kpAxis plot the axis at the first or last position of the chromosomes. Therefore, when using zoom, axis are not visible. Change the code to plot them at the begining/end of the plot.region. This should accomodate all situations.

Dear,
There is error when I use the karyoploteR for custom genome as follows.

custom.genome <- toGRanges(data.frame(chr=c("Pn5"), start=c(1), end=c(50000)))
kp <- plotKaryotype(genome = custom.genome)

library(GenomicFeatures)
txdb <- makeTxDbFromGFF(file = "C:/Users/hope/Desktop/sample.GTF", format = "gtf")
all_genes <- genes(txdb)
all_genes

GRanges object with 5 ranges and 1 metadata column:
     seqnames      ranges strand |     gene_id
        <Rle>   <IRanges>  <Rle> | <character>
  g1      Pn5   1813-2068      + |          g1
  g2      Pn5 10171-10521      + |          g2
  g3      Pn5 12320-13084      + |          g3
  g4      Pn5 13385-13624      + |          g4
  g5      Pn5 13785-14425      + |          g5
  -------
  seqinfo: 1 sequence from an unspecified genome; no seqlengths

The error are coming when I use kpPlotDensity to show Gene Density and display gene use kpPlotMarkers function.

> kpPlotDensity(kp, data=all_genes,window.size = 50000)
Error in graphics::polygon(x = c(x.chr, rev(x.chr)), y = c(y0.chr, rev(y1.chr)),  : 
  plot.new has not been called yet

> kpPlotMarkers(kp, data=all_genes, labels=all_genes$gene_id)
Error in strwidth(rep("M", length(chr.labels)), units = "user") : 
  plot.new has not been called yet

Any help is much appreciated.
Thanks.

Is there a way to combine, say 4 karyoploteR plots, into one plot?
I tired par() and grid.arrange(), but without success.

I want to install the R package KaryoploteR while the R version is too lower ,Did there any method can solve it ,since there is so many R package in my R that I don't want to update my R version. Thanks

Alex

Excellent work! I was just wondering whether you could think of supporting the Bioconductor AnnotationFilter for the subsetting of a plot, e.g. with a call such as: plotKaryoType(filter = ~ seq_name == "chr1") to restrict to data on chromosome 1 or plotKaryoType(filter = ~ genename == "BCL2").
This might be eventually interesting for other Bioconductor users since annotation resources start implementing the AnnotationFilter concept (e.g. ensembldb and soon also GenomicFeatures).

Add a new function "colByValue" that assigns a color to each data point based on its y value. Maybe it can receive a list/array of colors or a colorRamp or similar

Hello,

I am a post graduate student, now I want to use "karyoploteR" to plot my genome. But I do know that if I could use the genome assembled by myself? And if the answer is "yes", how should I do?

I am looking forward to your valuable reply.
Thanks a lot.

I installed the Github version of karyoploteR. I am not able to call the function "kpPlotTranscripts". Do I have to update to the latest version of R to do this? I'm currently using R 3.4.4.

Sorry to add something else to your "to do" list. I found something unpleasant in kpPlotCoverage visualization

There is a residue from the beginning of the chromosome to the last event in the data of kpPlotCoverage. It could represent the 0 coverage value but this residue vanish after the last event...

Example talks better :

custom.genome <- GRanges(seqnames="chr12",ranges=IRanges(1,300000),strand=NULL)
custom.coverage <- GRanges(seqnames=c("chr12","chr12","chr12"), ranges=c(IRanges(150000,200000),IRanges(150000,200000),IRanges(250000,260000)), strand=c("+","+","+"))
kp <- plotKaryotype(genome = custom.genome)
kpPlotCoverage(kp, data=custom.coverage)

Either the residue is added on the full length of the chromosome, like saying it is a 0 coverage nor simply remove the residue. As you wish !

Thanks again for the great tool !

Hello,
when I used the function "kpAddMainTitle", I cant change the cex of main title, is there a bug ?
It seems that code graphics::text(x = x, y = y, labels = , main, cex = 0.8, ...) have a bug.

thanks.

kpAddMainTitle
function (karyoplot, main = NULL, ...)
{
if (!is.null(main)) {
karyoplot$beginKpPlot()
on.exit(karyoplot$endKpPlot())
bb <- getMainTitleBoundingBox(karyoplot)
x <- (bb$x0 + bb$x1)/2
y <- (bb$y0 + bb$y1)/2
graphics::text(x = x, y = y, labels = , main, cex = 0.8,
...)
}
invisible(karyoplot)
}
<environment: namespace:karyoploteR>

Hello @bernatgel
As it seems simple to add a scale bar by myself on a kpPlotCoverage visualization for a single chromosome, creating a scale bar from 0 to "ymax" with some intermediate ticks (or -"ymax",0,"ymax" for sense and anti-sense values). It is more tricky when the display involved multiples chromosomes...

The only solution I got for now is to try to create multiple scale bar patterns, for 1 chromosome, 2 chromosomes, 3 chromosomes... Not very clean.

Thank you, again !

Hey,
I am trying to generate a plot.type = 4 karyoplot with a custom genome using the description here: https://bernatgel.github.io/karyoploter_tutorial//Examples/GeneDensity/GeneDensity.html
Everything is working ok but the kpAddCytobandsAsLine code does not add the chromosome bars. Relevant code is listed below:
`kp <- plotKaryotype(genome = Chr_sizes_GR, cytobands = gene_bed_GR, plot.type=4, ideogram.plotter = NULL, labels.plotter = NULL)
kpAddCytobandsAsLine(kp)
kpAddChromosomeNames(kp, srt=45)

ordered <- DEG_GR[order(DEG_GR$FDR, na.last = TRUE),]
fc.ymax=ceiling(max(abs(DEG_GR$logFC.GenotypeBb)))
fc.ymin=0

kpAxis(kp, ymax=fc.ymax, ymin=fc.ymin,side = 1,cex=0.5,r0 = 0.1, r1 = 0.45)
kpPlotDensity(kp, DEG_GR,r0 = 0.1,r1=0.45)
kpAddMainTitle(kp,main=title)
kpPlotRegions(kp,data = supergene_GR,col="red", r0=0,r1=0.05)
`
with Chr_sizes_GR looking like:
GRanges object with 16 ranges and 1 metadata column:
seqnames ranges strand | chr
|
[1] lg1 [1, 26801316] * | 1
[2] lg2 [1, 19642518] * | 2
[3] lg3 [1, 19384547] * | 3
[4] lg4 [1, 19999581] * | 4
[5] lg5 [1, 15556348] * | 5

and DEG_GR looking like:
GRanges object with 82 ranges and 8 metadata columns:
seqnames ranges strand | Row.names logFC.Genotypebb logFC.GenotypeBb logCPM F PValue FDR
|
275 lg13 [5389892, 5393558] * | gene10246 5.6892339 2.2617307 -0.44775874 13.99144 1.941337e-05 2.501616e-03
299 lg11 [1979965, 1981447] * | gene10268 -4.6336728 -4.6452638 0.02878333 12.80478 3.893802e-05 4.230502e-03
435 lg16 [8349870, 8355819] * | gene10391 7.3021439 6.6712809 4.73588785 23.68230 2.737338e-08 7.583794e-06
436 lg16 [8336934, 8342229] * | gene10392 0.7791989 0.4486888 6.25325327 11.00287 8.610967e-05 7.952228e-03

Any recommendations on how to help?
Thanks,
Sam

Hello Team,

is there a way we can use output of bedtools coverage with karyoploterR

Specifically this function kpPlotCoverage(kp, data=regions)

many thanks

Hi,
Thank you again for your previous help in plotting my data using karyoploteR. I have successfully used kpPlotRegions but was wondering if it is possible to colour the regions plotted above the ideogram? In my data they represent introgressions from multiple species so it would be great to be able to visually identify which species is present where.

Many thanks,
Sacha

Dear Bernat,
I feel so sorry to bother you twice in the same day. Here's another problem I met. I want to plot the GC content of a custom genome and I calculated it myself. However, I met problems when I tried to plot it with karyoploteR.

library(karyoploteR)
gme <-toGRanges("D:/work/experiment/transposon/lxq/script/function_combine/chr_info.txt")
pp <- getDefaultPlotParams(plot.type=2)
pp$leftmargin<-0.1
fig1<-plotKaryotype(gme,chromosome="CP017553.1",plot.type=2,plot.params=pp)
gc<-read.table(file="D:/bioinformatics/script/GC_content/gc.txt",head=TRUE)
head(gc)
chr region GC_content
1 CP017553.1 1-10000 0.4808
2 CP017553.1 10001-20000 0.5055
3 CP017553.1 20001-30000 0.4829
4 CP017553.1 30001-40000 0.4592
5 CP017553.1 40001-50000 0.5001
6 CP017553.1 50001-60000 0.4657
kpLines(fig1, data=gc, y=gc$GC_content)
Error in (function (classes, fdef, mtable) :
unable to find an inherited method for function 'seqnames' for signature '"data.frame"'

Then I tried,

gc<-DataFrame(gc)
head(gc)
DataFrame with 6 rows and 3 columns
chr region GC_content

1 CP017553.1 1-10000 0.4808
2 CP017553.1 10001-20000 0.5055
3 CP017553.1 20001-30000 0.4829
4 CP017553.1 30001-40000 0.4592
5 CP017553.1 40001-50000 0.5001
6 CP017553.1 50001-60000 0.4657
kpLines(fig1, data=gc, y=gc$GC_content)
Error in (function (classes, fdef, mtable) :
unable to find an inherited method for function 'seqnames' for signature '"DataFrame"'

I have no idea of what to do now.

Any help is appreciated.
Thanks.

Hello, when I was trying the tutorial, I always met an error with the function createRandomRegions().

regions <- createRandomRegions(nregions=10000, length.mean = 1e6, mask=NA)
Error in private_randomizeRegions(A = pending, genome = genome, mask = mask,  : 
  It was not possible to create a valid random region set after 5 retries. This might be due to the regions in A covering most of the available genome. Allowing overlapping random regions could solve this problem.
In addition: Warning messages:
1: In private_randomizeRegions(A = pending, genome = genome, mask = mask,  :
  It was not possible to create the random region set because there was no space available. Retrying.
2: In private_randomizeRegions(A = pending, genome = genome, mask = mask,  :
  It was not possible to create the random region set because there was no space available. Retrying.
3: In private_randomizeRegions(A = pending, genome = genome, mask = mask,  :
  It was not possible to create the random region set because there was no space available. Retrying.
4: In private_randomizeRegions(A = pending, genome = genome, mask = mask,  :
  It was not possible to create the random region set because there was no space available. Retrying.
5: In private_randomizeRegions(A = pending, genome = genome, mask = mask,  :
  It was not possible to create the random region set because there was no space available. Retrying.

I have installed the masked human genome hg19 by:
install("BSgenome.Hsapiens.UCSC.hg19")
Did I miss anything?

NA's cause different functions to fail (i.e. kpLines). Add a na.rm parameter and gracefully deal with these values (for example: make the missing values merely cause absence of image for only those points. For example, to just make the line to be discontinuous in kpLines. This is how NA is handled in ggplot2).

I'm trying to plot genes on a custom genome using a gff file (attached file saved with .txt suffix in order to upload here, but what I'm actually using has the .gff suffix). I can do the initial plotKaryotype step, but when I do kpPlotRegions, nothing shows up, and there is no error message. I tried assigning a blue color, but still nothing shows up on my plot. Without any error message, this is difficult to troubleshoot.

I checked my custom genome class, and it looks as expected:

class(mint.genome)
[1] "GRanges"
attr(,"package")
[1] "GenomicRanges"

Also, When I try to assign the custom genome at the import.gff step, I do get an error:
gff.file <- import.gff("Mlong585_v3.01_Rgenes.gff", genome=mint.genome)

Error in readGFFAsGRanges(con, version = version, colnames = colnames, :
'genome' must be a single string or NA, or a Seqinfo object
In addition: Warning message:
In if (is.na(genome)) { :
the condition has length > 1 and only the first element will be used

My gff file

Mlong585_v3.01_Rgenes2.txt

My code

mint.genome <- toGRanges(data.frame(chr=c("scaffold1_length_46699537", "scaffold2_length_45526029", "scaffold3_length_45460755", "scaffold4_length_44284954", "scaffold5_length_43231337", "scaffold6_length_37537474", "scaffold7_length_36621300", "scaffold8_length_36842082", "scaffold9_length_33738042", "scaffold10_length_33088173", "scaffold11_length_29943784", "scaffold12_length_29660084"),
start = c(1,1,1,1,1,1,1,1,1,1,1,1), end=c(46699537, 45526029, 45460755, 44284954, 43231337, 37537474, 36621300, 36842082, 33738042, 33088173, 29943784, 29660084)))
class(mint.genome)
kp <- plotKaryotype(genome = mint.genome, ideogram.plotter = NULL, plot.type=2)
kpAddCytobandsAsLine(kp)

gff.file <- import.gff("C:/Users/viningk/Desktop/Mint/Mlong_v3.01/MintChromPlots/Mlong585_v3.01_Rgenes.gff")

genes <- gff.file[gff.file$type=="gene"]

kpPlotRegions(kp, data = genes)
kpPlotRegions(kp, data=genes[strand(genes)=="+"], avoid.overlapping = FALSE, col="deepskyblue")

Dear,
There is error when I use the karyoploteR for custom genome as follows.

gme <- toGRanges("D:/work/experiment/transposon/lxq/script/function_combine/chr_info.txt")
unit<- toGRanges("D:/work/experiment/transposon/lxq/script/function_combine/genome_info.txt")
gme
GRanges object with 7 ranges and 0 metadata columns:
seqnames ranges strand
<Rle> <IRanges> <Rle>
[1] CP017553 1-2257857 *
[2] CP017554 1-3044971 *
[3] CP017555 1-3366276 *
[4] CP017556 1-3629463 *
[5] CP017557 1-4198534 *
[6] CP017558 1-4002965 *
[7] CP017559 1-47926 *
-------
seqinfo: 7 sequences from an unspecified genome; no seqlengths
unit
GRanges object with 8772 ranges and 2 metadata columns:
seqnames ranges strand | name id
<Rle> <IRanges> <Rle> | <integer> <factor>
[1] CP017553 1230-1648 * | 1 YALI1_A00014g
[2] CP017553 1806-2173 * | 2 YALI1_A00019g
[3] CP017553 3285-3920 * | 3 YALI1_A00032g
[4] CP017553 5868-8531 * | 4 YALI1_A00058g
[5] CP017553 10299-12134 * | 5 YALI1_A00102g
... ... ... ... . ... ...
[8768] CP017559 41321-41863 * | 52 YALI1_M00390g
[8769] CP017559 42454-43596 * | 53 YALI1_M00390g
[8770] CP017559 43776-45089 * | 54 YALI1_M00390g
[8771] CP017559 45843-47252 * | 55 YALI1_M00458g
[8772] CP017559 47272-47658 * | 56 YALI1_M00472r
-------
seqinfo: 7 sequences from an unspecified genome; no seqlengths
fig1<-plotKaryotype(gme,chromosome="CP017553",plot.type=2)
kpPlotDensity(fig1,data=unit,r0=0,r1=0.3,window.size=10000)
kpAxis(fig1, ymax=fig1$latest.plot$computed.values$max.density, r0=0, r1=0.3, cex=0.8)
kpAbline(fig1, h=mean(fig1$latest.plot$computed.values$density), lty=2, ymax=fig1$latest.plot$computed.values$max.density, r0=0, r1=0.3)
Warning message:
In mean.default(fig1$latest.plot$computed.values$density) :
argument is not numeric or logical: returning NA

I have tried :

kpAbline(fig1, h=mean(data.matrix(fig1$latest.plot$computed.values$density)), lty=2, ymax=fig1$latest.plot$computed.values$max.density, r0=0, r1=0.27)
Error in array(x, c(length(x), 1L), if (!is.null(names(x))) list(names(x), :
'data' must be of a vector type, was 'NULL'

and

fig1$latest.plot$computed.values$density
NULL

The figures now showed as:

Any help is much appreciated.
Thanks.

Similar to the two triangles in UCSC

kpPlotBAMDensity was written with large windows and the whole genome in mind. But for smaller windows and specially for small parts of the genome it can be very innefficient. Optimize it using the same approach as in kpPlotBigWig and clarify what's our preferred approach to plot the coverage of a BAM file.

Hi,

I wanted my density plot to display only values up to a certain number. When I try to use the ymax parameter I still see density regions way above my plot ceiling, and actually overlapping the plots above (image below).

kp <- kpPlotDensity(kp, data = dataGR, window.size = 10000, border="black", col="#b3ffe099", ymax=2)

• When I add kpAxis to this plot I only see values of 0-1, despite the density values ranging from 1-86. (I checked the kp$latest.plot$computed.values$density)
• Is there a better way to put a cap on what density value is displayed on the plot?

Thanks

Hi,
Thanks for developing the package looks great. I wonder if it’s possible to plot any sort of bands using custom colors? Something like the cytobands but input a bed file with regions and a column with colors associated to the type of region?

Thanks

Add a new data.panel to all plot.types, data.panel=0, that plots on the ideogram. coord change functions can be the same for all plot.types.

Could you add other plant genomes ?

Dear Bernat,

I met this problem in dealing with one bam file.

library(karyoploteR)
gme <- toGRanges("D:/work/experiment/transposon/lxq/script/function_combine/chr_info.txt")
pp <- getDefaultPlotParams(plot.type=2)
pp$leftmargin<-0.1
fig1<-plotKaryotype(gme,chromosome="CP017553.1",plot.type=2,plot.params=pp)
kpAddBaseNumbers(fig1, tick.dist = 100000,add.units=TRUE)
bam1<-("D:/bioinformatics/gbib/shared/sample/d1-1.sorted.bam")
fig1 <- kpPlotBAMCoverage(fig1, data=bam1, r0=0,r1=1.,max.valid.region.size=2e8)
kpAxis(fig1, ymax=fig1$latest.plot$computed.values$max.coverage, r0=0, r1=1)
fig1$latest.plot$computed.values$max.coverage
[1] 228

The max coverage is 228. However, the plot showed as this, no value seemed to be larger than 144. I don't know what goes wrong.

Besides, I wanted to extract the coverage data, but it only had one value. So, what should I do to get the data?

kpAxis(fig1, ymax=fig1$latest.plot$computed.values$max.coverage, r0=0, r1=1)
fig1$latest.plot$computed.values
$max.coverage
[1] 228

Thank you for your time.

Hello,
I was wondering if you had any suggestions as to how kpPoints might plot point density in a similar way to ggplot2? We have points of estimated copy number in 100kb bins across chromosomes, and it's difficult to determine whether or not outliers (CN > 4, 5, 6, etc...) are a minority of points.

Thanks,
Mike

Hello @bernatgel,
There is a bug in kpAddBaseNumbers, X-axis is 1-base offbeat from the plotKaryotype
custom.genome <- GRanges(seqnames="chr12",ranges=IRanges(300000000,300000100),strand=NULL)
custom.coverage <- GRanges(seqnames=c("chr12","chr12","chr12"), ranges=c(IRanges(300000010,300000040),IRanges(300000050,300000055),IRanges(300000070,300000095)), strand=c("+","+","+"))
kp <- plotKaryotype(plot.type=1, genome = custom.genome)
kpPlotCoverage(kp, data=custom.coverage, show.0.cov=FALSE)
kpAddBaseNumbers(kp, tick.dist = 5, tick.col="red", minor.tick.dist = 1, minor.tick.col = "gray")

sessionInfo()

[1] karyoploteR_1.8.7

If I may ask something else, I find the X-axis scale not informative enought when I try to zoom in, here on my example I want to zoom in from 300 000 000 to 300 000 100, would it be possible to display the full number of bases, not only 300(Mb) for each tick.

Something similar to set the digits option at 6, but without the dot and without the frame shifting

Thanks a ton !

Outstanding package to fit LAM-HTGTS method results other than Circos plot !
I have a request that I already post on Biostars (https://www.biostars.org/p/306637/).
I don't want to duplicate my post over Biostars, Github, Bioconductor...
My goal is to plot on the same plotKaryotype, with a custom genome, a slice of chr12 (from 113 200 000 to 113 550 000) and a slice of chr6 (from 70 720 000 to 71 150 000), then to had kpAddBaseNumbers, to get the scale. The issue is that kpAddBaseNumbers can't create a scale for chr12 and a different one for chr6. Thanks !

Hi guys,
I stumbled upon the impossibility to add Base Numbers to a Type 2 ideogram. A few months ago I was able to generate a KaryoPlot of type 2 with custom cytobands and custom annotations without any issues. I tried to correct one annotation recycling my code and stumbled upon the impossibility to add base numbers. Here is an example using the shipped datasets:

> kp <- plotKaryotype(genome="hg19",plot.type=2)
> kpAddBaseNumbers(kp)

Error in ccf(chr = rep(chr.name, length(tick.pos)), x = tick.pos) : 
  In coordChangeFunction: data.panel is required

Providing data.panel attribute to kpAddBaseNumbers does not help.

Is this only happening to me, or is it a bug?
Thanks in advance for looking into this.

I am trying out the kpPlotRainfall function with some internal datasets (cancer genomes). I seem to get an error when variants are absent from a particular chromosome. Considering the demo dataset used in the tutorial, the error can be exemplified as follows when removing variants from chromosome 1:

> sm <- sm %>% dplyr::filter(chr != "1")
> sm.gr <- toGRanges(sm[,c("chr", "start", "end", "ref", "alt")])
> seqlevelsStyle(sm.gr) <- "UCSC"
> kp <- plotKaryotype(plot.type = 4)
> kpPlotRainfall(kp, data = sm.gr)

Error_ in attr(x, "tsp") <- c(1, NROW(x), 1) :
attempt to set an attribute on NULL

Adding base numbers with very small tick dist is too slow. Reimplement to take into account zoomed in region before plotting.

Hi Bernat!

I've realized that kpPlotRegions has an argument avoid.overlapping to stack regions and avoid overlapping them - would be nice if kpPlotTranscripts had also the same option.

When plotting genes with kpPlotGenes in data.panel=2, the strand of the genes is flipped. Problems with the computation of the strand marks.

Hello,

As per the title, plotKaryotype doesn't seem to recognize zoom as a parameter.
A reproducible example should be:

gnome <- getBSgenome("BSgenome.Dmelanogaster.UCSC.dm3", 
                     masked = F)

detail3L <- toGRanges(data.frame("chr3L", 1550000, 1560000 ))

k <- plotKaryotype(gnome, plot.type = 2, zoom = detail3L)



> sessionInfo()
R version 3.4.2 (2017-09-28)
Platform: x86_64-apple-darwin15.6.0 (64-bit)
Running under: macOS High Sierra 10.13.1

Matrix products: default
BLAS: /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/3.4/Resources/lib/libRlapack.dylib

locale:
[1] en_CA.UTF-8/en_CA.UTF-8/en_CA.UTF-8/C/en_CA.UTF-8/en_CA.UTF-8

attached base packages:
 [1] grid      stats4    parallel  stats     graphics  grDevices
 [7] utils     datasets  methods   base     

other attached packages:
 [1] BSgenome.Dmelanogaster.UCSC.dm3_1.4.0
 [2] BiocInstaller_1.26.1                 
 [3] stringr_1.2.0                        
 [4] karyoploteR_1.2.2                    
 [5] regioneR_1.8.1                       
 [6] BSgenome_1.44.2                      
 [7] rtracklayer_1.36.6                   
 [8] memoise_1.1.0                        
 [9] gridExtra_2.3                        
[10] pcaExplorer_2.2.1                    
[11] vsn_3.44.0                           
[12] pheatmap_1.0.8                       
[13] gplots_3.0.1                         
[14] ggrepel_0.7.0                        
[15] naturalsort_0.1.3                    
[16] tximport_1.4.0                       
[17] dplyr_0.7.4                          
[18] plyr_1.8.4                           
[19] org.Dm.eg.db_3.4.1                   
[20] AnnotationDbi_1.38.2                 
[21] clusterProfiler_3.4.4                
[22] DOSE_3.2.0                           
[23] ggplot2_2.2.1                        
[24] VennDiagram_1.6.18                   
[25] futile.logger_1.4.3                  
[26] DESeq2_1.16.1                        
[27] RColorBrewer_1.1-2                   
[28] RUVSeq_1.10.0                        
[29] edgeR_3.18.1                         
[30] limma_3.32.10                        
[31] EDASeq_2.10.0                        
[32] ShortRead_1.34.2                     
[33] GenomicAlignments_1.12.2             
[34] SummarizedExperiment_1.6.5           
[35] DelayedArray_0.2.7                   
[36] matrixStats_0.52.2                   
[37] Rsamtools_1.28.0                     
[38] GenomicRanges_1.28.6                 
[39] GenomeInfoDb_1.12.3                  
[40] Biostrings_2.44.2                    
[41] XVector_0.16.0                       
[42] IRanges_2.10.5                       
[43] S4Vectors_0.14.7                     
[44] BiocParallel_1.10.1                  
[45] Biobase_2.36.2                       
[46] BiocGenerics_0.22.1                  

loaded via a namespace (and not attached):
  [1] shinydashboard_0.6.1          R.utils_2.6.0                
  [3] RSQLite_2.0                   htmlwidgets_0.9              
  [5] DESeq_1.28.0                  munsell_0.4.3                
  [7] codetools_0.2-15              preprocessCore_1.38.1        
  [9] DT_0.2                        colorspace_1.3-2             
 [11] GOSemSim_2.2.0                Category_2.42.1              
 [13] knitr_1.17                    NMF_0.20.6                   
 [15] GenomeInfoDbData_0.99.0       hwriter_1.3.2                
 [17] topGO_2.28.0                  bit64_0.9-7                  
 [19] rprojroot_1.2                 lambda.r_1.2                 
 [21] biovizBase_1.24.0             R6_2.2.2                     
 [23] doParallel_1.0.11             locfit_1.5-9.1               
 [25] AnnotationFilter_1.0.0        bitops_1.0-6                 
 [27] shinyAce_0.2.1                fgsea_1.2.1                  
 [29] assertthat_0.2.0              d3heatmap_0.6.1.1            
 [31] scales_0.5.0                  nnet_7.3-12                  
 [33] gtable_0.2.0                  affy_1.54.0                  
 [35] ensembldb_2.0.4               rlang_0.1.4                  
 [37] genefilter_1.58.1             splines_3.4.2                
 [39] lazyeval_0.2.1                acepack_1.4.1                
 [41] dichromat_2.0-0               shinyBS_0.61                 
 [43] checkmate_1.8.5               yaml_2.1.14                  
 [45] reshape2_1.4.2                GenomicFeatures_1.28.5       
 [47] threejs_0.3.1                 crosstalk_1.0.0              
 [49] backports_1.1.1               httpuv_1.3.5                 
 [51] qvalue_2.8.0                  Hmisc_4.0-3                  
 [53] RBGL_1.52.0                   tools_3.4.2                  
 [55] gridBase_0.4-7                affyio_1.46.0                
 [57] Rcpp_0.12.14                  base64enc_0.1-3              
 [59] zlibbioc_1.22.0               purrr_0.2.4                  
 [61] RCurl_1.95-4.8                rpart_4.1-11                 
 [63] cluster_2.0.6                 magrittr_1.5                 
 [65] data.table_1.10.4-3           futile.options_1.0.0         
 [67] DO.db_2.9                     SparseM_1.77                 
 [69] ProtGenerics_1.8.0            aroma.light_3.6.0            
 [71] mime_0.5                      evaluate_0.10.1              
 [73] xtable_1.8-2                  XML_3.98-1.9                 
 [75] compiler_3.4.2                biomaRt_2.32.1               
 [77] tibble_1.3.4                  KernSmooth_2.23-15           
 [79] R.oo_1.21.0                   htmltools_0.3.6              
 [81] GOstats_2.42.0                Formula_1.2-2                
 [83] tidyr_0.7.2                   geneplotter_1.54.0           
 [85] DBI_0.7                       MASS_7.3-47                  
 [87] Matrix_1.2-12                 R.methodsS3_1.7.1            
 [89] gdata_2.18.0                  bindr_0.1                    
 [91] igraph_1.1.2                  pkgconfig_2.0.1              
 [93] rvcheck_0.0.9                 registry_0.3                 
 [95] foreign_0.8-69                foreach_1.4.3                
 [97] annotate_1.54.0               rngtools_1.2.4               
 [99] pkgmaker_0.22                 AnnotationForge_1.18.2       
[101] VariantAnnotation_1.22.3      digest_0.6.12                
[103] graph_1.54.0                  rmarkdown_1.8                
[105] fastmatch_1.1-0               htmlTable_1.9                
[107] GSEABase_1.38.2               curl_3.0                     
[109] shiny_1.0.5                   gtools_3.5.0                 
[111] bindrcpp_0.2                  lattice_0.20-35              
[113] httr_1.3.1                    survival_2.41-3              
[115] GO.db_3.4.1                   interactiveDisplayBase_1.14.0
[117] glue_1.2.0                    png_0.1-7                    
[119] iterators_1.0.8               bit_1.1-12                   
[121] stringi_1.1.6                 blob_1.1.0                   
[123] AnnotationHub_2.8.3           latticeExtra_0.6-28          
[125] caTools_1.17.1  

To the best of my knowledge I've not missed anything obvious...
Any ideas?

Hi,

• I would like to have my y-axis reflect the values underlying the density calculation in kpPlotDensity.
• Using the code provided in your tutorial page I only get values from 0-1 on the y-axis.
  kpAxis(kp, ymax=kp$latest.plot$computed.values$max.coverage, r0=0.5, r1=0.9, cex=0.8)
• How can I make the y-axis reflect the raw values used to calculate density instead of the actual density?

Thanks

Dear author ,can the software add some color bars to the gene density. So that we can plot different colors to display the gene density coverage?
Alex

Hi,

I'm trying to use karyoploteR, but I got these error messages:

> kp <- plotKaryotype(genome = "dm6")
There was an error when filtering the chromosomes. Using the unfiltered genome. 
Error in keepSeqlevels(A, valid.chr, pruning.mode = "coarse"): unused argument (pruning.mode = "coarse")

Error in GenomeInfoDb::keepSeqlevels(cytobands, value = GenomeInfoDb::seqlevels(gr.genome),  : 
  unused argument (pruning.mode = "coarse")
> sessionInfo()
R version 3.4.1 (2017-06-30)
Platform: i386-w64-mingw32/i386 (32-bit)
Running under: Windows >= 8 (build 9200)

Matrix products: default

locale:
[1] LC_COLLATE=Chinese (Simplified)_China.936  LC_CTYPE=Chinese (Simplified)_China.936   
[3] LC_MONETARY=Chinese (Simplified)_China.936 LC_NUMERIC=C                              
[5] LC_TIME=Chinese (Simplified)_China.936    

attached base packages:
 [1] grid      parallel  stats4    stats     graphics  grDevices utils     datasets 
 [9] methods   base     

other attached packages:
 [1] karyoploteR_1.3.1    regioneR_1.8.1       BSgenome_1.42.0      rtracklayer_1.34.2  
 [5] Biostrings_2.42.1    XVector_0.14.1       memoise_1.1.0        BiocInstaller_1.24.0
 [9] Gviz_1.18.2          GenomicRanges_1.26.4 GenomeInfoDb_1.10.3  IRanges_2.8.2       
[13] S4Vectors_0.12.2     BiocGenerics_0.20.0 

loaded via a namespace (and not attached):
 [1] Rcpp_0.12.12                  Formula_1.2-2                
 [3] knitr_1.17                    AnnotationHub_2.6.5          
 [5] magrittr_1.5                  cluster_2.0.6                
 [7] devtools_1.13.3               GenomicAlignments_1.10.1     
 [9] splines_3.4.1                 zlibbioc_1.20.0              
[11] bit_1.1-12                    xtable_1.8-2                 
[13] colorspace_1.3-2              biovizBase_1.22.0            
[15] lattice_0.20-35               R6_2.2.2                     
[17] rlang_0.1.2                   latticeExtra_0.6-28          
[19] git2r_0.19.0                  withr_2.0.0                  
[21] matrixStats_0.52.2            htmltools_0.3.6              
[23] bit64_0.9-7                   digest_0.6.12                
[25] interactiveDisplayBase_1.12.0 tibble_1.3.4                 
[27] Matrix_1.2-11                 shiny_1.0.5                  
[29] acepack_1.4.1                 curl_2.8.1                   
[31] RCurl_1.95-4.8                compiler_3.4.1               
[33] scales_0.5.0                  backports_1.1.0              
[35] Hmisc_4.0-3                   Rsamtools_1.26.2             
[37] GenomicFeatures_1.26.4        httpuv_1.3.5                 
[39] AnnotationDbi_1.36.2          munsell_0.4.3                
[41] BiocParallel_1.8.2            blob_1.1.0                   
[43] httr_1.3.1                    plyr_1.8.4                   
[45] stringr_1.2.0                 ensembldb_1.6.2              
[47] tools_3.4.1                   nnet_7.3-12                  
[49] dichromat_2.0-0               SummarizedExperiment_1.4.0   
[51] htmlTable_1.9                 Biobase_2.34.0               
[53] data.table_1.10.4             gtable_0.2.0                 
[55] checkmate_1.8.3               DBI_0.7                      
[57] yaml_2.1.14                   lazyeval_0.2.0               
[59] survival_2.41-3               gridExtra_2.3                
[61] bezier_1.1                    ggplot2_2.2.1                
[63] RColorBrewer_1.1-2            bitops_1.0-6                 
[65] htmlwidgets_0.9               base64enc_0.1-3              
[67] biomaRt_2.30.0                rpart_4.1-11                 
[69] RSQLite_2.0                   mime_0.5                     
[71] stringi_1.1.5                 XML_3.98-1.9                 
[73] VariantAnnotation_1.20.3      foreign_0.8-69

Any suggestions would be appreciated.

Thanks!

During the execution of the following
biocLite("karyoploteR")
I received the following 2 error messages during the installation of source package 'rsconnect' ...

appDependencies html
Rd warning: K:/Temp/Windows Temp/RtmpCSsg3f/R.INSTALL216c2218440d/rsconnect/man/appDependencies.Rd:63: missing file link 'rsconnectPackages'

proxies html
Rd warning: K:/Temp/Windows Temp/RtmpCSsg3f/R.INSTALL216c2218440d/rsconnect/man/proxies.Rd:9: missing file link 'rsconnectOptions'

I don't know how important they are.

I tried...
library(karyoploteR)
It returned the prompt. Therefore, I just want to flag this and see whether anything I could do to "fix" the issues before going too far down the road.

Hi,

I'm trying to plot different segments along a custom genome. I can plot the chromosomes without the segments but when I add these the background image of the chromosome disappears and only the segments are visible (see below). Can you help?

Here is a sample of my mycytobands.txt file:

Thank you in advance!

Sacha

Hello,
I am having difficulty installing KaryoploteR.
I updated R to 3.5.1 and followed to the installation instructions. However, when I opened KaryoploteR, I received several errors (see below). Then, when I tried to plot an ideogram, the commands were not recognized. Any help/ideas?

source("https://bioconductor.org/biocLite.R")
Bioconductor version 3.7 (BiocInstaller 1.30.0), ?biocLite for help
biocLite("karyoploteR")
BioC_mirror: https://bioconductor.org
Using Bioconductor 3.7 (BiocInstaller 1.30.0), R 3.5.1 (2018-07-02).
Installing package(s) ‘karyoploteR’
trying URL 'https://bioconductor.org/packages/3.7/bioc/bin/macosx/el-capitan/contrib/3.5/karyoploteR_1.6.0.tgz'
Content type 'application/x-gzip' length 2800531 bytes (2.7 MB)
==================================================
downloaded 2.7 MB

library(karyoploteR)
Loading required package: regioneR
Loading required package: memoise
Loading required package: GenomicRanges
Loading required package: stats4
Loading required package: BiocGenerics
Loading required package: parallel

Attaching package: ‘BiocGenerics’

The following objects are masked from ‘package:parallel’:

clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
clusterExport, clusterMap, parApply, parCapply, parLapply,
parLapplyLB, parRapply, parSapply, parSapplyLB

The following objects are masked from ‘package:stats’:

IQR, mad, sd, var, xtabs

The following objects are masked from ‘package:base’:

anyDuplicated, append, as.data.frame, basename, cbind, colMeans,
colnames, colSums, dirname, do.call, duplicated, eval, evalq,
Filter, Find, get, grep, grepl, intersect, is.unsorted, lapply,
lengths, Map, mapply, match, mget, order, paste, pmax, pmax.int,
pmin, pmin.int, Position, rank, rbind, Reduce, rowMeans, rownames,
rowSums, sapply, setdiff, sort, table, tapply, union, unique,
unsplit, which, which.max, which.min

Loading required package: S4Vectors

Attaching package: ‘S4Vectors’

The following object is masked from ‘package:plyr’:

rename

The following object is masked from ‘package:base’:

expand.grid

Loading required package: IRanges

Attaching package: ‘IRanges’

The following object is masked from ‘package:plyr’:

desc

Loading required package: GenomeInfoDb
Loading required package: BSgenome
Loading required package: Biostrings
Loading required package: XVector

Attaching package: ‘XVector’

The following object is masked from ‘package:plyr’:

compact

Attaching package: ‘Biostrings’

The following object is masked from ‘package:base’:

strsplit

Loading required package: rtracklayer
Error: package or namespace load failed for ‘rtracklayer’ in loadNamespace(j <- i[[1L]], c(lib.loc, .libPaths()), versionCheck = vI[[j]]):
there is no package called ‘XML’
Error: package ‘rtracklayer’ could not be loaded

kp <- plotKaryotype(genome="hg19")
Error in plotKaryotype(genome = "hg19") :
could not find function "plotKaryotype"

Hello Bernat,

Awesome, package! I've got a (hopefully quick) question about plotting line data.

When I go to plot 'arbitrary data' over the karyotype (or chromosome), the data appears to be off by 1 chr (specifically, data for a particular chr is plotted on the chr directly preceding it).

You can see in the plot below just from the lengths of the line plotted, that it should go with chr4 and not chr3 (and the chr3 line data presumably is being plotted off the display here for chr2):

Code to generate the plot:

library(karyoploteR)
input <- 'Sviridis_500_v2.0_NC028075.1_data.tsv'
df <- read.table(input,sep='\t',header=F)
custom.genome <- toGRanges(df)
c=c("Chr_03","Chr_04")
kp <- plotKaryotype(genome=custom.genome, chromosomes=c)

# input overlay data
input <- 'Sviridis_500_v2.0_NC028075.1_entropy100K.tsv'
entropy <- read.table(input,sep='\t',header=F)
custom.data <- toGRanges(entropy)
kpLines(kp, chr=seqnames(custom.data), x=end(ranges(custom.data)), y=custom.data$V5, data.panel = 1)
# add axis scale
kpAxis(kp, data.panel=1)

input 1:

head Sviridis_500_v2.0_NC028075.1_data.tsv 
Chr_01	1	41732233
Chr_02	1	47849963
Chr_03	1	50382502
Chr_04	1	39677845
Chr_05	1	46702114
Chr_06	1	36371416
Chr_07	1	35460007
Chr_08	1	40988899
Chr_09	1	56381885
NC_028075.1	1	138102

input 2:

head Sviridis_500_v2.0_NC028075.1_entropy100K.tsv 
Chr_01	1	100000	50001	1.99854
Chr_01	100001	200000	150001	1.99015
Chr_01	200001	300000	250001	1.99809
Chr_01	300001	400000	350001	1.99701
Chr_01	400001	500000	450001	1.99505
Chr_01	500001	600000	550001	1.99683
Chr_01	600001	700000	650001	1.98968
Chr_01	700001	800000	750001	1.99389
Chr_01	800001	900000	850001	1.98916
Chr_01	900001	1000000	950001	1.99147

Might be something simple in my code, not sure. This same issue occurs whether or not the entropy data is a data.frame. or a GRanges object (as shown above).

Appreciate any feedback, thanks!

Hello,
I'm walking through the P. vivax genes tutorial in order to troubleshoot my own custom genome plotting issues. When I get to the following code block:

pp <- getDefaultPlotParams(plot.type=2)
pp$data1outmargin <- 100
pp$data2outmargin <- 100
pp$topmargin <- 450
kp <- plotKaryotype(genome=PvP01.genome, ideogram.plotter = NULL, plot.type=2, plot.params = pp)
kpAddCytobandsAsLine(kp)

I get this error:

Error in ccf(x = start(cyto), chr = as.character(seqnames(cyto))) :
In coordChangeFunction: data.panel is required

I tried adding a data.panel param, but got the same error:

kpAddCytobandsAsLine(kp, data.panel = 1)
Error in ccf(x = start(cyto), chr = as.character(seqnames(cyto))) :
In coordChangeFunction: data.panel is required

Why is this error showing up, and how do I fix it?

As reported by @lnonell there's a bug in plot.type=5 causing the data panel to be inverted. This is due to implementation changes that implemented it as a special case of plot.type=3. A potential solution would be to invert ymin and ymax? Otherwise reimplement as an independent type.

Dear Bernat Gel

When I use package "karyoploteR", I met a problem.

If I make the window.size=100 in command "kpPlotDensity", the window in somewhere will become 158891-158989 (It is only 99 bp, not 100 bp) . It is not from 158891-158990.

Why does this happen? And is there any way to avoid this case?

Best regards,
Zheng JIN

Hi, I really like this package for plotting data along a genome, and it has worked well for me when I visualize the entire genome using a custom genome. However, when I try to only visualize a single chromosome, I get the error:
"No valid genome specified and no cytobands provided. No cytobands will be passed to the ideogram plotter."
and the entire genome is plotted. My genome dataframe looks like this:

Hmel2pt5Genome
chromosome start end chr
3 chr1 1 17206585 1
14 chr2 1 9045316 2
15 chr3 1 10541528 3
16 chr4 1 9662098 4
17 chr5 1 9908586 5
18 chr6 1 14054175 6
19 chr7 1 14308859 7
20 chr8 1 9320449 8
21 chr9 1 8708747 9
1 chr10 1 17965481 10
2 chr11 1 11759272 11
4 chr12 1 16327298 12
5 chr13 1 18127314 13
6 chr14 1 9174305 14
7 chr15 1 10235750 15
8 chr16 1 10083215 16
9 chr17 1 14773299 17
10 chr18 1 16803890 18
11 chr19 1 16399344 19
12 chr20 1 14871695 20
13 chr21 1 13359691 21

I converted to Grange object with this command:
Hmel2pt5GenomeGrange <- makeGRangesFromDataFrame(Hmel2pt5Genome, seqnames.field = "chromosome")

And the resulting Grange object looks like this:

Hmel2pt5GenomeGrange
GRanges object with 21 ranges and 0 metadata columns:
seqnames ranges strand

3 chr1 [1, 17206585] *
14 chr2 [1, 9045316] *
15 chr3 [1, 10541528] *
16 chr4 [1, 9662098] *
17 chr5 [1, 9908586] *
.. ... ... ...
9 chr17 [1, 14773299] *
10 chr18 [1, 16803890] *
11 chr19 [1, 16399344] *
12 chr20 [1, 14871695] *
13 chr21 [1, 13359691] *

seqinfo: 21 sequences from an unspecified genome; no seqlengths

Is there a different method I should use to create the genome? Or perhaps a specific field identifier I need to use? Thank you!

Nate

library(karyoploteR)
kpArea()
Error in kpArea() : could not find function "kpArea"
?kpArea
No documentation for 'kpArea' in specified packages and libraries:

However, it is in the documentation at Bioconductor

I am getting the following when I run karyoploteR

library(karyoploteR)
kp <- plotKaryotype(genome = "hg19", plot.type = 3)

Error in graphics::par(kp$graphical.par$old.par) :
invalid value specified for graphical parameter "pin"
Error in graphics::par(kp$graphical.par$old.par) :
invalid value specified for graphical parameter "pin"

When I run the following:
My code:

pp <- getDefaultPlotParams(plot.type = 4)
pp$data1max <- 1
kp <- plotKaryotype(zoom = toGRanges(data.frame("chr1", 1, 1e6)),
                    main = "",
                    plot.params = pp,
                    cytobands = NULL)
kpDataBackground(kp, data.panel = 1, col = "#FFFFFF")

I get the following error

Error in (function (x0, y0, x1 = x0, y1 = y0, col = par("fg"), lty = par("lty"),  : 
  plot.new has not been called yet

Fyi, I get the same error if I call kpBars or kpAxis

sessionInfo()

R version 3.4.4 (2018-03-15)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 16.04.5 LTS

Matrix products: default
BLAS: /usr/lib/libblas/libblas.so.3.6.0
LAPACK: /usr/lib/lapack/liblapack.so.3.6.0

locale:
 [1] LC_CTYPE=en_US.UTF-8      
 [2] LC_NUMERIC=C              
 [3] LC_TIME=en_US.UTF-8       
 [4] LC_COLLATE=en_US.UTF-8    
 [5] LC_MONETARY=en_US.UTF-8   
 [6] LC_MESSAGES=en_US.UTF-8   
 [7] LC_PAPER=en_US.UTF-8      
 [8] LC_NAME=C                 
 [9] LC_ADDRESS=C              
[10] LC_TELEPHONE=C            
[11] LC_MEASUREMENT=en_US.UTF-8
[12] LC_IDENTIFICATION=C       

attached base packages:
[1] parallel  stats4    stats    
[4] graphics  grDevices utils    
[7] datasets  methods   base     

other attached packages:
 [1] ballgown_2.10.0                        
 [2] TxDb.Hsapiens.UCSC.hg19.knownGene_3.2.2
 [3] GenomicFeatures_1.30.3                 
 [4] AnnotationDbi_1.40.0                   
 [5] Biobase_2.38.0                         
 [6] karyoploteR_1.9.1                      
 [7] regioneR_1.10.0                        
 [8] BSgenome_1.46.0                        
 [9] Biostrings_2.46.0                      
[10] XVector_0.18.0                         
[11] memoise_1.1.0                          
[12] rtracklayer_1.38.3                     
[13] GenomicRanges_1.30.3                   
[14] GenomeInfoDb_1.14.0                    
[15] IRanges_2.12.0                         
[16] S4Vectors_0.16.0                       
[17] BiocGenerics_0.24.0                      

If r1 is NULL and r0 has two elements, r0 and r1, use them as r0 and r1. This will reduce the typing when using autotrack.