Whole-chromosome parallel plots

knitr::opts_chunk$set(cache = TRUE, cache.lazy = FALSE)
knitr::opts_knit$set(verbose = TRUE)

Introduction

Pairwise alignments between whole chromosomes are plotted in parallel in order to reflect synteny and the difference of scrambling between short and long arms.

Figure 1 panel B was generated in this vignette.

Load R pacakges and data

Load pacakges

library('OikScrambling') |> suppressPackageStartupMessages()
genomes <- OikScrambling:::loadAllGenomes()

## Warning in runHook(".onLoad", env, package.lib, package): input string
## 'Génoscope' cannot be translated from 'ANSI_X3.4-1968' to UTF-8, but is valid
## UTF-8

## Warning in runHook(".onLoad", env, package.lib, package): input string
## 'Génoscope' cannot be translated from 'ANSI_X3.4-1968' to UTF-8, but is valid
## UTF-8

load("BreakPoints.Rdata")

Phylogenetic cladogram

We assume that the North Pacific and the Atlantic species are more related to each other than to the Okinawan species.

requireNamespace("ade4")
treeLeaf <- function(name, length=NULL) {
  if(!is.null(length)) length <- paste0(':', length)
  paste0(name, length)
}

treeNode <- function(branch1, branch2, length = NULL) {
  if(!is.null(length)) length <- paste0(':', length)
  paste0('(', branch1, ',', branch2, ')', length)
}

addRoot <- function(branch)  paste0(branch, ";")

tree <-
  addRoot(
    treeNode(
      treeNode( length = 2,
        treeLeaf("Okinawa", 1),
        treeLeaf("Kume", 1)
      ),
      treeNode( length = 1,
        treeNode( length = 1,
          treeLeaf("Osaka", 1),
          treeLeaf("Aomori", 1)
        ),
        treeNode( length =1,
          treeLeaf("Norway", 1),
          treeLeaf("Barcelona", 1)
        )
      )
    )
  )

plot(ade4::newick2phylog(tree))

Plot chr2 in six species

We chose chromosome 2 because it has Hox4.

Parallel plot

KumChr2 <- scaffoldByFlipAndMerge(gbs$Oki_Kum |> swap(), scafs$Kum_Oki, drop = TRUE) |> swap() |> coalesce_contigs()
Aom_Osa <- scaffoldByFlipAndMerge(gbs$Osa_Aom |> swap(), scafs$Aom_Osa, drop = TRUE) |> swap() |> coalesce_contigs()
Aom_Oki <- scaffoldByFlipAndMerge(gbs$Oki_Aom |> swap(), scafs$Aom_Osa, drop = TRUE) |> swap() |> coalesce_contigs()
Bar_Nor <- gbs$Bar_Nor |> swap() |>
  splitSeqLevel("scaffold_3", 700924) |>
  splitSeqLevel("scaffold_8", 1110680) |>
  scaffoldByFlipAndMerge(scafs$Nor_Bar) |>
  coalesce_contigs() |> swap(sort = TRUE)

dsList6 <- list(
    Kume = KumChr2 |> swap() |> plyranges::filter(seqnames == 'Chr2', seqnames(query) == 'chr2') |> gr2dna_seg(),
    Okinawa = c(
      KumChr2           |> plyranges::filter(seqnames == 'chr2', seqnames(query) == 'Chr2') |> granges(),
      Aom_Oki           |> plyranges::filter(seqnames == 'Chr2', seqnames(query) == 'chr2') |> granges()
      ) |> reduce() |> gr2dna_seg(),
    Aomori = c(
      Aom_Oki |> swap() |> plyranges::filter(seqnames == 'Chr2', seqnames(query) == 'chr2') |> granges(),
      Aom_Osa |> swap() |> plyranges::filter(seqnames == 'Chr2', seqnames(query) == 'Chr2') |> granges()
      ) |> reduce() |> gr2dna_seg(),
    Osaka = c(
      Aom_Osa           |> plyranges::filter(seqnames == 'Chr2', seqnames(query) == 'Chr2') |> granges(),
      coa$Osa_Bar       |> plyranges::filter(seqnames == 'Chr2', seqnames(query) == 'Chr2') |> granges()
      ) |> reduce() |> gr2dna_seg(),
    Barcelona = c(
      coa$Bar_Osa       |> plyranges::filter(seqnames == 'Chr2', seqnames(query) == 'Chr2') |> granges(),
      Bar_Nor           |> plyranges::filter(seqnames == 'Chr2', seqnames(query) == 'Chr2') |> granges()
      ) |> reduce() |> gr2dna_seg(),
    Bergen = Bar_Nor |> swap() |> plyranges::filter(seqnames == 'Chr2', seqnames(query) == 'Chr2') |> gr2dna_seg()
)

compList6 <- list(
    Oki_Kum = KumChr2 |> swap() |> plyranges::filter(seqnames == 'Chr2', seqnames(query) == 'chr2') |> gb2comp(),
    Aom_Oki = Aom_Oki           |> plyranges::filter(seqnames == 'chr2', seqnames(query) == 'Chr2') |> gb2comp(),
    Osa_Aom = Aom_Osa |> swap() |> plyranges::filter(seqnames == 'Chr2', seqnames(query) == 'Chr2') |> gb2comp(),
    Osa_Bar = coa$Osa_Bar       |> plyranges::filter(seqnames == 'Chr2', seqnames(query) == 'Chr2') |> gb2comp(),
    Bar_Nor = Bar_Nor           |> plyranges::filter(seqnames == 'Chr2', seqnames(query) == 'Chr2') |> gb2comp()
)

dsList6$Kume$col <- dsList6$Kume$fill <- dsList6$Okinawa$col <- dsList6$Okinawa$fill <-
  dsList6$Aomori$col <- dsList6$Aomori$fill <-
  dsList6$Osaka$col <- dsList6$Osaka$fill <- dsList6$Barcelona$col <- dsList6$Barcelona$fill <-
  dsList6$Bergen$col <- dsList6$Bergen$fill <- "#A6D854"

compList6$Oki_Kum$color <- compList6$Aom_Oki$color <- compList6$Osa_Aom$color <-
  compList6$Osa_Bar$color <- compList6$Bar_Nor$color <- "#D4EACC"

compList6$Oki_Kum$col <- ifelse(compList6$Oki_Kum$col == "darksalmon", "#D4EACC", "#00A08E")
compList6$Aom_Oki$col <- ifelse(compList6$Aom_Oki$col == "darksalmon", "#D4EACC", "#00A08E")
compList6$Osa_Aom$col <- ifelse(compList6$Osa_Aom$col == "darksalmon", "#D4EACC", "#00A08E")
compList6$Osa_Bar$col <- ifelse(compList6$Osa_Bar$col == "darksalmon", "#D4EACC", "#00A08E")
compList6$Bar_Nor$col <- ifelse(compList6$Bar_Nor$col == "darksalmon", "#D4EACC", "#00A08E")

genoPlotR::plot_gene_map(dsList6, compList6, dna_seg_scale = FALSE,
                         tree = ade4::newick2phylog("((Kume:1,Okinawa:1):2,((Aomori:1,Osaka:1):1,(Barcelona:1,Bergen:1):1):1);"),
                         main = "Chromosome 2 in six Oikopleura genome assemblies")

Plot chr2 in four species

We chose chromosome 2 because it has Hox4.

Parallel plot

dsList4 <- list(
    KUM = KumChr2 |> swap() |> plyranges::filter(seqnames == 'Chr2', seqnames(query) == 'chr2') |> gr2dna_seg(),
    OKI = KumChr2           |> plyranges::filter(seqnames == 'chr2', seqnames(query) == 'Chr2') |> gr2dna_seg(),
    OSA = coa$Osa_Bar |> plyranges::filter(seqnames == 'Chr2', seqnames(query) == 'Chr2') |> gr2dna_seg(),
    BAR = coa$Bar_Osa |> plyranges::filter(seqnames == 'Chr2', seqnames(query) == 'Chr2') |> gr2dna_seg()
)

compList4 <- list(
    Oki_Kum = KumChr2 |> swap() |> plyranges::filter(seqnames == 'Chr2', seqnames(query) == 'chr2') |> gb2comp(),
    Oki_Osa = coa$Oki_Osa |> plyranges::filter(seqnames == 'chr2', seqnames(query) == 'Chr2') |> gb2comp(),
    Osa_Bar = coa$Osa_Bar |> plyranges::filter(seqnames == 'Chr2', seqnames(query) == 'Chr2') |> gb2comp()
  )

dsList4$KUM$col <- dsList4$KUM$fill <- dsList4$OKI$col <- dsList4$OKI$fill <-
  dsList4$OSA$col <- dsList4$OSA$fill <- dsList4$BAR$col <- dsList4$BAR$fill <-
  "#A6D854"

compList4$Oki_Kum$color <- compList4$Oki_Osa$color <- compList4$Osa_Bar$color <- "#D4EACC"

compList4$Oki_Kum$col <- ifelse(compList4$Oki_Kum$col == "darksalmon", "#D4EACC", "#00A08E")
compList4$Osa_Bar$col <- ifelse(compList4$Osa_Bar$col == "darksalmon", "#D4EACC", "#00A08E")
compList4$Oki_Osa$col <- ifelse(compList4$Oki_Osa$col == "darksalmon", "#D4EACC", "#00A08E")


genoPlotR::plot_gene_map(dsList4, compList4, dna_seg_scale = FALSE,
                         tree = ade4::newick2phylog(addRoot(treeNode(treeNode("OKI", "KUM"), treeNode("OSA", "BAR")))),
                         main = "Chromosome 2 in four Oikopleura genome assemblies")

Plot chr2 in five species

We chose chromosome 2 because it has Hox4.

Parallel plot

Aom_Osa <- scaffoldByFlipAndMerge(gbs$Osa_Aom |> swap(), scafs$Aom_Osa, drop = TRUE) |> swap() |> coalesce_contigs()
Aom_Oki <- scaffoldByFlipAndMerge(gbs$Oki_Aom |> swap(), scafs$Aom_Osa, drop = TRUE) |> swap() |> coalesce_contigs()

dsList5 <- list(
    KUM = KumChr2 |> swap() |> plyranges::filter(seqnames == 'Chr2', seqnames(query) == 'chr2') |> gr2dna_seg(),
    OKI = KumChr2           |> plyranges::filter(seqnames == 'chr2', seqnames(query) == 'Chr2') |> gr2dna_seg(),
    AOM = Aom_Osa |> swap() |> plyranges::filter(seqnames == 'Chr2', seqnames(query) == 'Chr2') |> gr2dna_seg(),
    OSA = coa$Osa_Bar |> plyranges::filter(seqnames == 'Chr2', seqnames(query) == 'Chr2') |> gr2dna_seg(),
    BAR = coa$Bar_Osa |> plyranges::filter(seqnames == 'Chr2', seqnames(query) == 'Chr2') |> gr2dna_seg()
)

compList5 <- list(
    Oki_Kum = KumChr2 |> swap() |> plyranges::filter(seqnames == 'Chr2', seqnames(query) == 'chr2') |> gb2comp(),
    Aom_Oki = Aom_Oki |> swap() |> plyranges::filter(seqnames == 'Chr2', seqnames(query) == 'chr2') |> gb2comp(),
    Osa_Aom = Aom_Osa |> plyranges::filter(seqnames == 'Chr2', seqnames(query) == 'Chr2') |> gb2comp(),
    Osa_Bar = coa$Osa_Bar |> plyranges::filter(seqnames == 'Chr2', seqnames(query) == 'Chr2') |> gb2comp()
  )

dsList5$KUM$col <- dsList5$KUM$fill <- dsList5$OKI$col <- dsList5$OKI$fill <-
  dsList5$AOM$col <- dsList5$AOM$fill <-
  dsList5$OSA$col <- dsList5$OSA$fill <- dsList5$BAR$col <- dsList5$BAR$fill <-
  "#A6D854"

compList5$Oki_Kum$color <- compList5$Aom_Oki$color <- compList5$Osa_Aom$color <-  compList5$Osa_Bar$color <- "#D4EACC"

compList5$Oki_Kum$col <- ifelse(compList5$Oki_Kum$col == "darksalmon", "#D4EACC", "#00A08E")
compList5$Aom_Oki$col <- ifelse(compList5$Aom_Oki$col == "darksalmon", "#D4EACC", "#00A08E")
compList5$Osa_Aom$col <- ifelse(compList5$Osa_Aom$col == "darksalmon", "#D4EACC", "#00A08E")
compList5$Osa_Bar$col <- ifelse(compList5$Osa_Bar$col == "darksalmon", "#D4EACC", "#00A08E")


genoPlotR::plot_gene_map(dsList5, compList5, dna_seg_scale = FALSE,
                         tree = ade4::newick2phylog(addRoot(treeNode(treeNode("OKI", "KUM"), treeNode(treeNode("OSA", "AOM"), "BAR")))),
                         main = "Chromosome 2 in five Oikopleura genome assemblies")

Strand randomisation indexes

These numbers were added to the plot in Figure 1B.

chr2Long <-  \(gb) plyranges::filter(gb, seqnames %in% c("chr2", "Chr2"), seqnames(query) %in% c("chr2", "Chr2"), Arm == "long",  query$Arm == "long")
chr2short <- \(gb) plyranges::filter(gb, seqnames %in% c("chr2", "Chr2"), seqnames(query) %in% c("chr2", "Chr2"), Arm == "short", query$Arm == "short")
chr2both <- \(gb) plyranges::filter(gb, seqnames %in% c("chr2", "Chr2"), seqnames(query) %in% c("chr2", "Chr2"))

KumChr2 <- GenomicBreaks::flagLongShort(KumChr2, longShort$OKI2018.I69)
KumChr2$query$Arm <- Rle("long")
KumChr2$query$Arm[
  end(KumChr2$query) <= (cumsum(seqlengths(coa$Oki_Kum$query)[scafs$Kum_Oki$Chr2$contig]) -1) ["contig_16_1"] &
    seqnames(KumChr2) == "chr2" &
    seqnames(KumChr2$query) == "Chr2"
  ] <- "short"

Aom_Osa <- GenomicBreaks::flagLongShort(Aom_Osa, longShort$OSKA2016v1.9)
Aom_Osa$query <- GenomicBreaks::flagLongShort(
  Aom_Osa$query,
  GRanges(c("Chr2:1-5523357", "Chr2:5523357-12906126"), Type = c("short", "long")))

Aom_Oki <- GenomicBreaks::flagLongShort(Aom_Oki, longShort$OKI2018.I69)
Aom_Oki$query <- GenomicBreaks::flagLongShort(
  Aom_Oki$query,
  GRanges(c("Chr2:1-5523357", "Chr2:5523357-12906126"), Type = c("short", "long")))


Bar_Nor <- GenomicBreaks::flagLongShort(Bar_Nor, longShort$Bar2.p4)
Bar_Nor$query <- GenomicBreaks::flagLongShort(
  Bar_Nor$query,
  GRanges(c("Chr2:1-4525974", "Chr2:4525975-12906790"), Type = c("short", "long")))

SRI_Both_Strands <- \(gb) mean(c(strand_randomisation_index(gb)
                                ,strand_randomisation_index(swap(gb))))

(SRIs <- c(
  Kum_Chr2_long  = KumChr2 |> chr2Long()  |> SRI_Both_Strands(),
  Kum_Chr2_short = KumChr2 |> chr2short() |> SRI_Both_Strands(),
  Kum_Chr2_both  = KumChr2 |> chr2both()  |> SRI_Both_Strands(),
  
  Oki_Aom_long   = Aom_Oki |> chr2Long()  |> SRI_Both_Strands(),
  Oki_Aom_short  = Aom_Oki |> chr2short() |> SRI_Both_Strands(),
  Oki_Aom_both   = Aom_Oki |> chr2both()  |> SRI_Both_Strands(),
  
  Osa_Aom_long   = Aom_Osa |> chr2Long()  |> SRI_Both_Strands(),
  Osa_Aom_short  = Aom_Osa |> chr2short() |> SRI_Both_Strands(),
  Osa_Aom_both   = Aom_Osa |> chr2both()  |> SRI_Both_Strands(),

  Oki_Osa_long   = coa$Oki_Osa |> chr2Long() |> SRI_Both_Strands(),
  Osa_Oki_long   = coa$Osa_Oki |> chr2Long() |> SRI_Both_Strands(),

  Oki_Osa_short  = coa$Oki_Osa |> chr2short() |> SRI_Both_Strands(),
  Osa_Oki_short  = coa$Osa_Oki |> chr2short() |> SRI_Both_Strands(),

  Oki_Osa_both   = coa$Oki_Osa |> chr2both() |> SRI_Both_Strands(),
  Osa_Oki_both   = coa$Osa_Oki |> chr2both() |> SRI_Both_Strands(),

  Osa_Bar_long   = coa$Osa_Bar |> chr2Long() |> SRI_Both_Strands(),
  Bar_Osa_long   = coa$Bar_Osa |> chr2Long() |> SRI_Both_Strands(),

  Osa_Bar_short  = coa$Osa_Bar |> chr2short() |> SRI_Both_Strands(),
  Bar_Osa_short  = coa$Bar_Osa |> chr2short() |> SRI_Both_Strands(),

  Osa_Bar_both   = coa$Osa_Bar |> chr2both() |> SRI_Both_Strands(),
  Bar_Osa_both   = coa$Bar_Osa |> chr2both() |> SRI_Both_Strands(),
  
  Bar_Nor_short  = Bar_Nor     |> chr2short() |> SRI_Both_Strands(),
  Bar_Nor_long   = Bar_Nor     |> chr2Long()  |> SRI_Both_Strands()
))

##  Kum_Chr2_long Kum_Chr2_short  Kum_Chr2_both   Oki_Aom_long  Oki_Aom_short 
##    0.832774687    0.762407551    0.807347070    0.007713088    0.014947894 
##   Oki_Aom_both   Osa_Aom_long  Osa_Aom_short   Osa_Aom_both   Oki_Osa_long 
##    0.020490460    0.762052760    0.169998327    0.509978155    0.013253234 
##   Osa_Oki_long  Oki_Osa_short  Osa_Oki_short   Oki_Osa_both   Osa_Oki_both 
##    0.017958605    0.020211761    0.019965884    0.016624847    0.014163168 
##   Osa_Bar_long   Bar_Osa_long  Osa_Bar_short  Bar_Osa_short   Osa_Bar_both 
##    0.158432788    0.159058114    0.018673220    0.016156226    0.108829940 
##   Bar_Osa_both  Bar_Nor_short   Bar_Nor_long 
##    0.105527771    0.980679790    0.967169963

roundMean <- \(x) round(mean(SRIs[x]), 2)
data.frame(
  short = c(
    Kum_Oki = roundMean(c("Kum_Chr2_short")),
    Oki_Aom = roundMean(c("Oki_Aom_short")),
    Aom_Osa = roundMean(c("Osa_Aom_short")),
    Osa_Bar = roundMean(c("Osa_Bar_short", "Bar_Osa_short")),
    Bar_Nor = roundMean(c("Bar_Nor_short"))
  ),
  long = c(
    Kum_Oki = roundMean(c("Kum_Chr2_long")),
    Oki_Aom = roundMean(c("Oki_Aom_long")),
    Aom_Osa = roundMean(c("Osa_Aom_long")),
    Osa_Bar = roundMean(c("Osa_Bar_long",  "Bar_Osa_long")),
    Bar_Nor = roundMean(c("Bar_Nor_long"))
  )
)

##         short long
## Kum_Oki  0.76 0.83
## Oki_Aom  0.01 0.01
## Aom_Osa  0.17 0.76
## Osa_Bar  0.02 0.16
## Bar_Nor  0.98 0.97

Plot pairs of chromosome 1s.

plotApairOfChrs(coa$Oki_Bar, "chr1", main = "Oki vs Bar")

plotApairOfChrs(coa$Oki_Osa, "chr1", main = "Oki vs Osa")

plotApairOfChrs(coa$Osa_Oki, "Chr1", main = "Osa vs Oki")

plotApairOfChrs(coa$Osa_Bar, "Chr1", main = "Osa vs Bar")

plotApairOfChrs(coa2$Osa_Bar, "Chr1", main = "Osa vs Bar (double-collapsed")

Scrambling of a 1-megabase region.

x <- subsetByOverlaps(coa2$Oki_Osa, granges(coa2$Oki_Bar)) |> subset(width > 1e5)
y <- subsetByOverlaps(coa2$Oki_Bar, granges(coa2$Oki_Osa)) |> subset(width > 1e5)
findOverlapPairs(x,y)

## Pairs object with 4 pairs and 0 metadata columns:
##                          first                   second
##                      <GBreaks>                <GBreaks>
##   [1] chr2:10664980-10829335:+ chr2:10664980-10828981:+
##   [2] chr2:13895789-14003399:- chr2:13895789-14003408:-
##   [3]  PAR:15193293-15358116:-  PAR:15193294-15358116:-
##   [4]  XSR:10090052-10210973:-  XSR:10090052-10210972:-

subsetByOverlaps(coa2$Oki_Osa, gaps(coa2$Oki_Bar)) |> subset(width > 1e5)

## GBreaks object with 16 ranges and 6 metadata columns:
##        seqnames            ranges strand |                  query      Arm
##           <Rle>         <IRanges>  <Rle> |              <GRanges> <factor>
##    [1]     chr2   5825747-5966560      + |   Chr2:5465216-5578318     long
##    [2]     chr2 10361302-10481638      + | Chr2:11648925-11718071     long
##    [3]     chr2 10664980-10829335      + |   Chr2:5679693-5828385     long
##    [4]     chr2 13895789-14003399      - | Chr2:11294781-11373503     long
##    [5]     chr2 14726918-14844516      + |   Chr2:8440297-8537610     long
##    ...      ...               ...    ... .                    ...      ...
##   [12]      XSR   7236669-7346658      + |    XSR:4093395-4195157      XSR
##   [13]      XSR   7543498-7653200      + |    XSR:3606737-3707501      XSR
##   [14]      XSR   8709632-8820503      + |    XSR:7297396-7413239      XSR
##   [15]      XSR   8929901-9075791      - |    XSR:7506741-7641724      XSR
##   [16]      XSR 10090052-10210973      - |  XSR:10484001-10612402      XSR
##                                  rep   repOvlp            transcripts
##                      <CharacterList> <integer>                  <Rle>
##    [1]        tandem,unknown,rnd,...      5240 g5554.t1;g5556.t1;g5..
##    [2]        tandem,unknown,rnd,...     11135 g6889.t1;g6890.t1;g6..
##    [3] rnd,unknown,LowComplexity,...      5389 g7009.t1;g7010.t1;g7..
##    [4]        rnd,unknown,tandem,...      6725 g7918.t1;g7922.t1;g7..
##    [5]        tandem,rnd,unknown,...      9346 g8164.t1;g8165.t1;g8..
##    ...                           ...       ...                    ...
##   [12]        tandem,rnd,unknown,...      2161 g15405.t1;g15406.t1;..
##   [13]        tandem,rnd,unknown,...      5241 g15508.t1;g15509.t1;..
##   [14]      rnd,tandem,LowComplexity      1409 g15864.t1;g15865.t1;..
##   [15] unknown,rnd,LowComplexity,...      3812 g15934.t1;g15935.t1;..
##   [16]  LowComplexity,rnd,tandem,...      1737 g16292.t1;g16293.t1;..
##               flag
##        <character>
##    [1]        <NA>
##    [2]        <NA>
##    [3]        <NA>
##    [4]        <NA>
##    [5]        <NA>
##    ...         ...
##   [12]         Tra
##   [13]        <NA>
##   [14]        <NA>
##   [15]        <NA>
##   [16]        <NA>
##   -------
##   seqinfo: 19 sequences from OKI2018.I69 genome

ROI <- GRanges("chr2:10000000-11000000")

a <- coa$Oki_Osa |> subsetByOverlaps(ROI) |> plyranges::filter(seqnames == 'chr2', seqnames(query) == 'Chr2')
b <- coa$Oki_Bar |> subsetByOverlaps(ROI) |> plyranges::filter(seqnames == 'chr2', seqnames(query) == 'Chr2')
c <- coa$Bar_Osa |> subsetByOverlaps(range(b$query))                    |> plyranges::filter(seqnames == 'Chr2', seqnames(query) == 'Chr2')

dsList <- list(
  OSA = swap(a) |> gr2dna_seg(),
  OKI = a |> gr2dna_seg(),
  BAR = swap(b) |> gr2dna_seg(),
  Osa = swap(c) |> gr2dna_seg()
)

compList <- list(
  a |> swap() |> gb2comp(),
  b |> gb2comp(),
  c |> gb2comp()
)

genoPlotR::plot_gene_map(dsList, compList, dna_seg_scale=TRUE)

Ciona species

plotApairOfChrs(coa2$Ply_Ros, "BNJZ01000001.1", main = "Ciona intestinalis Plymouth vs Roscoff")

plotApairOfChrs(coa2$Ply_Rob, "BNJZ01000001.1", main = "Ciona intestinalis Plymouth vs Ciona robusta")

Unfortunately, C. savignyi’s genome assembly is too fragmented. Here is a plot with the largest fragment.

plotApairOfChrs(coa2$Ply_Sav, "BNJZ01000001.1", main = "Ciona intestinalis Plymouth vs Ciona savigny")

Session information

sessionInfo()

## R version 4.3.1 (2023-06-16)
## Platform: x86_64-pc-linux-gnu (64-bit)
## Running under: Debian GNU/Linux 12 (bookworm)
## 
## Matrix products: default
## BLAS:   /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.11.0 
## LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.11.0
## 
## locale:
##  [1] LC_CTYPE=C.UTF-8       LC_NUMERIC=C           LC_TIME=C.UTF-8       
##  [4] LC_COLLATE=C.UTF-8     LC_MONETARY=C.UTF-8    LC_MESSAGES=C.UTF-8   
##  [7] LC_PAPER=C.UTF-8       LC_NAME=C              LC_ADDRESS=C          
## [10] LC_TELEPHONE=C         LC_MEASUREMENT=C.UTF-8 LC_IDENTIFICATION=C   
## 
## time zone: Etc/UTC
## tzcode source: system (glibc)
## 
## attached base packages:
## [1] stats4    stats     graphics  grDevices utils     datasets  methods  
## [8] base     
## 
## other attached packages:
##  [1] BSgenome.Oidioi.genoscope.OdB3_1.0.0   
##  [2] BSgenome.Oidioi.OIST.AOM.5.5f_1.0.1    
##  [3] BSgenome.Oidioi.OIST.KUM.M3.7f_1.0.1   
##  [4] BSgenome.Oidioi.OIST.Bar2.p4_1.0.1     
##  [5] BSgenome.Oidioi.OIST.OSKA2016v1.9_1.0.0
##  [6] BSgenome.Oidioi.OIST.OKI2018.I69_1.0.1 
##  [7] OikScrambling_5.0.0                    
##  [8] ggplot2_3.4.3                          
##  [9] GenomicBreaks_0.14.2                   
## [10] BSgenome_1.68.0                        
## [11] rtracklayer_1.60.0                     
## [12] Biostrings_2.68.1                      
## [13] XVector_0.40.0                         
## [14] GenomicRanges_1.52.0                   
## [15] GenomeInfoDb_1.36.1                    
## [16] IRanges_2.34.1                         
## [17] S4Vectors_0.38.1                       
## [18] BiocGenerics_0.46.0                    
## 
## loaded via a namespace (and not attached):
##   [1] splines_4.3.1               BiocIO_1.10.0              
##   [3] bitops_1.0-7                tibble_3.2.1               
##   [5] R.oo_1.25.0                 XML_3.99-0.14              
##   [7] rpart_4.1.19                lifecycle_1.0.3            
##   [9] rprojroot_2.0.3             lattice_0.20-45            
##  [11] MASS_7.3-58.2               backports_1.4.1            
##  [13] magrittr_2.0.3              Hmisc_5.1-0                
##  [15] sass_0.4.7                  rmarkdown_2.23             
##  [17] jquerylib_0.1.4             yaml_2.3.7                 
##  [19] plotrix_3.8-2               DBI_1.1.3                  
##  [21] CNEr_1.36.0                 minqa_1.2.5                
##  [23] RColorBrewer_1.1-3          ade4_1.7-22                
##  [25] abind_1.4-5                 zlibbioc_1.46.0            
##  [27] purrr_1.0.2                 R.utils_2.12.2             
##  [29] RCurl_1.98-1.12             nnet_7.3-18                
##  [31] pracma_2.4.2                GenomeInfoDbData_1.2.10    
##  [33] gdata_2.19.0                annotate_1.78.0            
##  [35] pkgdown_2.0.7               codetools_0.2-19           
##  [37] DelayedArray_0.26.7         tidyselect_1.2.0           
##  [39] shape_1.4.6                 lme4_1.1-34                
##  [41] matrixStats_1.0.0           base64enc_0.1-3            
##  [43] GenomicAlignments_1.36.0    jsonlite_1.8.7             
##  [45] mitml_0.4-5                 Formula_1.2-5              
##  [47] survival_3.5-3              iterators_1.0.14           
##  [49] systemfonts_1.0.5           foreach_1.5.2              
##  [51] tools_4.3.1                 ragg_1.2.5                 
##  [53] Rcpp_1.0.11                 glue_1.6.2                 
##  [55] gridExtra_2.3               pan_1.8                    
##  [57] xfun_0.40                   MatrixGenerics_1.12.2      
##  [59] EBImage_4.42.0              dplyr_1.1.3                
##  [61] withr_2.5.1                 fastmap_1.1.1              
##  [63] boot_1.3-28.1               fansi_1.0.5                
##  [65] digest_0.6.33               R6_2.5.1                   
##  [67] mice_3.16.0                 textshaping_0.3.7          
##  [69] colorspace_2.1-0            GO.db_3.17.0               
##  [71] gtools_3.9.4                poweRlaw_0.70.6            
##  [73] jpeg_0.1-10                 RSQLite_2.3.1              
##  [75] weights_1.0.4               R.methodsS3_1.8.2          
##  [77] utf8_1.2.3                  tidyr_1.3.0                
##  [79] generics_0.1.3              data.table_1.14.8          
##  [81] httr_1.4.7                  htmlwidgets_1.6.2          
##  [83] S4Arrays_1.0.5              pkgconfig_2.0.3            
##  [85] gtable_0.3.4                blob_1.2.4                 
##  [87] htmltools_0.5.6.1           fftwtools_0.9-11           
##  [89] plyranges_1.20.0            scales_1.2.1               
##  [91] Biobase_2.60.0              png_0.1-8                  
##  [93] knitr_1.44                  heatmaps_1.24.0            
##  [95] rstudioapi_0.15.0           tzdb_0.4.0                 
##  [97] reshape2_1.4.4              rjson_0.2.21               
##  [99] checkmate_2.2.0             nlme_3.1-162               
## [101] nloptr_2.0.3                cachem_1.0.8               
## [103] stringr_1.5.0               KernSmooth_2.23-20         
## [105] parallel_4.3.1              genoPlotR_0.8.11           
## [107] foreign_0.8-84              AnnotationDbi_1.62.2       
## [109] restfulr_0.0.15             desc_1.4.2                 
## [111] pillar_1.9.0                grid_4.3.1                 
## [113] vctrs_0.6.3                 jomo_2.7-6                 
## [115] xtable_1.8-4                cluster_2.1.4              
## [117] htmlTable_2.4.1             evaluate_0.22              
## [119] readr_2.1.4                 cli_3.6.1                  
## [121] locfit_1.5-9.8              compiler_4.3.1             
## [123] Rsamtools_2.16.0            rlang_1.1.1                
## [125] crayon_1.5.2                plyr_1.8.8                 
## [127] fs_1.6.3                    stringi_1.7.12             
## [129] BiocParallel_1.34.2         munsell_0.5.0              
## [131] tiff_0.1-11                 glmnet_4.1-7               
## [133] Matrix_1.5-3                hms_1.1.3                  
## [135] bit64_4.0.5                 KEGGREST_1.40.0            
## [137] SummarizedExperiment_1.30.2 broom_1.0.5                
## [139] memoise_2.0.1               bslib_0.5.1                
## [141] bit_4.0.5

Charles Plessy

06 November, 2023

Introduction

Load R pacakges and data

Load pacakges

Phylogenetic cladogram

Plot chr2 in six species

Parallel plot

Plot chr2 in four species

Parallel plot

Plot chr2 in five species

Parallel plot

Strand randomisation indexes

Plot pairs of chromosome 1s.

Scrambling of a 1-megabase region.

Ciona species

Session information