Last updated: 2022-11-15

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assembly_stats <- read_tsv("~/projects/MyotisGenomeAssembly/data/chiroptera.contig.assembly_stats.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)
Rows: 27336 Columns: 4
── Column specification ────────────────────────────────────────────────────────
Delimiter: "\t"
chr (2): genomeName, stat
dbl (2): v1, v2

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.
our_genomes = c(
  "Myotis_auriculus",
  "Myotis_californicus",
  "Myotis_occultus",
  "Myotis_lucifugus",
  "Myotis_yumanensis",
  "Myotis_volans",
  "Myotis_velifer",
  "Myotis_evotis",
  "Myotis_thysanodes"
)
meta <- read_tsv("../data/chiroptera_genomes_20220627.tsv") %>% 
  filter(!is.na(`Assembly BioProject Lineage Parent Accessions`)) %>% 
  mutate(`Organism Name` = `Organism Name` %>% str_replace_all(" ", "_"))
Rows: 129 Columns: 29
── Column specification ────────────────────────────────────────────────────────
Delimiter: "\t"
chr  (15): Assembly Name, Assembly Accession, Organism Name, Organism Infras...
dbl  (10): Annotation BUSCO Complete, Annotation BUSCO Duplicated, Annotatio...
lgl   (3): Organism Infraspecific Names Strain, Organism Infraspecific Names...
date  (1): Assembly Submission Date

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 %>% 
  filter(str_detect(`Assembly BioProject Lineage Title`, "[Aa]ssembl", negate = T)) %>%
  filter(str_detect(`Assembly BioProject Lineage Title`, "Myotis myotis", negate = T)) %>% 
  filter(str_detect(`Assembly BioProject Lineage Title`, "Pipistrellus", negate = T)) %>% 
  select(name=`Organism Name`, `Assembly BioProject Lineage Title`) %>% 
  group_by(name) %>% 
  summarize(Origin = `Assembly BioProject Lineage Title` %>% unique %>% sort %>%  paste(collapse=",")) %>% 
  mutate(Origin = Origin %>% 
           str_replace("The European Reference Genome Atlas,Vertebrate Genomes Project", "Vertebrate Genomes Project") %>% 
           str_replace("Bat1K Project,Vertebrate Genomes Project", "Bat1K Project") %>% 
           str_replace("Genome sequencing for Pteropus vampyrus", "Other") %>% 
           str_replace("Eptesicus fuscus Genome Sequencing", "Other")
         ) %>% 
  bind_rows(assembly_stats %>% filter(str_detect(name, "mMyo")) %>% select(name) %>% distinct %>% mutate(Origin="This Paper"))

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$name, "T2T"),"Origin"] <- "T2T"
assembly_stats.meta[str_detect(assembly_stats.meta$name, "Yum"),"Origin"] <- "CCGP"
tr <- treeio::read.newick("~/projects/MyotisGenomeAssembly/data/tree/species_timetree2.nwk") %>% 
  ape::drop.tip("Rhinolophus_sinicus")

setdiff(tr$tip.label, assembly_stats.meta$species)
character(0)
setdiff(assembly_stats.meta$species, tr$tip.label)
character(0)
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 697 rows containing missing values (`geom_point()`).
Warning: Removed 697 rows containing missing values (`geom_line()`).

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

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"))

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()


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")

p.tr.auNG

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.
p.tr.auNG.circ

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_point,
      mapping=aes(
        y= label,
        x = log(17.7),
        angle=angle
      ),
      color="black",
      shape = "-",
      size=2,
      vjust = 1,
      hjust = 1
    ),
    geom_fruit(
      data = auNG.fancy.color,
      geom = geom_point,
      mapping=aes(
        y= label,
        x = log(max(auNG)),
        angle=angle
      ),
      color="blue",
      shape = "-",
      size=2,
      vjust = 1,
      hjust = 1
    )
  ) +
  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, 
    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.
Warning in (function (mapping = NULL, data = NULL, stat = "identity", position =
"identity", : Ignoring unknown parameters: `vjust` and `hjust`
Warning in (function (mapping = NULL, data = NULL, stat = "identity", position =
"identity", : Ignoring unknown aesthetics: angle
Warning in (function (mapping = NULL, data = NULL, stat = "identity", position =
"identity", : Ignoring unknown parameters: `vjust` and `hjust`
Warning in (function (mapping = NULL, data = NULL, stat = "identity", position =
"identity", : Ignoring unknown aesthetics: angle
p.tr.auNG.circ.altcolor


sessionInfo()
R version 4.2.2 (2022-10-31)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 20.04.5 LTS

Matrix products: default
BLAS:   /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.9.0
LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.9.0

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

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

other attached packages:
 [1] ggsci_2.9         ggtext_0.1.2      ggtreeExtra_1.8.0 ggtree_3.7.1     
 [5] patchwork_1.1.2   ggpubr_0.4.0      magrittr_2.0.3    forcats_0.5.2    
 [9] stringr_1.4.1     dplyr_1.0.10      purrr_0.3.5       readr_2.1.3      
[13] tidyr_1.2.1       tibble_3.1.8      ggplot2_3.4.0     tidyverse_1.3.2  

loaded via a namespace (and not attached):
 [1] googledrive_2.0.0   ggnewscale_0.4.8    colorspace_2.0-3   
 [4] ggsignif_0.6.4      ellipsis_0.3.2      rprojroot_2.0.3    
 [7] markdown_1.3        fs_1.5.2            aplot_0.1.8        
[10] gridtext_0.1.5      rstudioapi_0.14     farver_2.1.1       
[13] bit64_4.0.5         fansi_1.0.3         lubridate_1.9.0    
[16] xml2_1.3.3          cachem_1.0.6        knitr_1.40         
[19] jsonlite_1.8.3      workflowr_1.7.0     broom_1.0.1        
[22] dbplyr_2.2.1        compiler_4.2.2      httr_1.4.4         
[25] backports_1.4.1     assertthat_0.2.1    fastmap_1.1.0      
[28] lazyeval_0.2.2      gargle_1.2.1        cli_3.4.1          
[31] later_1.3.0         htmltools_0.5.3     tools_4.2.2        
[34] gtable_0.3.1        glue_1.6.2          Rcpp_1.0.9         
[37] carData_3.0-5       cellranger_1.1.0    jquerylib_0.1.4    
[40] vctrs_0.5.0         ape_5.6-2           nlme_3.1-160       
[43] xfun_0.34           rvest_1.0.3         timechange_0.1.1   
[46] lifecycle_1.0.3     renv_0.16.0         rstatix_0.7.0      
[49] googlesheets4_1.0.1 scales_1.2.1        vroom_1.6.0        
[52] hms_1.1.2           promises_1.2.0.1    parallel_4.2.2     
[55] RColorBrewer_1.1-3  yaml_2.3.6          ggfun_0.0.8        
[58] yulab.utils_0.0.5   sass_0.4.2          stringi_1.7.8      
[61] highr_0.9           tidytree_0.4.1      rlang_1.0.6        
[64] pkgconfig_2.0.3     commonmark_1.8.1    evaluate_0.18      
[67] lattice_0.20-45     treeio_1.23.0       labeling_0.4.2     
[70] bit_4.0.4           tidyselect_1.2.0    R6_2.5.1           
[73] magick_2.7.3        generics_0.1.3      DBI_1.1.3          
[76] pillar_1.8.1        haven_2.5.1         withr_2.5.0        
[79] abind_1.4-5         modelr_0.1.9        crayon_1.5.2       
[82] car_3.1-1           utf8_1.2.2          tzdb_0.3.0         
[85] rmarkdown_2.17      grid_4.2.2          readxl_1.4.1       
[88] git2r_0.30.1        reprex_2.0.2        digest_0.6.30      
[91] httpuv_1.6.6        gridGraphics_0.5-1  munsell_0.5.0      
[94] ggplotify_0.1.0     bslib_0.4.1