Go to 1. Monocentrics Vignette
Go to 2. Holocentrics Vignette
Go to 3. Groups Vignette
Go to 4. Phylogeny Vignette
Go to 5. Human Vignette
1 idiogramFISH: Idiograms with Marks and Karyotype Indices
The goal of idiogramFISH is to plot idiograms of several karyotypes having a set of data.frames for chromosome data and optionally marks’ data (plotIdiograms
) (Roa and PC Telles, 2020).
Marks can have square or dot form, its legend (label) can be drawn inline or to the right of karyotypes. It is possible to calculate also chromosome and karyotype indexes (Romero-Zarco, 1986; Watanabe et al., 1999) and classify chromosomes by morphology (Levan et al., 1964; Guerra, 1986).
IdiogramFISH was written in R (R Core Team, 2019) and also uses crayon (Csárdi, 2017), plyr (Wickham, 2011) and dplyr packages (Wickham et al., 2019a). Documentation was written with R-packages roxygen2 (Wickham et al., 2018), usethis (Wickham and Bryan, 2019), bookdown (Xie, 2016), knitr (Xie, 2015), pkgdown (Wickham and Hesselberth, 2019), Rmarkdown (Xie et al., 2018), rvcheck (Yu, 2019a), badger (Yu, 2019b), kableExtra (Zhu, 2019), prettydoc (Qiu, 2019) and RCurl (Temple Lang and CRAN team, 2019). For some vignette figures, packages phytools (Revell, 2012), ggtree (Yu et al., 2018), ggplot2 (Wickham, 2016) and ggpubr (Kassambara, 2019) were used.
2 Installation
Or the devel version
From gitlab with devtools (Wickham et al., 2019b) :
Attention windows users, please install Rtools and git.
Vignettes use a lua filter, so you would need pandoc ver. > 2. rmarkdown::pandoc_version()
# This installs package devtools, necessary for installing the dev version
install.packages("devtools")
url <- "https://gitlab.com/ferroao/idiogramFISH"
# Necessary packages for vignettes:
list.of.packages <- c(
"knitr",
"kableExtra",
"prettydoc",
"rmarkdown",
"RCurl",
"rvcheck",
"badger"
)
new.packages <- list.of.packages[!(list.of.packages %in% installed.packages()[,"Package"])]
if(length(new.packages)) install.packages(new.packages)
4 Need help?
Manual
Documentation
Vignettes:
Online:
Monocentrics
Holocentrics
Groups of chromosomes
Alongside Phylogeny
Human karyotype
Launch vignettes from R for the installed version:
5 Basic examples
How to plot a karyotype:
Define your plotting window size with something like par(pin=c(10,6))
, or with svg()
, png()
, etc. Add chromosome morphology according to Guerra (1986) or (Levan et al., 1964)
# fig.width=10, fig.height=6
library(idiogramFISH)
data(dfOfChrSize) # chromsome data
data(dfMarkColor) # mark general data
data(dfOfMarks2) # mark position data (inc. cen.)
svg("dfOfChrSize.svg",width=12,height=8 )
plotIdiograms(dfChrSize=dfOfChrSize, # data.frame of chr. size
dfMarkColor=dfMarkColor, # d.f of mark style <- Optional
dfMarkPos=dfOfMarks2, # df of mark positions (includes cen. marks)
morpho="Guerra", # chr. morpho. classif. (Guerra, Levan, both, "" ) ver. >= 1.12 only
chrIndex="CI", # cen. pos. (CI, AR, both, "" ) ver. >= 1.12 only
rulerPos=-.9, # position of rulers
ruler.tck=-0.01, # size and orientation of ruler ticks
rulerNumberSize=.8 # font size of rulers
,legendWidth=1 # width of legend items
,distTextChr = .5 # chr. text separation
,xlimLeftMod = 2 # xlim left param.
,ylimBotMod = 0 # modify ylim bottom argument
,ylimTopMod = 0 # modify ylim top argument
,asp=1 # y/x aspect, see ?plot
)
dev.off()
Let’s explore the data.frames for monocentrics:
chrName shortArmSize longArmSize
1 1 3 4
2 2 4 5
3 3 2 3
4 X 1 2
markName markColor style
1 5S red dots
2 45S green square
3 DAPI blue square
4 CMA yellow square
p, q
and w
marks can have empty columns markDistCen
and markSize
since v. 1.9.1 to plot whole arms (p
, q
) and whole chr. w
.
chrName markName chrRegion markSize markDistCen
1 1 5S p 1 0.5
2 1 45S q 1 0.5
3 X 45S p NA NA
4 3 DAPI q 1 1.0
5 1 DAPI cen NA NA
6 X CMA cen NA NA
How to plot a karyotype of holocentrics:
function plotIdiogramsHolo
deprecated after ver. > 1.5.1
library(idiogramFISH)
# load some package data.frames
data(dfChrSizeHolo, dfMarkColor, dfMarkPosHolo)
# plotIdiogramsHolo is deprecated
par(mar = c(0, 0, 0, 0), omi=rep(0,4), oma=rep(0,4) )
# svg("testing.svg",width=14,height=8 )
plotIdiograms(dfChrSize=dfChrSizeHolo, # data.frame of chr. size
dfMarkColor=dfMarkColor, # df of mark style
dfMarkPos=dfMarkPosHolo, # df of mark positions
addOTUName=FALSE, # do not add OTU names
distTextChr = .5, # chr. name distance to chr.
rulerPos=-.9, # position of ruler
rulerNumberPos=.9, # position of numbers of rulers
xlimLeftMod=2, # modify xlim left argument of plot
ylimBotMod=.2 # modify ylim bottom argument of plot
,legendHeight=.5 # height of legend labels
,legendWidth = 1.2 # width of legend labels
,asp=1) # y/x aspect
Let’s explore the data.frames for holocentrics:
chrName chrSize
1 1 3
2 2 4
3 3 2
4 4 5
markName markColor style
1 5S red dots
2 45S green square
3 DAPI blue square
4 CMA yellow square
chrName markName markPos markSize
1 3 5S 1.0 0.5
2 3 DAPI 2.0 0.5
3 1 45S 2.0 0.5
4 2 DAPI 2.0 0.5
5 4 CMA 2.0 0.5
6 4 5S 0.5 0.5
Plotting both mono. and holo.
Available only for ver. > 1.5.1
Merge data.frames with plyr
(Wickham, 2011)
# chromosome data, if only 1 species, column OTU is optional
require(plyr)
dfOfChrSize$OTU <- "Species mono"
dfChrSizeHolo$OTU <- "Species holo"
monoholoCS <- plyr::rbind.fill(dfOfChrSize,dfChrSizeHolo)
dfOfMarks2$OTU <-"Species mono"
dfOfMarks2[which(dfOfMarks2$markName=="5S"),]$markSize<-.7
dfMarkPosHolo$OTU <-"Species holo"
monoholoMarks <- plyr::rbind.fill(dfOfMarks2,dfMarkPosHolo)
library(idiogramFISH)
# load some saved data.frames
# function plotIdiogramsHolo deprecated for ver. > 1.5.1
#svg("testing.svg",width=14,height=10 )
png("monoholoCS.png", width=700, height=500)
par(mar=rep(0,4))
plotIdiograms(dfChrSize = monoholoCS, # data.frame of chr. size
dfMarkColor= dfMarkColor, # df of mark style
dfMarkPos = monoholoMarks,# df of mark positions, includes cen. marks
roundness = 4, # vertices roundness
addOTUName = TRUE, # add OTU names
distTextChr = .5, # separ. among chr. and text and among chr. name and indices
karHeiSpace = 3, # karyotype height inc. spacing
karIndexPos = .2, # move karyotype index
legendHeight= 1, # height of legend labels
legendWidth = 1, # width of legend labels
rulerPos= -0.5, # position of ruler
ruler.tck=-0.02, # size and orientation of ruler ticks
rulerNumberPos=.9, # position of numbers of rulers
xlimLeftMod=1, # modify xlim left argument of plot
xlimRightMod=3, # modify xlim right argument of plot
ylimBotMod= .2 # modify ylim bottom argument of plot
,asp=1 # y x aspect ratio
)
dev.off()
Plotting GISH results
Available only for ver. > 1.8.3
library(idiogramFISH)
# load some saved data.frames
par(mar=rep(0,4))
# svg("allo.svg",width=10,height=9 )
plotIdiograms(dfChrSize = parentalAndHybChrSize, # d.f. of chr. sizes
dfMarkPos = dfAlloParentMarks, # d.f. of marks' positions
cenColor = NULL # cen. color when GISH
,karHeiSpace=5, # karyotype height including spacing
karSepar = FALSE, # equally sized karyotypes
rulerPos=-1, # ruler position
ruler.tck= -0.002, # ruler tick orientation and length
rulerNumberSize=.5 # ruler font size
,legend="" # no legend
,asp=1 # y x aspect ratio
,ylimBotMod = 1 # modifiy ylim bottom argument
,xlimRightMod = 0 # modify xlim right argument
)
5.1 Let’s explore the data.frames for GISH:
parentalAndHybChrSize
OTU chrName shortArmSize longArmSize
Parental 1 1 3.2 4
Parental 1 4 1.5 2
Parental 1 5 4.8 6
Parental 1 6 6.1 7
Parental 2 1 3.2 4
Parental 2 2 4.5 5
Parental 2 3 2.0 3
Allopolyploid 1 3.2 4
Allopolyploid 2 4.5 5
Allopolyploid 3 2.0 3
Allopolyploid 4 1.5 2
Allopolyploid 5 4.8 6
Allopolyploid 6 6.1 7
Use p
for short arm, q
for long arm, and w
for whole chromosome mark.
dfAlloParentMarks
OTU chrName markName chrRegion
Allopolyploid 1 Parental 1 p
Allopolyploid 1 Parental 2 q
Allopolyploid 1 Parental 2 cen
Allopolyploid 2 Parental 2 w
Allopolyploid 3 Parental 2 w
Allopolyploid 4 Parental 1 w
Allopolyploid 5 Parental 1 w
Allopolyploid 6 Parental 1 w
Parental 1 6 Parental 1 w
Parental 1 5 Parental 1 w
Parental 1 1 Parental 1 w
Parental 1 4 Parental 1 w
Parental 2 2 Parental 2 w
Parental 2 1 Parental 2 w
Parental 2 3 Parental 2 w
6 Citation
To cite idiogramFISH in publications, please use:
Roa F, Telles MPC (2020) idiogramFISH: Idiograms with Marks and Karyotype Indices, Universidade Federal de Goiás. Brazil. R-package. version 1.12.1 https://ferroao.gitlab.io/manualidiogramfish/. doi:10.5281/zenodo.3579417
To write citation to file:
References
Guerra M. 1986. Reviewing the chromosome nomenclature of Levan et al. Brazilian Journal of Genetics, 9(4): 741–743
Levan A, Fredga K, Sandberg AA. 1964. Nomenclature for centromeric position on chromosomes Hereditas, 52(2): 201–220. https://doi.org/10.1111/j.1601-5223.1964.tb01953.x. https://onlinelibrary.wiley.com/doi/abs/10.1111/j.1601-5223.1964.tb01953.x
Romero-Zarco C. 1986. A new method for estimating karyotype asymmetry Taxon, 35(3): 526–530. https://onlinelibrary.wiley.com/doi/abs/10.2307/1221906
Watanabe K, Yahara T, Denda T, Kosuge K. 1999. Chromosomal evolution in the genus Brachyscome (Asteraceae, Astereae): statistical tests regarding correlation between changes in karyotype and habit using phylogenetic information Journal of Plant Research, 112: 145–161. http://link.springer.com/article/10.1007/PL00013869
R-packages references
Csárdi G. 2017. Crayon: Colored terminal output. R package version 1.3.4. https://CRAN.R-project.org/package=crayon
Kassambara A. 2019. Ggpubr: ’Ggplot2’ based publication ready plots. R package version 0.2.3. https://CRAN.R-project.org/package=ggpubr
R Core Team. 2019. R: A language and environment for statistical computing R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org/
Revell LJ. 2012. Phytools: An r package for phylogenetic comparative biology (and other things). Methods in Ecology and Evolution, 3: 217–223. https://besjournals.onlinelibrary.wiley.com/doi/10.1111/j.2041-210X.2011.00169.x
Roa F, PC Telles M. 2020. idiogramFISH: Idiograms with marks and karyotype indices Universidade Federal de Goiás, UFG, Goiânia. R-package. version 1.12.1. https://doi.org/10.5281/zenodo.3579417. https://ferroao.gitlab.io/manualidiogramfish/
Wickham H. 2011. The split-apply-combine strategy for data analysis Journal of Statistical Software, 40(1): 1–29. http://www.jstatsoft.org/v40/i01/
Wickham H. 2016. Ggplot2: Elegant graphics for data analysis Springer-Verlag New York. https://ggplot2.tidyverse.org
Wickham H, François R, Henry L, Müller K. 2019a. Dplyr: A grammar of data manipulation. R package version 0.8.3. https://CRAN.R-project.org/package=dplyr
Wickham H, Hester J, Chang W. 2019b. Devtools: Tools to make developing r packages easier. R package version 2.2.1. https://CRAN.R-project.org/package=devtools
Yu G, Lam TT-Y, Zhu H, Guan Y. 2018. Two methods for mapping and visualizing associated data on phylogeny using ggtree. Molecular Biology and Evolution, 35(2): 3041–3043. https://doi.org/10.1093/molbev/msy194. https://academic.oup.com/mbe/article/35/12/3041/5142656
Documentation references
Qiu Y. 2019. Prettydoc: Creating pretty documents from r markdown. R package version 0.3.0. https://CRAN.R-project.org/package=prettydoc
Temple Lang D, CRAN team. 2019. RCurl: General network (http/ftp/...) client interface for r. R package version 1.95-4.12. https://CRAN.R-project.org/package=RCurl
Wickham H, Bryan J. 2019. Usethis: Automate package and project setup. R package version 1.5.1. https://CRAN.R-project.org/package=usethis
Wickham H, Danenberg P, Eugster M. 2018. Roxygen2: In-line documentation for r. R package version 6.1.1. https://CRAN.R-project.org/package=roxygen2
Wickham H, Hesselberth J. 2019. Pkgdown: Make static html documentation for a package. R package version 1.4.1. https://CRAN.R-project.org/package=pkgdown
Xie Y. 2015. Dynamic documents with R and knitr Chapman; Hall/CRC, Boca Raton, Florida. ISBN 978-1498716963. http://yihui.name/knitr/
Xie Y. 2016. Bookdown: Authoring books and technical documents with R markdown Chapman; Hall/CRC, Boca Raton, Florida. ISBN 978-1138700109. https://github.com/rstudio/bookdown
Xie Y, Allaire J, Grolemund G. 2018. R markdown: The definitive guide Chapman; Hall/CRC, Boca Raton, Florida. ISBN 9781138359338. https://bookdown.org/yihui/rmarkdown
Yu G. 2019a. Rvcheck: R/package version check. R package version 0.1.6. https://CRAN.R-project.org/package=rvcheck
Yu G. 2019b. Badger: Badge for r package. R package version 0.0.6. https://CRAN.R-project.org/package=badger
Zhu H. 2019. KableExtra: Construct complex table with ’kable’ and pipe syntax. R package version 1.1.0. https://CRAN.R-project.org/package=kableExtra