | 1.0 | 1 | NA |
| 4 | Species 1 | 3 | DAPI | q | 1.0 | 1 | NA |
| 13 | Species 1 genome | 1 | 5S | NA | NA | 100000000 | 250000000 |
| 14 | Species 1 genome | 1 | 45S | NA | NA | 100000000 | 50000000 |
| 15 | Species 1 genome | 2 | 45S | NA | NA | 100000000 | 350000000 |
| 16 | Species 1 genome | 3 | DAPI | NA | NA | 100000000 | 0 |
| 25 | Species 1 genome | 1 | sim. cen. | NA | NA | NA | 175000000 |
| 26 | Species 1 genome | 2 | sim. cen. | NA | NA | NA | 225000000 |
| 27 | Species 1 genome | 3 | sim. cen. | NA | NA | NA | 125000000 |
6.4 Use cM as units
Info in cM can be combined in the same plot with info. in micrometers.
To make the rules fit better, having less excess of length over chr., use ceilingFactor.
#fig.width=10, fig.height=10
# merge data.frames in micrometers and cM
bigdfOfChrSize3cM<-bigdfOfChrSize3Mb[1:8,]
bigdfOfChrSize3cM$chrSize<-bigdfOfChrSize3cM$chrSize/100000
mixedThreeSpChrSize2 <- plyr::rbind.fill(bigdfOfChrSize[1:8,], bigdfOfChrSize3cM)
# sort by OTU name
mixedThreeSpChrSize2 <- mixedThreeSpChrSize2[order(mixedThreeSpChrSize2$OTU),]
# create data with cM. markSize col. is not necessary because style is cM
bigdfOfMarks3cM<-bigdfOfMarks3Mb
bigdfOfMarks3cM$markPos<-bigdfOfMarks3Mb$markPos/100000
bigdfOfMarks3cM$markSize<-NA
# As we want only the cM idiograms to be plotted as cM (lines), change mark names
bigdfOfMarks3cM$markName<-paste0("cM",bigdfOfMarks3cM$markName)
# d.f of all marks
mixedThreeSpMarks2 <- plyr::rbind.fill(bigdfOfMarks , bigdfOfMarks3cM)
# create a data.frame with mark characteristics
mixedDfMarkStyle <- makedfMarkColorMycolors(unique(mixedThreeSpMarks2$markName),
c("red","chartreuse3","dodgerblue","darkgoldenrod1")
)
# mark names of cM marks with "cM" style (lines): not dots, not squares
mixedDfMarkStyle[which(mixedDfMarkStyle$markName %in%
grep("cM", mixedDfMarkStyle$markName, value=TRUE) ) ,]$style<-"cM"
par(mar=rep(0,4))
plotIdiograms(dfChrSize = mixedThreeSpChrSize2, # chr. size data.frame
dfMarkPos = mixedThreeSpMarks2, # mark position data.frame
dfMarkColor = mixedDfMarkStyle, # mark style data.frame
chrWidth=.6, # width of chr.
chrSpacing = .7, # space among chr.
specialOTUNames = bigdfOfMarks3cM$OTU, # OTUs in this object will have different ruler units
specialyTitle = "cM", # ruler title for specialOTUNames
specialChrWidth = .2, # modify chr width of OTUs in specialOTUNames
specialChrSpacing = 1.1, # modify chr spacing of OTUs in specialOTUNames
karHeight = 3, # kar. height without interspace
karHeiSpace = 6, # vertical size of karyotype including spacer
amoSepar = 3, # separ. among kar.
chrSize=TRUE, # show chr. size under chr.
indexIdTextSize=.6, # font size of chr. name and indices
distTextChr = .85, # separation among chr. names and indices
protruding = 1, # extension of cM mark type
pattern = "cM", # regex pattern to remove from mark names
markLabelSize=.7 # font size of mark legends
,legendWidth = 2 # legend items width
,fixCenBorder = TRUE # use chrColor as border color of cen. or cen. marks
,lwd.cM = 2 # thickness of cM marks
,holocenNotAsChromatids=TRUE# do not use chromatids in holocen. kar.
,xPosRulerTitle = 3.2 # position of Mb or cM (title) in ruler
,rulerPos= 0, # ruler position
ruler.tck=-0.005, # ticks of ruler size and orientation
rulerNumberPos =.7, # position of numbers in ruler
rulerNumberSize=0.7, # font size of ruler numbers
rulerIntervalcM = 12, # ruler interval for OTU in specialOTUnames and MbThreshold not met
ceilingFactor = 1, # affects max. value in ruler. See also rulerInterval
ylimBotMod = 0.4, # modify ylim bottom argument
ylimTopMod = 0 # modify ylim top argument
)