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Assembly Stats

our_genomes = c(
  "Myotis_auriculus",
  "Myotis_californicus",
  "Myotis_occultus",
  "Myotis_lucifugus",
  "Myotis_yumanensis",
  "Myotis_volans",
  "Myotis_velifer",
  "Myotis_evotis",
  "Myotis_thysanodes"
)
assembly_stats <- read_tsv("../data/assembly_stats/all_assembly_stats.contigs.tsv", col_names = c("genomeName", "stat", "v1", "v2")) %>% 
  mutate(contig = str_detect(genomeName, "contig")) %>% 
  filter(str_detect(genomeName, "M_|mmyo|\\.chr", negate=T)) %>%
  filter(str_detect(genomeName, "mMyo.+1(?!_unmasked)", negate=T)) %>%
  separate(genomeName, c("name", "scaffold"), sep="\\.") %>% 
  arrange(name, contig) %>% 
  select(-scaffold) %>% 
  mutate(name=name %>% str_remove("_unmasked"))
assembly_stats <- read_tsv('../data/assembly_stats/all_assembly_stats.cleaned.tsv')
Rows: 30552 Columns: 5
── Column specification ────────────────────────────────────────────────────────
Delimiter: "\t"
chr (2): name, stat
dbl (2): v1, v2
lgl (1): contig

ℹ Use `spec()` to retrieve the full column specification for this data.
ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
meta <- read_tsv("../data/chiropteraGenomes-20230427.tsv") %>% 
  mutate(`Organism Name` = `Organism Name` %>% str_replace_all(" ", "_"))
Rows: 52 Columns: 33
── Column specification ────────────────────────────────────────────────────────
Delimiter: "\t"
chr (19): Assembly Accession, Assembly Name, Organism Name, Organism Infrasp...
dbl (12): Assembly Stats Total Sequence Length, Assembly Stats Contig N50, A...
lgl  (2): Organism Infraspecific Names Strain, Organism Infraspecific Names ...

ℹ Use `spec()` to retrieve the full column specification for this data.
ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
meta.origin <- meta %>% 
  select(name=`Organism Name`, Origin=Group, Citation) %>% 
  group_by(name) %>% 
  mutate(
    Origin = ifelse(Origin %in% c('Zoonomia', 'Bat1K', 'DNAZoo', 'CCGP'), Origin, 'Other')
  ) %>% 
  bind_rows(assembly_stats %>% filter(str_detect(name, "mMyo")) %>% select(name) %>% distinct %>% mutate(Origin="This Paper", Citation = "This Paper", name = name %>% str_remove("_unmasked")))

assembly_stats.meta <- assembly_stats %>% 
  left_join(meta.origin, by="name") %>% 
  replace_na(list(Origin="Other"))%>% mutate(
    species = name %>% 
      str_replace("mMyoAui.*", "Myotis_auriculus") %>% 
      str_replace("mMyoCai.*", "Myotis_californicus") %>% 
      str_replace("mMyoOcc.*", "Myotis_occultus") %>% 
      str_replace("mMyoLuc.*", "Myotis_lucifugus") %>% 
      str_replace("mMyoYum.*", "Myotis_yumanensis") %>% 
      str_replace("mMyoVol.*", "Myotis_volans") %>% 
      str_replace("mMyoVel.*", "Myotis_velifer") %>% 
      str_replace("mMyoEvo.*", "Myotis_evotis") %>% 
      str_replace("mMyoThy.*", "Myotis_thysanodes") %>% 
      str_replace("_T2T","") %>% 
      str_replace("myoLuc2", "Myotis_lucifugus")
  )

assembly_stats.meta[str_detect(assembly_stats.meta$name, "T2T"),"Origin"] <- "T2T"

Table

table.auNG <- assembly_stats.meta %>% 
  filter(stat=='auNG') %>% 
  arrange(v2) %>% 
  mutate(v2=scales::label_comma()(v2),
         species= species %>% str_replace_all('_', " ")) %>%
  select(-v1, -contig, -Citation, -name) %>% 
  select(Species=species, everything()) %>% 
  dplyr::rename(auNG='v2')
table.LG50 <- assembly_stats.meta %>% 
  filter(stat=='LGx', v1==50) %>% 
  arrange(v2) %>% 
  mutate(v2=scales::label_comma()(v2),
         species= species %>% str_replace_all('_', " ")) %>%
  select(-v1, -contig, -Citation, -name) %>% 
  select(Species=species, everything()) %>% 
  dplyr::rename(LG50='v2')
table.NG50 <- assembly_stats.meta %>% 
  filter(stat=='NGx', v1==50) %>% 
  arrange(desc(v2)) %>% 
  mutate(v2=scales::label_comma()(v2),
         species= species %>% str_replace_all('_', " ")) %>%
  select(-v1, -contig, -Citation, -name) %>% 
  select(Species=species, everything()) %>% 
  dplyr::rename(NG50='v2')

## TODO:
# table.NScaff <- assembly_stats.meta %>% 
#   filter(stat=='N', v1=='Scaffold') %>% 
#   arrange(desc(v2)) %>% 
#   mutate(v2=scales::label_comma()(v2),
#          species= species %>% str_replace_all('_', " ")) %>%
#   select(-v1, -contig, -Citation, -name) %>% 
#   select(species, everything()) %>% 
#   dplyr::rename(Scaffolds='v2')
# table.NGap <- assembly_stats.meta %>% 
#   filter(stat=='N', v1=='Gap') %>% 
#   arrange(desc(v2)) %>% 
#   mutate(v2=scales::label_comma()(v2),
#          species= species %>% str_replace_all('_', " ")) %>%
#   select(-v1, -contig, -Citation, -name) %>% 
#   select(species, everything()) %>% 
#   dplyr::rename(Gaps='v2')
# table.NST2T <- assembly_stats.meta %>% 
#   filter(stat=='N', v1=='Scaffolds_T2T') %>% 
#   arrange(desc(v2)) %>% 
#   mutate(v2=scales::label_comma()(v2),
#          species= species %>% str_replace_all('_', " ")) %>%
#   select(-v1, -contig, -Citation, -name) %>% 
#   select(species, everything()) %>% 
#   dplyr::rename(Scaffolds_T2T='v2')
# table.NCT2T <- assembly_stats.meta %>% 
#   arrange(desc(v2)) %>% 
#   mutate(v2=scales::label_comma()(v2),
#          species= species %>% str_replace_all('_', " ")) %>%
#   select(-v1, -contig, -Citation, -name) %>% 
#   select(species, everything()) %>% 
#   dplyr::rename(Complete_Scaffolds='v2')

table.stats <- table.auNG %>%
  # full_join(table.NScaff) %>% 
  # full_join(table.NGap) %>% 
  # full_join(table.NST2T) %>% 
  # full_join(table.NCT2T) %>% 
  full_join(table.NG50) %>% 
  full_join(table.LG50)
Joining with `by = join_by(Species, stat, Origin)`
Joining with `by = join_by(Species, stat, Origin)`

Notes about the tree

In order to get TimeTree to play nicely with the phylogeny, a few changes were needed: - Murina aurata feae (replaced with Murina aurata) - Pteropus pselaphon (replaced with Pteropus mariannus) - Miniopterus schreibersii (replace with Miniopterus schreibersii orianae) - Myotis occultus (replaced with Myotis lucifugus lucifugus) - Myotis lucifugus (replaced with Myotis lucifugus carissima) - Hipposideros pendleburyi (replaced with Hipposideros turpis) - TimetreeV5 has split Eptesicus and broken its nomenclature/link to NCBI, so you can’t find “Eptesicus fuscus” anymore. Instead, you have to look for all of Chiroptera or Vespertilliodinae and then look for Eptesicus fuscus hispaniolae.

If you do all these changes, then undo the changes in post, you get this tree. Note that it was very annoying to splice the two trees together by eye so avoid needing to redo this.

tr <- treeio::read.newick("../data/trees/TimeTree.org/genomeSpecies.timetree.nwk")

# setdiff(tr$tip.label, assembly_stats.meta$species)
# setdiff(assembly_stats.meta$species, tr$tip.label)

NGx curves

plot.NGx <- assembly_stats.meta %>% 
  filter(stat == "NGx",
         contig==T
         ) %>% 
  ggplot(aes(x=v1, y=v2, color=Origin, group=name)) + 
  labs(x="NGx", y = "bp", title = "Contig Contiguity") + 
  geom_point() + 
  geom_line() + 
  ylim(1e4,NA) + 
  scale_color_brewer(palette = "Dark2") + 
  # scale_y_log10(limits=c(1e0,NA)) +
  # scale_y_continuous(limits=c(1e0,NA)) +
  theme_pubclean() + 
  labs_pubr() + 
  theme(legend.position = "bottom")
plot.NGx
Warning: Removed 850 rows containing missing values (`geom_point()`).
Warning: Removed 850 rows containing missing values (`geom_line()`).

Version Author Date
d0ca892 docmanny 2023-12-22
3d9fd9c docmanny 2023-12-15
5848dd7 Juan M Vazquez (docmanny) 2023-01-31 
col.source <- c(
  "This Paper" = "#FFBA08",
  Bat1K = "#B33951",
  T2T = "#d1b1c8",
  Zoonomia = "#4357AD",
  Other = "#6f7c12"
)

plot.NGx.altCol.log <- assembly_stats.meta %>% 
  mutate(Origin = Origin %>% factor(levels=names(col.source))) %>% 
  filter(stat == "NGx",
         contig==T
         ) %>% 
  ggplot(aes(x=v1, y=v2, color=Origin, group=name)) + 
  labs(x="NGx", y = "bp", title = "Contig Contiguity") + 
  # geom_point() + 
  geom_line(linewidth=0.5) + 
  scale_y_log10(lim=c(1e4,NA))+
  scale_color_manual(values=col.source) + 
  theme_pubclean() + 
  labs_pubr() + 
  theme(legend.position = "bottom")
plot.NGx.altCol.log
Warning: Removed 850 rows containing missing values (`geom_line()`).

Version Author Date
d0ca892 docmanny 2023-12-22
3d9fd9c docmanny 2023-12-15 
plot.NGx.altCol <- assembly_stats.meta %>% 
  mutate(Origin = Origin %>% factor(levels=names(col.source))) %>% 
  filter(stat == "NGx",
         contig==T
         ) %>% 
  ggplot(aes(x=v1, y=v2, color=Origin, group=name)) + 
  labs(x="NGx", y = "bp", title = "Contig Contiguity") + 
  # geom_point() + 
  geom_line(linewidth=0.5) + 
  ylim(1e4,NA) +
  scale_color_manual(values=col.source) + 
  theme_pubclean() + 
  labs_pubr() + 
  theme(legend.position = "bottom")
plot.NGx.altCol
Warning: Removed 850 rows containing missing values (`geom_line()`).

Version Author Date
d0ca892 docmanny 2023-12-22
3d9fd9c docmanny 2023-12-15 
plot.NGx.altCol %>% ggsave(plot=., filename = "../output/NGx_curves.pdf", width = 6, height = 3.71, dpi=900, units = "in")
assembly_stats.plotme <- assembly_stats.meta %>% 
  mutate(Origin = Origin %>% factor(levels=names(col.source))) %>% 
  filter(stat == "NGx",
         contig==T
         )
plot.NGx.altCol.t2tzoo <- assembly_stats.plotme %>% 
  ggplot(aes(x=v1, y=v2, color=Origin, group=name)) + 
  labs(x="NGx", y = "bp", title = "Contig Contiguity") + 
  # geom_point() + 
  geom_line(
    data=assembly_stats.plotme %>% filter(Origin %in% c("T2T", "Zoonomia")),
    linewidth=0.5
  ) + 
  ylim(1e4,NA) +
  scale_color_manual(values=col.source) + 
  theme_pubclean() + 
  labs_pubr() + 
  theme(legend.position = "bottom")
plot.NGx.altCol.t2tzoo
Warning: Removed 333 rows containing missing values (`geom_line()`).

Version Author Date
d0ca892 docmanny 2023-12-22
3d9fd9c docmanny 2023-12-15 
plot.NGx.altCol.t2tzoo %>% ggsave(plot=., filename = "../output/NGx_curves_onlyT2TZoonomia.pdf", width = 6, height = 3.71, dpi=900, units = "in")

auNG

plot.auNG <- assembly_stats.meta %>% 
  filter(stat == "auNG",
         contig==T
         ) %>% 
  arrange(desc(v2)) %>% 
  mutate(name = factor(name, levels = name %>% unique)) %>% 
  ggplot(aes(x=v2, y=name, color=Origin)) + 
  labs(x="auNG", y = "Assembly", title = "auNG") + 
  geom_point() + 
  scale_color_brewer(palette = "Dark2") + 
  # scale_y_log10(limits=c(1e0,NA)) +
  # scale_y_continuous(limits=c(1e0,NA)) +
  theme_pubclean() + 
  labs_pubr() + 
  theme(legend.position = "bottom")
plot.auNG

Version Author Date
d0ca892 docmanny 2023-12-22
3d9fd9c docmanny 2023-12-15
5848dd7 Juan M Vazquez (docmanny) 2023-01-31

Tree plus auNG

auNG <- assembly_stats.meta %>% 
  filter(stat == "auNG",
         contig==T
         ) %>% 
  select(species, Origin, v2, v1) %>% 
  rename(label=species, auNG=v2, genomeSize=v1) %>% 
  filter(!(str_detect(label, "lucifugus") & Origin=="Other")) %>% 
  # a bug lead to an accidental dup when there was both a contig and a scaffold
  group_by(label, Origin) %>% 
  filter(auNG==max(auNG)) %>% 
  ungroup
  

color_scale_origin = RColorBrewer::brewer.pal(n=auNG %>% pull(Origin) %>% unique %>% length, name="Dark2") %>% set_names(., auNG %>% pull(Origin) %>% unique)

# tr.auNG <- full_join(tr,auNG)

## Sometimes I hate ggtree
nodes_ourgenomes <- tr %>% 
  as_tibble %>% 
  filter(label %in% our_genomes) %>% 
  select(label, node) %>% 
  deframe()
! # Invaild edge matrix for <phylo>. A <tbl_df> is returned.
p.tr.auNG <- tr %>% 
  ggtree() + 
  geom_tiplab(
    aes(
      subset = (node %in% nodes_ourgenomes)
    ),
    align = T,
    fontface="bold"
    ) +
  geom_tiplab(
    aes(
      subset = !(node %in% nodes_ourgenomes)
    ),
    align = T
    ) +
  xlim_tree(c(NA,250)) +
  geom_facet(
    panel = "auNG (bar)",
    data = auNG,
    geom = geom_col,
    mapping=aes(
      # x = log(1),
      x = log(auNG),
      color=Origin,
      fill=Origin
    ),
    orientation = 'y',
    width = .6
  )+
  geom_facet(
    panel = "auNG (point)", 
    data = auNG, 
    geom = geom_point, 
    mapping=aes(
      # x = log(1),
      x = log(auNG),
      color=Origin,
      fill=Origin
    ), 
    size=2
  )+
  theme_tree2() +
  scale_color_manual("Origin", values = color_scale_origin) +
  scale_fill_manual("Origin", values = color_scale_origin) +
  # geom_facet(panel = "Genome Size", data = auNG %>% select(label, genomeSize, Origin), geom = geom_point, 
  #              mapping=aes(x = genomeSize, color=Origin))+ 
  theme(legend.position = "bottom")
ℹ invalid tbl_tree object. Missing column: parent,node.
ℹ invalid tbl_tree object. Missing column: parent,node.
ℹ invalid tbl_tree object. Missing column: parent,node.
ℹ invalid tbl_tree object. Missing column: parent,node.
p.tr.auNG

Version Author Date
d0ca892 docmanny 2023-12-22
3d9fd9c docmanny 2023-12-15
5848dd7 Juan M Vazquez (docmanny) 2023-01-31 
auNG.fancy <- auNG %>% 
  mutate(
    label_fancy = sapply(label, . %>% if_else(. %in% our_genomes, str_c("**",.,"**"), .)) %>% 
      str_remove("_mesoamericanus") %>% 
      str_replace_all("_", " ")
  )
angle_rotate <- function(angle){
    # subset1 <- "(angle < 90 | angle > 270)"
    # subset2 <- "(angle >= 90 & angle <=270)"
    if (angle < 90 | angle > 270){
      return(angle)
    } else {
      return(angle+180)
    }
}
h_readjust <- function(angle){
    if (angle < 90 | angle > 270){
      return(0)
    } else {
      return(1)
    }
}

p.tr.auNG.circ <-
  tr %>%
  ggtree(layout = "fan", open.angle=180) +
  xlim_tree(c(NA,100))+ 
  geom_fruit(
    data = auNG.fancy,
    geom = geom_col,
    mapping=aes(
      y= label,
      x = log(auNG),
      color=Origin,
      fill=Origin
    ),
    orientation = 'y',
    width = .6
  ) +
  geom_fruit(
    data = auNG.fancy,
    geom = geom_richtext, 
    mapping = aes(
      y=label,
      label=label_fancy,
      color=Origin,
      angle=sapply(angle,angle_rotate),
      hjust=sapply(angle,h_readjust)
    ),
    fill = NA, 
    label.color = NA, 
    label.padding = grid::unit(rep(0, 4), "pt"),
    
  ) + 
  scale_color_manual("Origin", values = color_scale_origin, guide="none") +
  scale_fill_manual("Origin", values = color_scale_origin,
                    guide = guide_legend(nrow = 2, ncol=6, title.position = "left")) +
  theme(legend.position = c(0.6,0.3), plot.margin = unit(c(4,0,0,0),"cm"))
Scale for y is already present.
Adding another scale for y, which will replace the existing scale.
ℹ invalid tbl_tree object. Missing column: parent,node.

ℹ invalid tbl_tree object. Missing column: parent,node.

ℹ invalid tbl_tree object. Missing column: parent,node.

ℹ invalid tbl_tree object. Missing column: parent,node.
p.tr.auNG.circ

Version Author Date
d0ca892 docmanny 2023-12-22
3d9fd9c docmanny 2023-12-15
5848dd7 Juan M Vazquez (docmanny) 2023-01-31 
species_color = ggsci::pal_d3(palette = "category20")(length(our_genomes)+1) %>% 
  set_names(., c(our_genomes, "Other"))

species_color["Myotis_evotis"] = "#17BECFFF"
species_color["Other"] = "#7F7F7FFF"

auNG.fancy.color <- auNG.fancy %>% 
  mutate(color_me = sapply(label, . %>% ifelse(. %in% our_genomes, ., "Other")))
p.tr.auNG.circ.altcolor <-
  tr %>%
  ggtree(layout = "fan", open.angle=180) +
  xlim_tree(c(NA,100))+ 
  # geom_fruit_list(
    geom_fruit(
      data = auNG.fancy.color,
      geom = geom_col,
      mapping=aes(
        y= label,
        x = log(auNG),
        color=color_me,
        fill=color_me
      ),
      orientation = 'y',
      width = .6
    ) + 
    geom_fruit(
      data = auNG.fancy.color,
      geom = geom_richtext, 
      mapping = aes(
        y=label,
        label=label_fancy,
        color=color_me,
        angle=sapply(angle,angle_rotate),
        hjust=sapply(angle,h_readjust)
      ),
      fill = NA, 
      label.color = NA, 
      # offset=0.2,
      label.padding = grid::unit(rep(0,4), "pt"),
    ) + 
  # ) +
  scale_color_manual("Origin", values = species_color, guide="none") +
  scale_fill_manual("Origin", values = species_color, guide="none") +
  theme(plot.margin = unit(c(4,0,0,0),"cm"))
Scale for y is already present.
Adding another scale for y, which will replace the existing scale.
ℹ invalid tbl_tree object. Missing column: parent,node.

ℹ invalid tbl_tree object. Missing column: parent,node.

ℹ invalid tbl_tree object. Missing column: parent,node.

ℹ invalid tbl_tree object. Missing column: parent,node.
p.tr.auNG.circ.altcolor

Version Author Date
d0ca892 docmanny 2023-12-22
3d9fd9c docmanny 2023-12-15
5848dd7 Juan M Vazquez (docmanny) 2023-01-31 
t2t.base = p.tr.auNG.circ.altcolor$data %>% filter(label == 'Homo_sapiens') %>% pull(x)
! # Invaild edge matrix for <phylo>. A <tbl_df> is returned.
! # Invaild edge matrix for <phylo>. A <tbl_df> is returned.
t2t.bartop = p.tr.auNG.circ.altcolor$layers[[4]]$data %>% filter(label == 'Homo_sapiens') %>% pull(new_xtmp) +
  p.tr.auNG.circ.altcolor$layers[[4]]$data %>% filter(label == 'Homo_sapiens') %>% pull(x)
t2t.start = min(p.tr.auNG.circ.altcolor$data$y)
t2t.end = max(p.tr.auNG.circ.altcolor$data$y)

p.tr.auNG.circ.altcolor.withLine <- p.tr.auNG.circ.altcolor + 
  geom_segment(
    aes(
      x = t2t.base + t2t.bartop,
      xend = t2t.base + t2t.bartop,
      y = t2t.start, 
      yend = t2t.end
    )
  )

Updated Phylo

tr.536 <- read.tree('../data/trees/536Mammals-rooted-nodeNames.nwk')

tr.536$tip.label <- tr.536$tip.label %>% 
            str_replace('Canis_lupus_familiaris', 'Canis_familiaris') #%>% 
            # 

auNG.fancy.color$label <- auNG.fancy.color$label %>% 
  str_replace('Murina_aurata_feae', 'Murina_aurata') %>% 
  str_replace('Pteronotus_parnellii_mesoamericanus', 'Pteronotus_parnellii')
  
t.tr.536 <- tr.536 %>% as_tibble

node.chiroptera = t.tr.536%>% filter(label=='Chiroptera') %>% pull(node)
! # Invaild edge matrix for <phylo>. A <tbl_df> is returned.
tipnodes.chiroptera = tidytree::offspring(
  tr.536, 
  .node=node.chiroptera, 
  type = 'tips'
)

tipnodes.chiroptera <- t.tr.536 %>% 
    filter(node %in% tipnodes.chiroptera) %>% 
    pull(label)
! # Invaild edge matrix for <phylo>. A <tbl_df> is returned.
tips = c(
  # t.tr.536 %>% 
  #   filter(node %in% tipnodes.chiroptera) %>% 
  #   pull(label),
  tipnodes.chiroptera,
  "Homo_sapiens",
  "Mus_musculus",
  "Canis_familiaris",
  "Bos_taurus"
)

tr.genomes <- tr.536 %>% 
  keep.tip(
    tips
  )
p.trNew.auNG.circ.altcolor <-
  tr.genomes %>%
  ggtree(layout = "fan", open.angle=180, branch.length = 'none') +
  # xlim_tree(c(NA,10))+ 
  # geom_fruit_list(
    geom_fruit(
      data = auNG.fancy.color,
      geom = geom_col,
      mapping=aes(
        y= label,
        x = log(auNG),
        color=color_me,
        fill=color_me
      ),
      orientation = 'y',
      width = .6
    ) + 
    geom_fruit(
      data = auNG.fancy.color,
      geom = geom_richtext, 
      mapping = aes(
        y=label,
        label=label_fancy,
        color=color_me,
        angle=sapply(angle,angle_rotate),
        hjust=sapply(angle,h_readjust)
      ),
      fill = NA, 
      label.color = NA,
      fontface='italic',
      size=8/.pt,
      # offset=0.2,
      label.padding = grid::unit(rep(0,4), "pt"),
    ) + 
  # ) +
  scale_color_manual("Origin", values = species_color, guide="none") +
  scale_fill_manual("Origin", values = species_color, guide="none") +
  theme(plot.margin = unit(c(4,0,0,0),"cm"))
Scale for y is already present.
Adding another scale for y, which will replace the existing scale.
ℹ invalid tbl_tree object. Missing column: parent,node.

ℹ invalid tbl_tree object. Missing column: parent,node.

ℹ invalid tbl_tree object. Missing column: parent,node.

ℹ invalid tbl_tree object. Missing column: parent,node.
t2t.base = p.trNew.auNG.circ.altcolor$data %>% filter(label == 'Homo_sapiens') %>% pull(x)
! # Invaild edge matrix for <phylo>. A <tbl_df> is returned.
! # Invaild edge matrix for <phylo>. A <tbl_df> is returned.
t2t.bartop = p.trNew.auNG.circ.altcolor$layers[[3]]$data %>% filter(label == 'Homo_sapiens') %>% pull(new_xtmp) +0.6#+   p.trNew.auNG.circ.altcolor$layers[[3]]$data %>% filter(label == 'Homo_sapiens') %>% pull(x)
t2t.start = min(p.trNew.auNG.circ.altcolor$data$y)
t2t.end = max(p.trNew.auNG.circ.altcolor$data$y)

p.trNew.auNG.circ.altcolor.withLine <- p.trNew.auNG.circ.altcolor + 
  geom_segment(
    aes(
      x = t2t.base + t2t.bartop,
      xend = t2t.base + t2t.bartop,
      y = t2t.start, 
      yend = t2t.end
    ),
    linewidth=0.1, 
    # lty='dashed'
  )

p.trNew.auNG.circ.altcolor.withLine

Version Author Date
d0ca892 docmanny 2023-12-22 
# g <- ggplotGrob(p.trNew.auNG.circ.altcolor.withLine)

p.trNew.auNG.circ.altcolor.withLine %>% 
  ggsave(
    filename = '../output/subfigs/phylo_auNG_circ_col_withLine.pdf',
    plot= ., 
    width = 7.5, 
    height = 4, 
    units = 'in', 
    dpi = 300
  )

sessionInfo()
R version 4.3.1 (2023-06-16)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 22.04.3 LTS

Matrix products: default
BLAS:   /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.10.0 
LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.10.0

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: America/La_Paz
tzcode source: system (glibc)

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
 [1] ragg_1.2.5        gridExtra_2.3     ggsci_3.0.0       ggtext_0.1.2     
 [5] ggtreeExtra_1.8.1 tidytree_0.4.5    ggtree_3.6.2      patchwork_1.1.3  
 [9] ggpubr_0.6.0      magrittr_2.0.3    ape_5.7-1         lubridate_1.9.2  
[13] forcats_1.0.0     stringr_1.5.0     dplyr_1.1.3       purrr_1.0.2      
[17] readr_2.1.4       tidyr_1.3.0       tibble_3.2.1      ggplot2_3.4.3    
[21] tidyverse_2.0.0  

loaded via a namespace (and not attached):
 [1] tidyselect_1.2.0   farver_2.1.1       fastmap_1.1.1      lazyeval_0.2.2    
 [5] promises_1.2.1     digest_0.6.33      timechange_0.2.0   lifecycle_1.0.3   
 [9] compiler_4.3.1     rlang_1.1.1        sass_0.4.7         tools_4.3.1       
[13] utf8_1.2.3         yaml_2.3.7         knitr_1.44         ggsignif_0.6.4    
[17] labeling_0.4.3     bit_4.0.5          RColorBrewer_1.1-3 xml2_1.3.5        
[21] aplot_0.2.1        abind_1.4-5        workflowr_1.7.1    withr_2.5.0       
[25] grid_4.3.1         fansi_1.0.5        git2r_0.32.0       colorspace_2.1-0  
[29] scales_1.2.1       cli_3.6.1          crayon_1.5.2       rmarkdown_2.25    
[33] treeio_1.25.4      generics_0.1.3     rstudioapi_0.15.0  tzdb_0.4.0        
[37] commonmark_1.9.0   cachem_1.0.8       parallel_4.3.1     ggplotify_0.1.2   
[41] vctrs_0.6.3        yulab.utils_0.1.0  jsonlite_1.8.7     carData_3.0-5     
[45] car_3.1-2          gridGraphics_0.5-1 hms_1.1.3          bit64_4.0.5       
[49] rstatix_0.7.2      magick_2.8.1       systemfonts_1.0.4  ggnewscale_0.4.9  
[53] jquerylib_0.1.4    glue_1.6.2         stringi_1.7.12     gtable_0.3.4      
[57] later_1.3.1        munsell_0.5.0      pillar_1.9.0       htmltools_0.5.6   
[61] R6_2.5.1           textshaping_0.3.6  rprojroot_2.0.3    vroom_1.6.3       
[65] evaluate_0.21      lattice_0.21-8     markdown_1.8       backports_1.4.1   
[69] gridtext_0.1.5     memoise_2.0.1      broom_1.0.5        httpuv_1.6.11     
[73] ggfun_0.1.3        bslib_0.5.1        Rcpp_1.0.11        nlme_3.1-163      
[77] whisker_0.4.1      xfun_0.40          fs_1.6.3           pkgconfig_2.0.3