1 Load package

visit gitlab for installation instructions https://gitlab.com/ferroao/idiogramFISH

#load package
library(idiogramFISH) 

2 Get your chromosome size data

Initially you have to open your chromosome data as a data.frame.

# Example data.frame written in R, use: (column OTU is optional if only 1 OTU)
mydfChrSizeHolo<-read.table(text=
"            OTU chrName chrSize  
\"Species one\"   1     6.5      
\"Species one\"   2     5.0      
\"Species one\"   3     4.0
\"Species one\"   4     4.0
\"Species one\"   X     3.0    "  ,  header=TRUE, stringsAsFactors=FALSE,fill=TRUE)

setwd("~/folder/subfolder")

mydfChrSize<-read.csv("somefile.csv")

colnames(mydfChrSize)<-c("OTU", "chrName","chrSize")

3 Get marks general data

This data.frame is optional for ver. > 1.0.0

packageVersion("idiogramFISH")

Open or make your mark data as a data.frame. This data.frame has the marks present in all karyotypes with color and style, without position info. If style column is not present it will be filled with square during plotting.

# From scratch:
mydfMarkColor<-read.table(text=
"  markName markColor  style
1       5S       red   dots
2      45S     green square
3     DAPI      blue square
4      CMA    yellow square"  ,  header=TRUE, stringsAsFactors=FALSE,fill=TRUE)

For fixing column names use:

colnames(mydfMarkColor)<-c("markName", "markColor","style") 
# if style column not present it will be filled with "square"

4 Get marks positions data

Open or write your mark positions as a data.frame. This data.frame has the marks present in all karyotypes with position info.

# We will use column OTU if data.frame because chromosome size df has it
mydfMarkPosHolo<-read.table(text=
"             OTU  chrName markName markPos markSize chrRegion
\"Species one\"       4        B      NA       NA        w           # whole chromosome mark, use 'w' in col. chrRegion 
\"Species one\"       3     DAPI     2.0      0.5
\"Species one\"       1      45S     2.0      0.5
\"Species one\"       2     DAPI     2.0      0.5
\"Species one\"       X      CMA     2.0      0.5
\"Species one\"       X       5S     0.5      0.5
\"Species one\"       X       5S     0.5      0.5"  ,  header=TRUE, stringsAsFactors=FALSE,fill=TRUE)

For fixing column names use something like:

colnames(mydfMarkColor)<-c("OTU", "chrName","markName","markPos","markSize") 

5 Plotting

function plotIdiogramsHolo deprecated after ver. > 1.5.1

You can plot without marks (passing only 1st data.frame), but we will use all 4 data.frames created:

# library(idiogramFISH)
svg("mydfChrSizeHolo.svg",width=13.5,height=8 )
# png("mydfChrSizeHolo.png", width=600, height=400)
par(mar=c(1,4,1,1)) # bottom left top right

# function `plotIdiogramsHolo` deprecated after ver. > 1.5.1

plotIdiograms(dfChrSize  = mydfChrSizeHolo,# data.frame of chr. sizes
              dfMarkColor= mydfMarkColor,  # df of mark style
              dfMarkPos  = mydfMarkPosHolo,# df of mark positions
              karHeight = 1.4,             # vertical size of karyotype plus spacing
              addOTUName=FALSE,            # add OTU names
               
              chrWidth = 2,                # width of chromosomes
              chrSpacing = 2,              # space among chromosomes
              indexIdTextSize=1,           # font size of chr. name and indices 
               
              dotRoundCorr=2,              # correction factor for roundness of dots
              legend="aside" ,             # position of legend, not "inline"
              markLabelSize=1,             # font size of legend
               
              rulerNumberSize=1,           # font size of ruler
              rulerPos=-2.2,               # position of ruler
              ruler.tck=-0.01,             # size and orient. of tick of ruler
              rulerNumberPos=.9,           # ruler's number position
 
              xlimLeftMod=2.2,             # modify xlim left argument
              xlimRightMod=10,             # modify xlim right argument
              ylimBotMod=.1                # modify ylim bottom argument
              ,legendWidth=1               # width of legend
              ,legendHeight=0.5            # height of legend item 
              )
dev.off()

For ver. > 1.0.0 there is no need to add dfMarkColor and you can also use the parameter mycolors (optional too), to establish marks’ colors. When using mycolors, colors are assigned depending on the order of marks, i.e.:

unique(dfMarkPosHolo$markName)

par(mar=c(1,4,1,1)) 
# function plotIdiogramsHolo was deprecated
plotIdiograms(dfChrSize = dfChrSizeHolo, # d.f. of chr. size
             dfMarkPos  = dfMarkPosHolo, # d.f. of marks' positions
             mycolors   = c("green","yellow","blue","red"),  # colors for marks
             dotRoundCorr=2.5,           # correction of roundness of vert. and dots
             chrWidth=2.5,               # rel. chr width
             indexIdTextSize=1,          # font size of indexes and chr. name
             legend="aside",             # position of legend to the right
             markLabelSize=1,            # font size of legend
             addOTUName=F,               # add OTU name
             rulerNumberSize=1,          # font size of ruler
             rulerPos=-.7,               # ruler position
             ruler.tck=-0.04,            # ruler ticks size and orient.
             rulerNumberPos=.9,          # position of numbers of ruler
             xlimLeftMod=1,              # modify left xlim 
             xlimRightMod=10,            # modify right xlim
             ylimBotMod=.2               # modify bottom ylim
)

6 Example with several species (OTUs)

To illustrate this, we will load some data.frames from the package

• Chromosome sizes

data(bigdfChrSizeHolo)

• Mark characteristics, does not require OTU

data(dfMarkColor) 

• Mark position

data(bigdfMarkPosHolo)

library(idiogramFISH)

# fig.width=6, fig.height=6
png("bigdfChrSizeHolo.png", width=600, height=600)
par(mar=c(1,1,1,1))

plotIdiograms(dfChrSize=bigdfChrSizeHolo,     # df of chr. sizes
                  dfMarkColor=dfMarkColor,    # df of mark style
                  dfMarkPos=bigdfMarkPosHolo, # df of marks' position
                  
                  MarkDistanceType="cen",     # distance to mark (center of mark)
                  roundness=6,                # vertices roundness of chr. and marks 
                  dotRoundCorr=1,             # correction of dots roundness
                  
                  karHeight = 1,              # rel. karyotype height
                  karHeiSpace = 1.7,          # karyotype height including spacing
                  karSepar=FALSE,             # reduce vertical space among karyotypes 
                  
                  markLabelSpacer = 1         # distance from chr. (right) to legend
                  ,legendWidth = 1            # width of legend labels
                  ,legend="aside"             # type of legend, right side
              
                  ,chrId="simple",            # numbering of chr., not using "original" name
                  chrWidth = 0.5,             # chr. width
                  chrSpacing = 1,             # space among chr.
                  
                  indexIdTextSize=.9,         # font size of chr names and indices
                  markLabelSize=.9,           # font size of legends
                  rulerNumberSize=.9,         # font size of ruler
                  OTUTextSize=1.2,            # font size of OTUs' names
                  
                  xlimRightMod=2,             # modify xlim right argument
                  ylimBotMod=.4               # modify ylim bottom argument
)
dev.off()

7 Using bases instead of micrometers

Create some data in millions of bases:

# transform previous data.frames for simplicity
bigdfChrSizeHoloMb <- bigdfChrSizeHolo
bigdfChrSizeHoloMb$chrSize <- bigdfChrSizeHoloMb$chrSize * 980000
bigdfMarkPosHoloMb <- bigdfMarkPosHolo
bigdfMarkPosHoloMb$markPos <- bigdfMarkPosHoloMb$markPos * 980000
bigdfMarkPosHoloMb$markSize<- bigdfMarkPosHoloMb$markSize * 980000

png("bigdfChrSizeHolo2.png", width=700, height=600)
par(mar=c(1,1,1,1))

plotIdiograms(dfChrSize=bigdfChrSizeHoloMb,  # df of chr. sizes
              dfMarkColor=dfMarkColor,       # df of mark style
              dfMarkPos=bigdfMarkPosHoloMb,  # df of mark positions
              
              MarkDistanceType="cen",        # distance to mark is to its center
              Mb=TRUE, # <- THIS IS NEW      # distances provided are in Mbs
              ylabline = -3.6, # <- NEW      # if Mb=TRUE modifies position of y axis title (Mb)
              roundness=6,                   # vertices roundness of chr. and marks 
              dotRoundCorr=1,                # correction of dots roundness
              
              karHeight = 1,                 # rel. karyotype height
              karHeiSpace = 1.7,             # karyotype height including spacing
              karSepar=TRUE,                 # reduce spacing among karyotypes 
              amoSepar = 3,                  # depends on karSepar, amount of sep.
              
              chrId="simple",                # chr. names not "original"
              chrWidth   = 0.5,              # chr. width
              chrSpacing = 1.0,              # space among chr.
              indexIdTextSize=.9,            # font size of chr names and indices
              karIndex = FALSE,              # do not add karyotype asymmetry index
              
              markLabelSize=.9,              # font size of legend
              rulerNumberSize=.9,            # font size of ruler
              rulerPos = 0,                  # position of ruler
              OTUTextSize=1.2,               # font size of OTU names

              xlimRightMod=2,                # modify right argument of xlim
              xlimLeftMod = 3,               # modify left argument of xlim
              ylimBotMod=.4)                 # modify bottom argument of ylim
dev.off()

8 GISH of holocentric chromosomes

You need the data.frame of chr. sizes, and a d.f. of marks

parentalAndHybHoloChrSize

dfAlloParentMarksHolo

# svg("gish.svg",width=8,height=7 )
# png("mydfChrSize.png", width=600, height=500)
plotIdiograms(dfChrSize = parentalAndHybHoloChrSize,  # d.f. of chr. sizes
              dfMarkPos = dfAlloParentMarksHolo,     # d.f. of marks' positions
              chrColor  = "gray",          # chr. color
              cenColor  = NULL,            # cen. color when GISH

              OTUTextSize = 1,             # font size for OTU names
              dotRoundCorr=2,              # correction of roundness of vert. and dots
              chrWidth=2.5,                # rel. chr. width
              chrSpacing = 2.5,            # rel. horizontal chr. spacing
              karHeiSpace=2,               # karyotype height including spacing
              indexIdTextSize=1,           # font size for chr. indexes and chr. name
                            distTextChr = 0.5,
              markLabelSize=1,             # font size for labels (legend)

              rulerPos=-1.9,               # ruler position
              ruler.tck=-0.02,             # ruler tick orientation and length
              rulerNumberPos=.5,           # rulers' numbers position
              rulerNumberSize=0.7            # ruler font size
              ,legend=""                   # no legend
)

# dev.off()