Last updated: 2021-10-07

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Knit directory: Amphibolis_Posidonia_Comparison/

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library(tidyverse)
-- Attaching packages --------------------------------------- tidyverse 1.3.1 --
v ggplot2 3.3.5     v purrr   0.3.4
v tibble  3.1.5     v dplyr   1.0.7
v tidyr   1.1.4     v stringr 1.4.0
v readr   2.0.2     v forcats 0.5.1
-- Conflicts ------------------------------------------ tidyverse_conflicts() --
x dplyr::filter() masks stats::filter()
x dplyr::lag()    masks stats::lag()
library(cowplot)
theme_set(theme_cowplot())
library(RColorBrewer)
library(patchwork)

Attaching package: 'patchwork'
The following object is masked from 'package:cowplot':

    align_plots
library(UpSetR)
groups <- read_tsv('./data/Orthogroups.tsv') 
Rows: 31136 Columns: 20
-- Column specification --------------------------------------------------------
Delimiter: "\t"
chr (20): Orthogroup, Amphibolis_final.genome.scf.bigger1kbp.all.maker.prote...

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.
names(groups) <- c('Orthogroup', 'A. antarctica', 'A. trichopada', 'B. distachyon', 'C. reinhardtii', 'L. gibba', 'O. sativa', 'P. australis', 'P. patens', 'P. trichocarpa', 'S. moellendorffii', 'S. polyrhiza', 'A. thaliana', 'T. parvula', 'V. vinifera', 'Z. mays', 'Z. muelleri', 'Z. marina', 'O. lucimarinus', 'W. australis')
# for upsetr, we need to know only which OG-groups are shared between species, the actual genes don't matter
per_spec <- groups %>% pivot_longer(-Orthogroup) %>% 
  filter(!is.na(value)) %>% # species not in an orthogroup are still listed, they just have NA genes for this group
  select(-value) # don't need all gene names, speed things up
# now I want the data in this format:
# listInput <- list(one = c(1, 2, 3, 5, 7, 8, 11, 12, 13), two = c(1, 2, 4, 5, 
#   10), three = c(1, 5, 6, 7, 8, 9, 10, 12, 13))
x <- per_spec %>% 
  select(name, Orthogroup) %>% # turn the table around
  deframe() # convert to named vector
mylist <- lapply(split(x, names(x)), unname) # yuck - ugly code to convert the named vector to a list
x <- upset(fromList(mylist), order.by='freq', nsets = length(groups) - 1)
x

Let’s get the species-only cluster numbers

species_specific_orthos <- per_spec %>% 
  group_by(Orthogroup) %>% 
  summarise(counts = length(name)) %>%
  filter(counts == 1)
per_spec %>% 
  filter(Orthogroup %in% species_specific_orthos$Orthogroup) %>% 
  group_by(name) %>% 
  count() %>% 
  arrange(n) %>% 
  knitr::kable()
name n
A. antarctica 74
S. polyrhiza 155
O. lucimarinus 198
L. gibba 267
P. australis 267
T. parvula 273
Z. marina 322
P. trichocarpa 485
A. thaliana 489
B. distachyon 507
Z. muelleri 619
V. vinifera 682
A. trichopada 848
W. australis 1006
C. reinhardtii 1105
Z. mays 1108
S. moellendorffii 1334
O. sativa 1419
P. patens 1568

How many orthogroups are shared between the four seagrasses?

newlist <- mylist[c('A. antarctica', 'Z. marina', 'P. australis', 'Z. muelleri')]

x <- upset(fromList(newlist), order.by='freq', nsets = 4)
x


sessionInfo()
R version 4.1.1 (2021-08-10)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 17134)

Matrix products: default

locale:
[1] LC_COLLATE=English_Australia.1252  LC_CTYPE=English_Australia.1252   
[3] LC_MONETARY=English_Australia.1252 LC_NUMERIC=C                      
[5] LC_TIME=English_Australia.1252    

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

other attached packages:
 [1] UpSetR_1.4.0       patchwork_1.1.1    RColorBrewer_1.1-2 cowplot_1.1.1     
 [5] forcats_0.5.1      stringr_1.4.0      dplyr_1.0.7        purrr_0.3.4       
 [9] readr_2.0.2        tidyr_1.1.4        tibble_3.1.5       ggplot2_3.3.5     
[13] tidyverse_1.3.1    workflowr_1.6.2   

loaded via a namespace (and not attached):
 [1] httr_1.4.2       bit64_4.0.5      vroom_1.5.5      jsonlite_1.7.2  
 [5] modelr_0.1.8     assertthat_0.2.1 highr_0.9        cellranger_1.1.0
 [9] yaml_2.2.1       pillar_1.6.3     backports_1.2.1  glue_1.4.2      
[13] digest_0.6.28    promises_1.2.0.1 rvest_1.0.1      colorspace_2.0-2
[17] htmltools_0.5.2  httpuv_1.6.3     plyr_1.8.6       pkgconfig_2.0.3 
[21] broom_0.7.9      haven_2.4.3      scales_1.1.1     whisker_0.4     
[25] later_1.3.0      tzdb_0.1.2       git2r_0.28.0     generics_0.1.0  
[29] farver_2.1.0     ellipsis_0.3.2   withr_2.4.2      cli_3.0.1       
[33] magrittr_2.0.1   crayon_1.4.1     readxl_1.3.1     evaluate_0.14   
[37] fs_1.5.0         fansi_0.5.0      xml2_1.3.2       tools_4.1.1     
[41] hms_1.1.1        lifecycle_1.0.1  munsell_0.5.0    reprex_2.0.1    
[45] compiler_4.1.1   jquerylib_0.1.4  rlang_0.4.11     grid_4.1.1      
[49] rstudioapi_0.13  labeling_0.4.2   rmarkdown_2.11   gtable_0.3.0    
[53] DBI_1.1.1        R6_2.5.1         gridExtra_2.3    lubridate_1.7.10
[57] knitr_1.36       fastmap_1.1.0    bit_4.0.4        utf8_1.2.2      
[61] rprojroot_2.0.2  stringi_1.7.5    parallel_4.1.1   Rcpp_1.0.7      
[65] vctrs_0.3.8      dbplyr_2.1.1     tidyselect_1.1.1 xfun_0.26