GO enrichment

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Last updated: 2022-02-25

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Knit directory: Amphibolis_Posidonia_Comparison/

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    Untracked:  output/Lost_GO_terms_in_five_species.PlantSpecific.xlsx
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Unstaged changes:
    Deleted:    data/Lost_GO_terms_in_five_species.PlantSpecific.xlsx
    Deleted:    data/Lost_GO_terms_in_five_species.xlsx
    Modified:   data/Lost_present_gene_lists/Genes_lost_in_A_antarctica_not_other_seagrasses.txt
    Modified:   data/Lost_present_gene_lists/Genes_lost_in_P_australis_not_other_seagrasses.txt
    Modified:   data/Lost_present_gene_lists/Genes_lost_in_Z_marina_not_other_seagrasses.txt
    Modified:   data/Lost_present_gene_lists/Genes_lost_in_Z_muelleri_not_other_seagrasses.txt
    Modified:   data/arabidopsis_gene_level_comparison.xlsx
    Modified:   data/arabidopsis_gene_level_comparison_only_losts.xlsx
    Modified:   data/arabidopsis_gene_level_counts.xlsx
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    Deleted:    output/missing_arabidopsis_vs_all_GO.txt.png
    Deleted:    output/missing_posi_vs_all_GO.txt.png
    Deleted:    output/missing_seagrasses_GO.txt.png
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    Deleted:    output/only_seagrasses_GO.txt.png

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These are the previous versions of the repository in which changes were made to the R Markdown (analysis/GOenrichment.Rmd) and HTML (docs/GOenrichment.html) files. If you’ve configured a remote Git repository (see ?wflow_git_remote), click on the hyperlinks in the table below to view the files as they were in that past version.

File	Version	Author	Date	Message
Rmd	61c8f69	Philipp Bayer	2022-02-25	Replace GO enrichment
html	9b59467	Philipp Bayer	2022-02-23	Rewrite Orthofinder analysis
Rmd	ab9a1f6	Philipp Bayer	2022-02-21	add some more changes
html	65d3fa4	Philipp Bayer	2021-12-20	Build site.
Rmd	21f4c6f	Philipp Bayer	2021-12-20	fix tables again, finally :) haha
html	d8ec8d3	Philipp Bayer	2021-12-20	Build site.
Rmd	2fb63eb	Philipp Bayer	2021-12-20	fix tables again, finally :)
html	cf2e045	Philipp Bayer	2021-12-20	Build site.
Rmd	280fc5d	Philipp Bayer	2021-12-20	fix tables again
html	5356e2c	Philipp Bayer	2021-12-20	Build site.
Rmd	9f4be6f	Philipp Bayer	2021-12-20	fix tables
html	7816b8c	Philipp Bayer	2021-12-20	Build site.
Rmd	73bffa4	Philipp Bayer	2021-12-20	add tables
html	c1288a4	Philipp Bayer	2021-12-20	Build site.
Rmd	2691cad	Philipp Bayer	2021-12-20	add tables
html	292db59	Philipp Bayer	2021-10-18	Build site.
Rmd	35aa72f	Philipp Bayer	2021-10-18	wflow_publish(c(“analysis/GOenrichment.Rmd”, “analysis/plotGenes.Rmd”,
Rmd	7e370e9	Philipp Bayer	2021-10-07	Updated GOenrichment
Rmd	95586f9	Philipp Bayer	2021-10-07	Add missing data
html	95586f9	Philipp Bayer	2021-10-07	Add missing data
html	c0db4a5	Philipp Bayer	2021-10-07	Build site.
Rmd	08b28ea	Philipp Bayer	2021-10-07	wflow_publish(files = c("analysis/*"))

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Lost in seagrasses

The GO enrichment does not work well on my laptop so I’m setting this to eval=FALSE and run it on a remote server. The script which writes the input files is a Python script in the scripts/ folder: findClustersUniqueToAquatic.py. This script parses Orthofinder output to pull out genome-specific groups and genes.

# give properly formatted background in format: GO:0005838  GSBRNA2T00088508001;GSBRNA2T00088313001;GSBRNA2T00035842001 
#annAT <- readMappings('BACKGROUND.txt.gz', sep="\t", IDsep=";")
#save(annAT, file='annAtObject.RData')

load('annAtObject.RData')
allgenes <- unique(unlist(annAT))

compare <- function(genelistfile, outname, allgenes, annAT) {
  # give file with your genes of interest, one gene_id per line
  
  mygenes <-scan(genelistfile ,what="")
  geneList <- factor(as.integer(allgenes %in% mygenes))
  names(geneList) <- allgenes
  
  GOdata <-new ("topGOdata", ontology = 'BP', allGenes = geneList, nodeSize = 5, annot=annFUN.GO2genes, GO2genes=annAT)
  # using ClassicCount:
  #test.stat <-new ("classicCount", testStatistic = GOFisherTest, name = "Fisher Test")
  #resultsFisherC <-getSigGroups (GOdata, test.stat)
  # using weight01:
  weight01.fisher <- runTest(GOdata, statistic = "fisher")
  # using ClassicCount:
  # allRes <- GenTable(GOdata, classicFisher= resultsFisherC, topNodes = 30)
  # using weight01:
  allRes <- GenTable(GOdata, classicFisher=weight01.fisher,topNodes=30)#,topNodes=100)
  names(allRes)[length(allRes)] <- "p.value"
  p_values <- score(weight01.fisher)
  adjusted_p <- p.adjust(p_values)
  adjusted_p[adjusted_p < 0.05] %>% enframe() %>% write_csv('data/' + outname)

}

Comparing the three big groups

# all genes shared - this runs out of memory
#compare('Lost_present_gene_lists/Genes_only_in_Aquatics_and_Seagrasses_and_Terrestrials.txt', 'output/GO_results_genes_in_Aquatics_and_Seagrasses_and_Terrestrials.csv', allgenes, annAT)

# Genes in aquatics and seagrasses - IMPORTANT This is NOT the union - this is the intersection!
# Union is below
compare('Lost_present_gene_lists/Genes_only_in_Aquatics_and_Seagrasses.txt', 'output/GO_results_genes_in_Aquatics_and_Seagrasses_NOT_Terrestrials.csv', allgenes, annAT)

# Genes only in aquatics
compare('Lost_present_gene_lists/Genes_only_in_Aquatics.txt', 'output/GO_results_genes_in_Aquatics_NOT_Seagrasses_NOT_Terrestrials.csv', allgenes, annAT)

# Genes only in seagrasses
compare('Lost_present_gene_lists/Genes_only_in_Seagrasses.txt', 'output/GO_results_genes_in_Seagrasses_NOT_Aquatics_NOT_Terrestrials.csv', allgenes, annAT)

# Genes only in terrestrials
compare('Lost_present_gene_lists/Genes_only_in_Terrestrials.txt', 'output/GO_results_genes_in_Terrestrials_NOT_Aquatics_NOT_Seagrasses.csv', allgenes, annAT)

# Genes union of Seagrass and Aquatics
compare('Lost_present_gene_lists/Genes_union_of_Seagrass_and_Aquatics_union.txt', 'output/GO_results_genes_union_Aquatics_and_Seagrasses_NOT_Terrestrials.csv', allgenes, annAT)

Seagrass only comparisons

Now we compare seagrasses within each other.

For the seagrass-only comparisons, I’m using a Seagrass-only background as that makes more biological sense to me.s

# give properly formatted background in format: GO:0005838  GSBRNA2T00088508001;GSBRNA2T00088313001;GSBRNA2T00035842001 
#sannAT <- readMappings('SEAGRASSBACKGROUND.txt', sep="\t", IDsep=";")
#save(sannAT, file='sannAtObject.RData')

load('sannAtObject.RData')
sallgenes <- unique(unlist(sannAT))

lost in seagrasses

compare('Lost_present_gene_lists/Genes_lost_in_A_antarctica_not_other_seagrasses.txt', 'output/GO_results_genes_lost_A_antarctica_not_other_seagrasses.csv', sallgenes, sannAT)

compare('Lost_present_gene_lists/Genes_lost_in_Z_marina_not_other_seagrasses.txt', 'output/GO_results_genes_lost_Z_marina_not_other_seagrasses.csv', sallgenes, sannAT)

compare('Lost_present_gene_lists/Genes_lost_in_P_australis_not_other_seagrasses.txt', 'output/GO_results_genes_lost_P_australis_not_other_seagrasses.csv', sallgenes, sannAT)

compare('Lost_present_gene_lists/Genes_lost_in_Z_muelleri_not_other_seagrasses.txt', 'output/GO_results_genes_lost_Z_muelleri_not_other_seagrasses.csv', sallgenes, sannAT)

Present in seagrasses

compare('Lost_present_gene_lists/Genes_only_in_Z_marina_not_other_seagrasses.txt', 'output/GO_results_genes_only_Z_marina_not_other_seagrasses.csv', sallgenes, sannAT)

compare('Lost_present_gene_lists/Genes_only_in_Z_muelleri_not_other_seagrasses.txt', 'output/GO_results_genes_only_Z_muelleri_not_other_seagrasses.csv', sallgenes, sannAT)

compare('Lost_present_gene_lists/Genes_only_in_P_australis_not_other_seagrasses.txt', 'output/GO_results_genes_only_P_australis_not_other_seagrasses.csv', sallgenes, sannAT)

compare('Lost_present_gene_lists/Genes_only_in_A_antarctica_not_other_seagrasses.txt', 'output/GO_results_genes_only_A_antarctica_not_other_seagrasses.csv', sallgenes, sannAT)

Alright now we have all these different GO terms in all these files - we can send them to revigo for visualiation and some deduplication!

Revigo

This code is based on http://revigo.irb.hr/CodeExamples/revigo.R.txt

results_list <- list()

for (f in list.files('./output/', pattern='*.csv')){
  filename <- paste('./output/', f, sep='')
  go_and_pvalues <- readChar(filename, file.info(filename)$size)
  go_and_pvalues <- gsub(',', ' ', go_and_pvalues)
  
  httr::POST(
    url = "http://revigo.irb.hr/StartJob.aspx",
    body = list(
      cutoff = "0.7",
      valueType = "pvalue",
     # speciesTaxon = "4577", # zea mays
     #speciesTaxon = '39947', # japonica
     speciesTaxon = '3702', # arabidopsis
      measure = "SIMREL",
      goList = go_and_pvalues
    ),
    # application/x-www-form-urlencoded
    encode = "form"
  ) -> res
  
  dat <- httr::content(res, encoding = "UTF-8")
  
  jobid <- jsonlite::fromJSON(dat,bigint_as_char=TRUE)$jobid
  
  # Check job status
  running <- "1"
  while (running != "0" ) {
      httr::POST(
        url = "http://revigo.irb.hr/QueryJobStatus.aspx",
        query = list( jobid = jobid )
      ) -> res2
      dat2 <- httr::content(res2, encoding = "UTF-8")
      running <- jsonlite::fromJSON(dat2)$running
      Sys.sleep(1)
  }
  
  # Fetch results
  httr::POST(
    url = "http://revigo.irb.hr/ExportJob.aspx",
    query = list(
      jobid = jobid, 
      namespace = "1",
      type = "CSVTable"
    )
  ) -> res3
  
  dat3 <- httr::content(res3, encoding = "UTF-8")
  
  dat3 <- stri_replace_all_fixed(dat3, "\r", "")
  # Now we have a csv table in a string!

  # read_csv does not like the ', ', it wants ','
  dat <- read_csv(gsub(', ', ',', dat3), show_col_types = FALSE) 
  
  # do we even have results?
  if(nrow(dat) == 0){next}
  results_list[[f]] <- dat
  
}

Warning in readChar(filename, file.info(filename)$size): truncating string with
embedded nuls

Warning in readChar(filename, file.info(filename)$size): truncating string with
embedded nuls

Warning in readChar(filename, file.info(filename)$size): truncating string with
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Warning in readChar(filename, file.info(filename)$size): truncating string with
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Warning in readChar(filename, file.info(filename)$size): truncating string with
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Warning in readChar(filename, file.info(filename)$size): truncating string with
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Warning in readChar(filename, file.info(filename)$size): truncating string with
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Warning in readChar(filename, file.info(filename)$size): truncating string with
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Warning in readChar(filename, file.info(filename)$size): truncating string with
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Warning in readChar(filename, file.info(filename)$size): truncating string with
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Warning in readChar(filename, file.info(filename)$size): truncating string with
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Warning in readChar(filename, file.info(filename)$size): truncating string with
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OK we have a list with all results in a big list. Now we can plot!

Making Supplementary Tables for the REVIGO results

Let’s also pull these terms out as tables. Value is the unadjusted p-value (-3.7 = 10 * -3.7)

for( i in names(results_list)) {
  print(i)
  print(results_list[[i]] %>% filter(Eliminated == FALSE) %>% select(TermID, Name, Value) %>% arrange(Value) %>% kbl() %>%  kable_styling())
  cat("\n")
}

[1] “GO_results_genes_in_Aquatics_and_Seagrasses_NOT_Terrestrials.csv”

TermID	Name	Value
GO:0032197	transposition,RNA-mediated	-67.507734
GO:0006278	RNA-dependent DNA biosynthetic process	-49.118091
GO:0090501	RNA phosphodiester bond hydrolysis	-43.436290
GO:0006508	proteolysis	-28.556828
GO:0045747	positive regulation of Notch signaling pathway	-21.348070
GO:0016360	sensory organ precursor cell fate determination	-21.348070
GO:0045314	regulation of compound eye photoreceptor development	-21.348070
GO:0007398	ectoderm development	-21.348070
GO:0035204	negative regulation of lamellocyte differentiation	-21.348070
GO:2000027	regulation of animal organ morphogenesis	-21.236806
GO:0007616	long-term memory	-21.231089
GO:0030718	germ-line stem cell population maintenance	-18.709600
GO:0007422	peripheral nervous system development	-18.628472
GO:0007498	mesoderm development	-18.628472
GO:0030707	ovarian follicle cell development	-17.937024
GO:0033962	P-body assembly	-12.505301
GO:0000290	deadenylation-dependent decapping of nuclear-transcribed mRNA	-10.390740
GO:0008104	protein localization	-8.899044
GO:0001896	autolysis	-8.396837
GO:0043386	mycotoxin biosynthetic process	-8.396837
GO:0010914	positive regulation of sterigmatocystin biosynthetic process	-8.396837
GO:0051260	protein homooligomerization	-7.067176
GO:0008356	asymmetric cell division	-6.018134
GO:0000209	protein polyubiquitination	-5.141380
GO:0010501	RNA secondary structure unwinding	-5.076995
GO:0009062	fatty acid catabolic process	-4.163845
GO:0042306	regulation of protein import into nucleus	-3.362772
GO:0016446	somatic hypermutation of immunoglobulin genes	-3.103944
GO:0010098	suspensor development	-2.948600
GO:0040007	growth	-2.774732
GO:0097164	ammonium ion metabolic process	-2.588258
GO:0019365	pyridine nucleotide salvage	-2.389379
GO:0006657	CDP-choline pathway	-2.045139
GO:0006458	‘de novo’ protein folding	-2.026123
GO:0016560	protein import into peroxisome matrix,docking	-1.985661
GO:0098719	sodium ion import across plasma membrane	-1.614660
GO:1904580	regulation of intracellular mRNA localization	-1.534859
GO:0006970	response to osmotic stress	-1.532272
GO:0046520	sphingoid biosynthetic process	-1.482379
GO:0010555	response to mannitol	-1.441326
GO:0006885	regulation of pH	-1.341458

[1] “GO_results_genes_in_Aquatics_NOT_Seagrasses_NOT_Terrestrials.csv”

TermID	Name	Value
GO:0010025	wax biosynthetic process	-26.626443
GO:0019432	triglyceride biosynthetic process	-25.954024
GO:0048438	floral whorl development	-25.054223
GO:0009753	response to jasmonic acid	-13.955898
GO:0017148	negative regulation of translation	-13.764822
GO:2000117	negative regulation of cysteine-type endopeptidase activity	-12.436518
GO:0006869	lipid transport	-10.654295
GO:0009723	response to ethylene	-10.158676
GO:0090696	post-embryonic plant organ development	-9.654049
GO:0001666	response to hypoxia	-9.070723
GO:0001101	response to acid chemical	-8.606000
GO:0034605	cellular response to heat	-8.228346
GO:0010373	negative regulation of gibberellin biosynthetic process	-7.331038
GO:0010208	pollen wall assembly	-6.453670
GO:0009266	response to temperature stimulus	-6.229266
GO:0010030	positive regulation of seed germination	-6.157498
GO:0006606	protein import into nucleus	-5.868931
GO:0019365	pyridine nucleotide salvage	-5.687459
GO:0042254	ribosome biogenesis	-5.646111
GO:0010220	positive regulation of vernalization response	-5.563470
GO:0006355	regulation of transcription,DNA-templated	-4.209775
GO:0009910	negative regulation of flower development	-3.634419
GO:0048441	petal development	-3.509074
GO:0006396	RNA processing	-3.319062
GO:0090143	nucleoid organization	-3.064675
GO:0009416	response to light stimulus	-2.859747
GO:0010262	somatic embryogenesis	-2.802825
GO:0032353	negative regulation of hormone biosynthetic process	-2.781174
GO:0050821	protein stabilization	-2.655356
GO:0009650	UV protection	-2.631031
GO:0006212	uracil catabolic process	-2.393548
GO:0009093	cysteine catabolic process	-2.271820
GO:0048830	adventitious root development	-2.256427
GO:0009739	response to gibberellin	-1.992537
GO:0042814	monopolar cell growth	-1.754299
GO:0072699	protein localization to cortical microtubule cytoskeleton	-1.754299
GO:0085029	extracellular matrix assembly	-1.708512
GO:0010077	maintenance of inflorescence meristem identity	-1.620899
GO:0055046	microgametogenesis	-1.407736

[1] “GO_results_genes_in_Seagrasses_NOT_Aquatics_NOT_Terrestrials.csv”

TermID	Name	Value
GO:0051603	proteolysis involved in cellular protein catabolic process	-11.456833
GO:0006278	RNA-dependent DNA biosynthetic process	-9.577934
GO:0032197	transposition,RNA-mediated	-9.168511
GO:0033275	actin-myosin filament sliding	-6.682353
GO:0090501	RNA phosphodiester bond hydrolysis	-6.648430
GO:0043007	maintenance of rDNA	-6.455202
GO:0033298	contractile vacuole organization	-5.583611
GO:0032060	bleb assembly	-5.583611
GO:0050982	detection of mechanical stimulus	-5.431629
GO:1900049	regulation of histone exchange	-5.042366
GO:0016131	brassinosteroid metabolic process	-4.909247
GO:1902466	positive regulation of histone H3-K27 trimethylation	-4.579819
GO:0051591	response to cAMP	-4.509703
GO:0001932	regulation of protein phosphorylation	-3.934885
GO:0032989	cellular component morphogenesis	-3.724531
GO:0048578	positive regulation of long-day photoperiodism,flowering	-3.385409
GO:0006468	protein phosphorylation	-3.226314
GO:0080156	mitochondrial mRNA modification	-3.221374
GO:0097193	intrinsic apoptotic signaling pathway	-3.003236
GO:0009048	dosage compensation by inactivation of X chromosome	-2.792735
GO:0090701	specification of plant organ identity	-2.713400
GO:0010022	meristem determinacy	-2.675579
GO:0006971	hypotonic response	-2.372108
GO:0010090	trichome morphogenesis	-2.336224
GO:0051707	response to other organism	-2.284036
GO:0051555	flavonol biosynthetic process	-2.102840
GO:1904872	regulation of telomerase RNA localization to Cajal body	-1.978326
GO:0051127	positive regulation of actin nucleation	-1.905381
GO:0097242	amyloid-beta clearance	-1.718349
GO:0010992	ubiquitin recycling	-1.718349
GO:0010815	bradykinin catabolic process	-1.718349
GO:2001240	negative regulation of extrinsic apoptotic signaling pathway in absence of ligand	-1.641177
GO:0016926	protein desumoylation	-1.543029
GO:0071048	nuclear retention of unspliced pre-mRNA at the site of transcription	-1.532452
GO:0010222	stem vascular tissue pattern formation	-1.487551
GO:0010492	maintenance of shoot apical meristem identity	-1.433920
GO:0048576	positive regulation of short-day photoperiodism,flowering	-1.364131
GO:0043086	negative regulation of catalytic activity	-1.351735
GO:0031154	culmination involved in sorocarp development	-1.309504

[1] “GO_results_genes_in_Terrestrials_NOT_Aquatics_NOT_Seagrasses.csv”

TermID	Name	Value
GO:0051762	sesquiterpene biosynthetic process	-143.501548
GO:0006952	defense response	-117.942439
GO:0010082	regulation of root meristem growth	-108.551199
GO:2000280	regulation of root development	-86.448127
GO:0007165	signal transduction	-73.886537
GO:0046345	abscisic acid catabolic process	-57.837256
GO:0000966	RNA 5’-end processing	-56.420803
GO:0031146	SCF-dependent proteasomal ubiquitin-dependent protein catabolic process	-52.213782
GO:0048509	regulation of meristem development	-51.881994
GO:0045338	farnesyl diphosphate metabolic process	-41.706252
GO:2000026	regulation of multicellular organismal development	-40.141627
GO:0051554	flavonol metabolic process	-37.734717
GO:0009819	drought recovery	-36.208841
GO:0010469	regulation of signaling receptor activity	-36.089822
GO:0090615	mitochondrial mRNA processing	-35.930259
GO:0019756	cyanogenic glycoside biosynthetic process	-35.084917
GO:0080003	thalianol metabolic process	-31.306539
GO:0009617	response to bacterium	-31.074845
GO:0009625	response to insect	-29.065755
GO:0009962	regulation of flavonoid biosynthetic process	-26.749126
GO:0006468	protein phosphorylation	-26.047386
GO:0006885	regulation of pH	-23.177460
GO:0016567	protein ubiquitination	-23.062311
GO:0010618	aerenchyma formation	-21.148233
GO:0045168	cell-cell signaling involved in cell fate commitment	-21.038631
GO:0052544	defense response by callose deposition in cell wall	-19.928674
GO:2000083	negative regulation of L-ascorbic acid biosynthetic process	-19.592316
GO:0000304	response to singlet oxygen	-18.701819
GO:0071368	cellular response to cytokinin stimulus	-17.533700
GO:0045926	negative regulation of growth	-16.846454
GO:1902025	nitrate import	-16.819160
GO:0060307	regulation of ventricular cardiac muscle cell membrane repolarization	-16.402211
GO:0036371	protein localization to T-tubule	-16.095554
GO:0033292	T-tubule organization	-16.095554
GO:0036309	protein localization to M-band	-16.095554
GO:1901021	positive regulation of calcium ion transmembrane transporter activity	-16.095554
GO:0009626	plant-type hypersensitive response	-15.316450
GO:0097185	cellular response to azide	-14.492924
GO:0080027	response to herbivore	-14.021250
GO:0010221	negative regulation of vernalization response	-13.971217
GO:0042742	defense response to bacterium	-13.848529
GO:0080184	response to phenylpropanoid	-13.215717
GO:0009684	indoleacetic acid biosynthetic process	-12.791295
GO:0009871	jasmonic acid and ethylene-dependent systemic resistance,ethylene mediated signaling pathway	-12.418186
GO:0071236	cellular response to antibiotic	-11.827987
GO:0009852	auxin catabolic process	-11.760676
GO:0010942	positive regulation of cell death	-11.630087
GO:0071466	cellular response to xenobiotic stimulus	-11.288199
GO:0071766	Actinobacterium-type cell wall biogenesis	-10.455440
GO:0007166	cell surface receptor signaling pathway	-10.403838
GO:1904526	regulation of microtubule binding	-10.390529
GO:0009611	response to wounding	-10.241320
GO:0009410	response to xenobiotic stimulus	-9.812383
GO:0006812	cation transport	-9.518886
GO:1905255	regulation of RNA binding transcription factor activity	-9.396917
GO:0035024	negative regulation of Rho protein signal transduction	-8.998029
GO:0009914	hormone transport	-8.966261
GO:0010930	negative regulation of auxin mediated signaling pathway	-8.845442
GO:0002213	defense response to insect	-8.830445
GO:0071395	cellular response to jasmonic acid stimulus	-8.620748
GO:0070301	cellular response to hydrogen peroxide	-8.478385
GO:0002011	morphogenesis of an epithelial sheet	-8.038068
GO:0010030	positive regulation of seed germination	-8.035314
GO:0016045	detection of bacterium	-7.948233
GO:0097237	cellular response to toxic substance	-7.664251
GO:1902265	abscisic acid homeostasis	-7.523139
GO:0034394	protein localization to cell surface	-6.648005
GO:0009865	pollen tube adhesion	-6.357568
GO:0006355	regulation of transcription,DNA-templated	-6.326918
GO:0090559	regulation of membrane permeability	-6.145108
GO:0007584	response to nutrient	-6.032889
GO:0009866	induced systemic resistance,ethylene mediated signaling pathway	-6.031631
GO:0010310	regulation of hydrogen peroxide metabolic process	-5.857372
GO:0097167	circadian regulation of translation	-5.774298
GO:0009734	auxin-activated signaling pathway	-5.408543
GO:0003283	atrial septum development	-5.371665
GO:0007267	cell-cell signaling	-5.269003
GO:0009737	response to abscisic acid	-5.143354
GO:0009311	oligosaccharide metabolic process	-5.050193
GO:0010233	phloem transport	-5.045523
GO:0009826	unidimensional cell growth	-4.938939
GO:0010114	response to red light	-4.892294
GO:0071218	cellular response to misfolded protein	-4.859071
GO:0061157	mRNA destabilization	-4.507855
GO:0010438	cellular response to sulfur starvation	-4.191383
GO:0007422	peripheral nervous system development	-4.020084
GO:0031542	positive regulation of anthocyanin biosynthetic process	-3.961486
GO:0002239	response to oomycetes	-3.957108
GO:0015708	silicic acid import across plasma membrane	-3.932028
GO:0006335	DNA replication-dependent chromatin assembly	-3.844884
GO:0032504	multicellular organism reproduction	-3.826316
GO:0009745	sucrose mediated signaling	-3.815288
GO:0035600	tRNA methylthiolation	-3.689252
GO:0001101	response to acid chemical	-3.608320
GO:0009751	response to salicylic acid	-3.586672
GO:1905614	negative regulation of developmental vegetative growth	-3.393833
GO:0032527	protein exit from endoplasmic reticulum	-3.369785
GO:0010305	leaf vascular tissue pattern formation	-3.344485
GO:1902290	positive regulation of defense response to oomycetes	-3.258939
GO:0051513	regulation of monopolar cell growth	-3.182886
GO:0002230	positive regulation of defense response to virus by host	-3.125303
GO:0097503	sialylation	-3.117517
GO:0006898	receptor-mediated endocytosis	-3.067736
GO:0009960	endosperm development	-2.946166
GO:0043086	negative regulation of catalytic activity	-2.893705
GO:0009733	response to auxin	-2.892061
GO:0031347	regulation of defense response	-2.842056
GO:0042177	negative regulation of protein catabolic process	-2.756067
GO:0045314	regulation of compound eye photoreceptor development	-2.705864
GO:0007398	ectoderm development	-2.705864
GO:0045747	positive regulation of Notch signaling pathway	-2.705864
GO:0035204	negative regulation of lamellocyte differentiation	-2.705864
GO:0010150	leaf senescence	-2.704461
GO:0071229	cellular response to acid chemical	-2.695489
GO:0031640	killing of cells of other organism	-2.629273
GO:1903553	positive regulation of extracellular exosome assembly	-2.629137
GO:0044364	disruption of cells of other organism	-2.629137
GO:0048265	response to pain	-2.629137
GO:2000027	regulation of animal organ morphogenesis	-2.615330
GO:0007498	mesoderm development	-2.610391
GO:0048821	erythrocyte development	-2.525503
GO:1905663	positive regulation of telomerase RNA reverse transcriptase activity	-2.437567
GO:0009627	systemic acquired resistance	-2.272801
GO:0009828	plant-type cell wall loosening	-2.257521
GO:0010275	NAD(P)H dehydrogenase complex assembly	-2.187116
GO:1904355	positive regulation of telomere capping	-1.975465
GO:1900745	positive regulation of p38MAPK cascade	-1.870783
GO:0031930	mitochondria-nucleus signaling pathway	-1.675324
GO:0046482	para-aminobenzoic acid metabolic process	-1.654849
GO:0001824	blastocyst development	-1.628424
GO:0071219	cellular response to molecule of bacterial origin	-1.522636
GO:0097366	response to bronchodilator	-1.511918
GO:0002215	defense response to nematode	-1.438176
GO:0042761	very long-chain fatty acid biosynthetic process	-1.415808
GO:0009958	positive gravitropism	-1.402316
GO:0000769	syncytium formation by mitosis without cytokinesis	-1.356437
GO:0045056	transcytosis	-1.355560
GO:0048211	Golgi vesicle docking	-1.355560
GO:0032526	response to retinoic acid	-1.346440
GO:0009218	pyrimidine ribonucleotide metabolic process	-1.324744
GO:0090548	response to nitrate starvation	-1.315645
GO:0006424	glutamyl-tRNA aminoacylation	-1.313120

[1] “GO_results_genes_lost_A_antarctica_not_other_seagrasses.csv”

TermID	Name	Value
GO:0006278	RNA-dependent DNA biosynthetic process	-180.916060
GO:0032197	transposition,RNA-mediated	-175.316613
GO:0090501	RNA phosphodiester bond hydrolysis	-160.989575
GO:0006508	proteolysis	-72.416255
GO:0090305	nucleic acid phosphodiester bond hydrolysis	-55.006996
GO:0009451	RNA modification	-51.871677
GO:0044550	secondary metabolite biosynthetic process	-23.892755
GO:0010726	positive regulation of hydrogen peroxide metabolic process	-18.244993
GO:0080181	lateral root branching	-14.606194
GO:0032350	regulation of hormone metabolic process	-11.320614
GO:0051258	protein polymerization	-10.767659
GO:0071395	cellular response to jasmonic acid stimulus	-10.138487
GO:0016101	diterpenoid metabolic process	-9.758264
GO:0010942	positive regulation of cell death	-9.704042
GO:0044245	polysaccharide digestion	-6.692450
GO:0016081	synaptic vesicle docking	-6.692450
GO:0032260	response to jasmonic acid stimulus involved in jasmonic acid and ethylene-dependent systemic resistance	-6.439823
GO:0051603	proteolysis involved in cellular protein catabolic process	-6.039701
GO:0015695	organic cation transport	-5.617644
GO:0048462	carpel formation	-4.934992
GO:0010337	regulation of salicylic acid metabolic process	-4.452476
GO:0072488	ammonium transmembrane transport	-4.131855
GO:0045962	positive regulation of development,heterochronic	-4.056345
GO:0040007	growth	-3.522516
GO:1900049	regulation of histone exchange	-3.227057
GO:0071289	cellular response to nickel ion	-3.177715
GO:0015709	thiosulfate transport	-3.177715
GO:0033259	plastid DNA replication	-3.177715
GO:0006182	cGMP biosynthetic process	-2.777287
GO:0006032	chitin catabolic process	-2.777287
GO:0007165	signal transduction	-2.454269
GO:0009629	response to gravity	-2.417378
GO:0009694	jasmonic acid metabolic process	-2.381020
GO:0043086	negative regulation of catalytic activity	-2.306902
GO:0080021	response to benzoic acid	-2.299520
GO:0072756	cellular response to paraquat	-2.299520
GO:0071465	cellular response to desiccation	-2.299520
GO:0034265	isopentenyl adenine biosynthetic process	-2.299520
GO:0070562	regulation of vitamin D receptor signaling pathway	-2.278555
GO:0048385	regulation of retinoic acid receptor signaling pathway	-2.278555
GO:0002229	defense response to oomycetes	-2.187161
GO:0006012	galactose metabolic process	-2.057857
GO:0010258	NADH dehydrogenase complex (plastoquinone) assembly	-1.880093
GO:0051707	response to other organism	-1.559465
GO:0034461	uropod retraction	-1.484321
GO:0090284	positive regulation of protein glycosylation in Golgi	-1.465553
GO:0042773	ATP synthesis coupled electron transport	-1.424052
GO:0080143	regulation of amino acid export	-1.421822
GO:0043153	entrainment of circadian clock by photoperiod	-1.421822
GO:0015990	electron transport coupled proton transport	-1.421822
GO:0008347	glial cell migration	-1.366082

[1] “GO_results_genes_lost_P_australis_not_other_seagrasses.csv”

TermID	Name	Value
GO:0009451	RNA modification	-89.911120
GO:0090305	nucleic acid phosphodiester bond hydrolysis	-89.381091
GO:0006278	RNA-dependent DNA biosynthetic process	-20.038600
GO:0032197	transposition,RNA-mediated	-19.701475
GO:0090501	RNA phosphodiester bond hydrolysis	-17.299422
GO:0051603	proteolysis involved in cellular protein catabolic process	-10.112687
GO:0032260	response to jasmonic acid stimulus involved in jasmonic acid and ethylene-dependent systemic resistance	-8.751969
GO:0016081	synaptic vesicle docking	-8.178899
GO:0048462	carpel formation	-6.173514
GO:0006508	proteolysis	-5.348966
GO:0006885	regulation of pH	-4.363572
GO:0080156	mitochondrial mRNA modification	-4.352576
GO:0071602	phytosphingosine biosynthetic process	-4.167583
GO:0009694	jasmonic acid metabolic process	-3.855562
GO:0043086	negative regulation of catalytic activity	-3.708144
GO:0030244	cellulose biosynthetic process	-3.449424
GO:0019761	glucosinolate biosynthetic process	-3.391467
GO:0018008	N-terminal peptidyl-glycine N-myristoylation	-3.253926
GO:0010064	embryonic shoot morphogenesis	-3.253926
GO:0016131	brassinosteroid metabolic process	-3.208332
GO:1902184	negative regulation of shoot apical meristem development	-3.165687
GO:0006812	cation transport	-3.078937
GO:0042273	ribosomal large subunit biogenesis	-2.363144
GO:0010500	transmitting tissue development	-2.323910
GO:0050434	positive regulation of viral transcription	-2.302352
GO:0071289	cellular response to nickel ion	-2.302352
GO:0010208	pollen wall assembly	-2.288990
GO:0042773	ATP synthesis coupled electron transport	-2.166858
GO:0080143	regulation of amino acid export	-2.163578
GO:0043153	entrainment of circadian clock by photoperiod	-2.163578
GO:0015990	electron transport coupled proton transport	-2.163578
GO:0046785	microtubule polymerization	-1.922603
GO:0032461	positive regulation of protein oligomerization	-1.861507
GO:0048658	anther wall tapetum development	-1.861507
GO:0006446	regulation of translational initiation	-1.783246
GO:0097480	establishment of synaptic vesicle localization	-1.778068
GO:0019471	4-hydroxyproline metabolic process	-1.716219
GO:0018401	peptidyl-proline hydroxylation to 4-hydroxy-L-proline	-1.716219
GO:0090284	positive regulation of protein glycosylation in Golgi	-1.640876
GO:0042407	cristae formation	-1.635329
GO:1900140	regulation of seedling development	-1.374861
GO:0052472	modulation by host of symbiont transcription	-1.358014
GO:0010374	stomatal complex development	-1.351927

[1] “GO_results_genes_lost_Z_marina_not_other_seagrasses.csv”

TermID	Name	Value
GO:0009083	branched-chain amino acid catabolic process	-12.099651
GO:1902418	(+)-abscisic acid D-glucopyranosyl ester transmembrane transport	-12.065236
GO:0098660	inorganic ion transmembrane transport	-9.090653
GO:0015700	arsenite transport	-8.216962
GO:1901684	arsenate ion transmembrane transport	-7.927843
GO:0040007	growth	-7.168854
GO:0090284	positive regulation of protein glycosylation in Golgi	-6.355361
GO:0071669	plant-type cell wall organization or biogenesis	-5.783306
GO:0007059	chromosome segregation	-5.267361
GO:0043617	cellular response to sucrose starvation	-4.682327
GO:0007018	microtubule-based movement	-4.630782
GO:0009313	oligosaccharide catabolic process	-4.522609
GO:0090303	positive regulation of wound healing	-4.515170
GO:2000114	regulation of establishment of cell polarity	-4.303925
GO:1902198	3-methylbut-2-enoyl-CoA(4-) metabolic process	-3.727762
GO:1904211	membrane protein proteolysis involved in retrograde protein transport,ER to cytosol	-3.727762
GO:0043007	maintenance of rDNA	-3.677400
GO:1900400	regulation of iron ion import into cell by regulation of transcription from RNA polymerase II promoter	-3.277240
GO:1901255	nucleotide-excision repair involved in interstrand cross-link repair	-3.277240
GO:0008347	glial cell migration	-3.277240
GO:0032508	DNA duplex unwinding	-3.131414
GO:0034260	negative regulation of GTPase activity	-3.043832
GO:0010104	regulation of ethylene-activated signaling pathway	-2.878893
GO:0030837	negative regulation of actin filament polymerization	-2.774984
GO:0097502	mannosylation	-2.734209
GO:1900153	positive regulation of nuclear-transcribed mRNA catabolic process,deadenylation-dependent decay	-2.645697
GO:1900049	regulation of histone exchange	-2.607858
GO:0097193	intrinsic apoptotic signaling pathway	-2.601213
GO:0000913	preprophase band assembly	-2.495797
GO:0016573	histone acetylation	-2.305824
GO:0009556	microsporogenesis	-2.080502
GO:0006075	(1->3)-beta-D-glucan biosynthetic process	-1.868028
GO:0071329	cellular response to sucrose stimulus	-1.827140
GO:0051289	protein homotetramerization	-1.755497
GO:0009624	response to nematode	-1.749373
GO:0106004	tRNA (guanine-N7)-methylation	-1.563561
GO:1900000	regulation of anthocyanin catabolic process	-1.563561
GO:0097242	amyloid-beta clearance	-1.533347
GO:0010992	ubiquitin recycling	-1.533347
GO:0008340	determination of adult lifespan	-1.533347
GO:0010815	bradykinin catabolic process	-1.533347
GO:0010208	pollen wall assembly	-1.374147
GO:0035194	post-transcriptional gene silencing by RNA	-1.312663

[1] “GO_results_genes_lost_Z_muelleri_not_other_seagrasses.csv”

TermID	Name	Value
GO:0051603	proteolysis involved in cellular protein catabolic process	-9.343439
GO:0071482	cellular response to light stimulus	-4.060248
GO:0080156	mitochondrial mRNA modification	-3.977341
GO:0046785	microtubule polymerization	-3.919147
GO:0006624	vacuolar protein processing	-3.194610
GO:0006597	spermine biosynthetic process	-3.169700
GO:1990019	protein storage vacuole organization	-2.561493
GO:0030174	regulation of DNA-dependent DNA replication initiation	-2.463341
GO:0042372	phylloquinone biosynthetic process	-2.463341
GO:0046900	tetrahydrofolylpolyglutamate metabolic process	-1.766281
GO:0070914	UV-damage excision repair	-1.765542
GO:0071332	cellular response to fructose stimulus	-1.444683
GO:0010157	response to chlorate	-1.444683

[1] “GO_results_genes_only_P_australis_not_other_seagrasses.csv”

TermID	Name	Value
GO:0005983	starch catabolic process	-2.055820
GO:0034721	histone H3-K4 demethylation,trimethyl-H3-K4-specific	-1.884385
GO:0046686	response to cadmium ion	-1.754551
GO:0071333	cellular response to glucose stimulus	-1.582738
GO:0030174	regulation of DNA-dependent DNA replication initiation	-1.307768

[1] “GO_results_genes_only_Z_marina_not_other_seagrasses.csv”

TermID	Name	Value
GO:0051603	proteolysis involved in cellular protein catabolic process	-23.445501
GO:0046785	microtubule polymerization	-13.774183
GO:0006624	vacuolar protein processing	-9.895786
GO:1990019	protein storage vacuole organization	-8.591400
GO:0080156	mitochondrial mRNA modification	-7.414447
GO:0010157	response to chlorate	-5.513515
GO:0048281	inflorescence morphogenesis	-4.588824
GO:0032989	cellular component morphogenesis	-4.508650
GO:0090156	cellular sphingolipid homeostasis	-4.494330
GO:0010090	trichome morphogenesis	-4.097280
GO:1901332	negative regulation of lateral root development	-2.847257
GO:0006278	RNA-dependent DNA biosynthetic process	-2.761258
GO:0032197	transposition,RNA-mediated	-2.708915
GO:0010286	heat acclimation	-2.016484
GO:0090709	regulation of timing of plant organ formation	-1.857388
GO:0006537	glutamate biosynthetic process	-1.818101
GO:0090305	nucleic acid phosphodiester bond hydrolysis	-1.818070
GO:0048194	Golgi vesicle budding	-1.775108
GO:0009408	response to heat	-1.548177
GO:0045332	phospholipid translocation	-1.546385
GO:0015770	sucrose transport	-1.318982

[1] “GO_results_genes_only_Z_muelleri_not_other_seagrasses.csv”

TermID	Name	Value
GO:0090284	positive regulation of protein glycosylation in Golgi	-5.506616
GO:0010222	stem vascular tissue pattern formation	-5.047945
GO:0008347	glial cell migration	-4.650340
GO:0090303	positive regulation of wound healing	-4.387055
GO:0040007	growth	-4.373448
GO:1900049	regulation of histone exchange	-4.140205
GO:2000114	regulation of establishment of cell polarity	-3.856587
GO:0043007	maintenance of rDNA	-3.318770
GO:2001240	negative regulation of extrinsic apoptotic signaling pathway in absence of ligand	-2.928272
GO:0046328	regulation of JNK cascade	-2.672143
GO:0080119	ER body organization	-2.146026
GO:0007030	Golgi organization	-1.799156
GO:0034260	negative regulation of GTPase activity	-1.793183
GO:0046459	short-chain fatty acid metabolic process	-1.740640
GO:0006336	DNA replication-independent chromatin assembly	-1.395115

[1] “GO_results_genes_union_Aquatics_and_Seagrasses_NOT_Terrestrials.csv”

TermID	Name	Value
GO:0071577	zinc ion transmembrane transport	-6.945551
GO:0000398	mRNA splicing,via spliceosome	-6.679986
GO:0010252	auxin homeostasis	-4.110544
GO:0006886	intracellular protein transport	-4.096642
GO:0006334	nucleosome assembly	-3.942266
GO:0006487	protein N-linked glycosylation	-2.841110
GO:0009637	response to blue light	-2.750609
GO:0034599	cellular response to oxidative stress	-2.436697
GO:0009658	chloroplast organization	-2.279829
GO:1903508	positive regulation of nucleic acid-templated transcription	-2.028043
GO:0006412	translation	-1.833720
GO:0045454	cell redox homeostasis	-1.787827
GO:0019915	lipid storage	-1.718930
GO:0015770	sucrose transport	-1.566032
GO:0000290	deadenylation-dependent decapping of nuclear-transcribed mRNA	-1.465894
GO:0008333	endosome to lysosome transport	-1.454659
GO:1902358	sulfate transmembrane transport	-1.365088
GO:0009853	photorespiration	-1.311822

Let’s have a look at all of these plots. Manually zooming in leads to ggrepel reloading labels, so on the small scale a lot of these plots don’t have labels.

for(i in names(plot_list)) {
  file_name = paste('output/',  i, '.png', sep='')
  
  cowplot::save_plot(file_name, plot_list[[i]], base_height=6)
  
}

Let me also try and make some patchworks.

# For some reason with this plot the legends aren't correctly collected by patchwork, 
# so I need to manually turn one off
patchy <- (plot_list[["GO_results_genes_in_Terrestrials_NOT_Aquatics_NOT_Seagrasses.csv"]] + theme(legend.position = "none")) /
  plot_list[["GO_results_genes_union_Aquatics_and_Seagrasses_NOT_Terrestrials.csv"]] + plot_layout(guides = 'collect') + plot_annotation(tag_levels = 'A')
patchy

cowplot::save_plot('output/GO_results_terrestrials_vs_union_aquatics_seagrasses.png', patchy, base_height=7)

OK I’ll better make this figure for the seagrasses alone, it’s quite messy this way.

Seagrass-specific loss

Let’s check which GO terms overlap between the 4 seagrasses!

How many shared lost GO-terms are there?

a <- list(`P. australis` = results_list$GO_results_genes_lost_P_australis_not_other_seagrasses.csv$Name,
          `A. antarctica` = results_list$GO_results_genes_lost_A_antarctica_not_other_seagrasses.csv$Name,
          `Z. marina` = results_list$GO_results_genes_lost_Z_marina_not_other_seagrasses.csv$Name,
          `Z. muelleri` = results_list$GO_results_genes_lost_Z_muelleri_not_other_seagrasses.csv$Name)

a_go_ids <- list(`P. australis` = results_list$GO_results_genes_lost_P_australis_not_other_seagrasses.csv$TermID,
          `A. antarctica` = results_list$GO_results_genes_lost_A_antarctica_not_other_seagrasses.csv$TermID,
          `Z. marina` = results_list$GO_results_genes_lost_Z_marina_not_other_seagrasses.csv$TermID,
          `Z. muelleri` = results_list$GO_results_genes_lost_Z_muelleri_not_other_seagrasses.csv$TermID)

plot(venn(a), 
     quantities = TRUE,
     fill = rev(wes_palette("Zissou1", 15, type = 'continuous')),
    alpha = 0.5,
     labels = list(font = 4))

upset(fromList(a), order.by='freq', )

a_no_ara <- list(`P. australis` = results_list$missing_posi_vs_all_GO.txt$Name,
          `A. antarctica` = results_list$missing_amphi_vs_all_GO.txt$Name,
          `Z. marina` = results_list$missing_zmar_vs_all_GO.txt$Name,
          `Z. muelleri` = results_list$missing_zmuel_vs_all_GO.txt$Name)

What are the shared GO-terms in seagrasses, WITHOUT the Ara loss??

Reduce(union, a) %>% enframe() %>% writexl::write_xlsx('./output/Seagrasses_shared_lost_genes.xlsx')

What if we remove Posidonia?

b <- list(`A. antarctica` = results_list$missing_amphi_vs_all_GO.txt$Name,
          `Z. marina` = results_list$missing_zmar_vs_all_GO.txt$Name,
          `Z. muelleri` = results_list$missing_zmuel_vs_all_GO.txt$Name)
intersections <- Reduce(intersect, b)
intersections[grepl('ethylene', intersections)]

NULL

OK we need a big list of all GO-terms here - which GO-term is lost in which species. That will be a supplementary table.

all_species <- c("P. australis","A. antarctica","Z. marina","Z. muelleri", 'A. thaliana')  
all_go_terms <- Reduce(union, a)
all_go_ids <- Reduce(union, a_go_ids)
results_d <- data.frame('GOID' = character(),
                        'GO' = character(),
                        'P. australis' = character(),
                        'A. antarctica' = character(),
                        'Z. marina' = character(),
                        'Z. muelleri' = character(),
                        'A. thaliana' = character())


for (index in seq_along(all_go_terms)){
  go <- all_go_terms[index]
  go_id <- all_go_ids[index]
  specs <- c()
  for (species in names(a)) {
    if ( length(a[[species]][grep(paste('^', go, '$', sep=''), a[[species]])]) > 0 ) {
      specs <- c(specs, species)
    }
  }
  
  results_d[index,] <- c(go_id, go, gsub('FALSE', 'Present', gsub('TRUE', 'Lost', all_species %in% specs)))
}

writexl::write_xlsx(results_d, 'output/Lost_GO_terms_in_five_species.xlsx')

After filtering for plant-specific GO-terms

We will use the GO-terms that are plant-specific as identified by the GOMAP paper. See https://github.com/wkpalan/GOMAP-maize-analysis/blob/main/6.plantSpecific/1.getSppSpecific.R or https://plantmethods.biomedcentral.com/articles/10.1186/s13007-021-00754-1

go_plant <- read_tsv('https://raw.githubusercontent.com/wkpalan/GOMAP-maize-analysis/main/data/go/speciesSpecificGOTerms.txt')

Rows: 45031 Columns: 5

-- Column specification --------------------------------------------------------
Delimiter: "\t"
chr (1): GOterm
dbl (4): NCBITaxon:10090, NCBITaxon:33090, NCBITaxon:3702, NCBITaxon:40674

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.

# taxon 33090 is Viridiplantae
plantSpecificGO <- go_plant %>% dplyr::filter(`NCBITaxon:33090`==1) %>% pull(GOterm)
plantSpecificGO <- c(plantSpecificGO,c("GO:0005575","GO:0008150","GO:0003674"))

results_d %>% filter(GOID %in% plantSpecificGO) %>% writexl::write_xlsx('output/Lost_GO_terms_in_five_species.PlantSpecific.xlsx')

Now let’s redo the Venn diagram with those filtered GO-terms

filters <- lapply(a_go_ids, function(ch) ch %in% plantSpecificGO)

newa <- list()
for (species in names(filters)) {
  before <- a[[species]]
  after <- before[filters[[species]]]
  newa[[species]] <- after
}

plot(venn(newa), 
     quantities = TRUE,
     fill = rev(wes_palette("Zissou1", 15, type = 'continuous')),
    alpha = 0.5,
     labels = list(font = 4))

Not much difference?

Session information

sessionInfo()

R version 4.1.0 (2021-05-18)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 19042)

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] stats4    parallel  stats     graphics  grDevices utils     datasets 
[8] methods   base     

other attached packages:
 [1] patchwork_1.1.1      kableExtra_1.3.4     rrvgo_1.4.4         
 [4] UpSetR_1.4.0         eulerr_6.1.1         ggrepel_0.9.1       
 [7] stringi_1.7.5        httr_1.4.2           wesanderson_0.3.6   
[10] rvest_1.0.2          forcats_0.5.1        stringr_1.4.0       
[13] dplyr_1.0.7          purrr_0.3.4          readr_2.0.2         
[16] tidyr_1.1.4          tibble_3.1.5         ggplot2_3.3.5       
[19] tidyverse_1.3.1      topGO_2.44.0         SparseM_1.81        
[22] GO.db_3.13.0         AnnotationDbi_1.54.1 IRanges_2.26.0      
[25] S4Vectors_0.30.2     Biobase_2.52.0       graph_1.70.0        
[28] BiocGenerics_0.38.0  workflowr_1.6.2     

loaded via a namespace (and not attached):
  [1] colorspace_2.0-2       ellipsis_0.3.2         rprojroot_2.0.2       
  [4] XVector_0.32.0         fs_1.5.0               rstudioapi_0.13       
  [7] farver_2.1.0           bit64_4.0.5            fansi_0.5.0           
 [10] lubridate_1.8.0        xml2_1.3.2             cachem_1.0.6          
 [13] GOSemSim_2.18.1        knitr_1.36             polyclip_1.10-0       
 [16] jsonlite_1.7.2         broom_0.7.9            gridBase_0.4-7        
 [19] dbplyr_2.1.1           png_0.1-7              pheatmap_1.0.12       
 [22] shiny_1.7.1            compiler_4.1.0         backports_1.2.1       
 [25] assertthat_0.2.1       fastmap_1.1.0          cli_3.0.1             
 [28] later_1.3.0            htmltools_0.5.2        tools_4.1.0           
 [31] igraph_1.2.7           NLP_0.2-1              gtable_0.3.0          
 [34] glue_1.4.2             GenomeInfoDbData_1.2.6 Rcpp_1.0.7            
 [37] slam_0.1-48            cellranger_1.1.0       jquerylib_0.1.4       
 [40] vctrs_0.3.8            Biostrings_2.60.2      writexl_1.4.0         
 [43] svglite_2.1.0          polylabelr_0.2.0       xfun_0.27             
 [46] mime_0.12              lifecycle_1.0.1        zlibbioc_1.38.0       
 [49] scales_1.1.1           treemap_2.4-3          vroom_1.5.5           
 [52] hms_1.1.1              promises_1.2.0.1       RColorBrewer_1.1-2    
 [55] curl_4.3.2             yaml_2.2.1             memoise_2.0.0         
 [58] gridExtra_2.3          sass_0.4.0             RSQLite_2.2.8         
 [61] highr_0.9              GenomeInfoDb_1.28.4    systemfonts_1.0.4     
 [64] rlang_0.4.12           pkgconfig_2.0.3        matrixStats_0.61.0    
 [67] bitops_1.0-7           evaluate_0.14          lattice_0.20-44       
 [70] labeling_0.4.2         cowplot_1.1.1          bit_4.0.4             
 [73] tidyselect_1.1.1       plyr_1.8.6             magrittr_2.0.1        
 [76] R6_2.5.1               generics_0.1.1         DBI_1.1.1             
 [79] pillar_1.6.4           haven_2.4.3            whisker_0.4           
 [82] withr_2.4.2            KEGGREST_1.32.0        RCurl_1.98-1.5        
 [85] modelr_0.1.8           crayon_1.4.1           wordcloud_2.6         
 [88] utf8_1.2.2             tzdb_0.1.2             rmarkdown_2.11        
 [91] grid_4.1.0             readxl_1.3.1           data.table_1.14.2     
 [94] blob_1.2.2             git2r_0.28.0           webshot_0.5.2         
 [97] reprex_2.0.1           digest_0.6.28          xtable_1.8-4          
[100] tm_0.7-8               httpuv_1.6.3           munsell_0.5.0         
[103] viridisLite_0.4.0      bslib_0.3.1