Reading data
Get bulk export from bugsigdb.org:
full.dat <- bugsigdbr::importBugSigDB(version = "devel", cache = FALSE)
dim(full.dat)## [1] 7041 50
colnames(full.dat)## [1] "BSDB ID" "Study"
## [3] "Study design" "PMID"
## [5] "DOI" "URL"
## [7] "Authors list" "Title"
## [9] "Journal" "Year"
## [11] "Keywords" "Experiment"
## [13] "Location of subjects" "Host species"
## [15] "Body site" "UBERON ID"
## [17] "Condition" "EFO ID"
## [19] "Group 0 name" "Group 1 name"
## [21] "Group 1 definition" "Group 0 sample size"
## [23] "Group 1 sample size" "Antibiotics exclusion"
## [25] "Sequencing type" "16S variable region"
## [27] "Sequencing platform" "Statistical test"
## [29] "Significance threshold" "MHT correction"
## [31] "LDA Score above" "Matched on"
## [33] "Confounders controlled for" "Pielou"
## [35] "Shannon" "Chao1"
## [37] "Simpson" "Inverse Simpson"
## [39] "Richness" "Signature page name"
## [41] "Source" "Curated date"
## [43] "Curator" "Revision editor"
## [45] "Description" "Abundance in Group 1"
## [47] "MetaPhlAn taxon names" "NCBI Taxonomy IDs"
## [49] "State" "Reviewer"Stripping illformed entries:
Curation output
Number of papers and signatures curated:
## [1] 1233
nrow(full.dat)## [1] 7041Publication date of the curated papers:
pmids <- pmids[!is.na(pmids)]
pubyear <- pmid2pubyear(pmids)
head(cbind(pmids, pubyear))## pmids pubyear
## [1,] "28038683" "2016"
## [2,] "28173873" "2017"
## [3,] "27015276" "2016"
## [4,] "27625705" "2016"
## [5,] "23071781" "2012"
## [6,] "28467925" "2017"
tab <- table(pubyear)
tab <- tab[-length(tab)]
tab <- tab[order(as.integer(names(tab)))]
df <- data.frame(year = names(tab), papers = as.integer(tab))
ggbarplot(df, x = "year", y = "papers",
label = TRUE, fill = "steelblue",
ggtheme = theme_bw())
Stripping empty signatures:
ind1 <- lengths(full.dat[["MetaPhlAn taxon names"]]) > 0
ind2 <- lengths(full.dat[["NCBI Taxonomy IDs"]]) > 0
dat <- full.dat[ind1 & ind2,]
nrow(dat)## [1] 7041Papers containing only empty UP and DOWN signatures (under curation?):
## numeric(0)Progress over time:
dat[,"Curated date"] <- as.character(lubridate::dmy(dat[,"Curated date"]))
plotProgressOverTime(dat)
plotProgressOverTime(dat, diff = TRUE)
Stratified by curator:
npc <- stratifyByCurator(dat)
plotCuratorStats(dat, npc)
Number of complete and revised signatures:
table(df[["State"]])## < table of extent 0 >
table(dat[,"Revision editor"])##
## AaishahM
## 25
## Aananditaa
## 1
## Aananditaa,Peace Sandy
## 1
## Aananditaa,Scholastica
## 3
## Abiola-Salako
## 1
## Abiola-Salako,Folakunmi
## 2
## Abiola-Salako,Scholastica
## 12
## Adeitan,Scholastica
## 1
## Adeitan,Welile,Scholastica
## 1
## Adenike Oladimeji-Kasumu
## 11
## Adenike Oladimeji-Kasumu,Peace Sandy
## 2
## Adenike Oladimeji-Kasumu,Rahila
## 1
## Adenike Oladimeji-Kasumu,Scholastica
## 10
## Adeoyo Olajumoke
## 2
## Adi13
## 1
## Adi13,ChiomaBlessing
## 6
## Adwan,Tosin
## 1
## Agatha,KateRasheed
## 2
## Agatha,KateRasheed,Aleru Divine
## 1
## Aishat,Aleru Divine
## 1
## Aishat,Folakunmi
## 2
## Aishat,KateRasheed
## 4
## Aishat,Scholastica
## 4
## AishatBolarinwa
## 5
## AishatBolarinwa,Aleru Divine
## 11
## AishatBolarinwa,Aleru Divine,Folakunmi
## 5
## AishatBolarinwa,Folakunmi
## 1
## AishatBolarinwa,KateRasheed
## 4
## AishatBolarinwa,MyleeeA
## 3
## AishatBolarinwa,MyleeeA,KateRasheed
## 1
## Aiyshaaaa
## 19
## Aiyshaaaa,Atrayees
## 4
## Aiyshaaaa,Claregrieve1
## 4
## Aiyshaaaa,WikiWorks,Atrayees
## 1
## Aiyshaaaa,WikiWorks,Merit
## 3
## Aiyshaaaa,WikiWorks,Merit,Atrayees
## 1
## Aleru Divine
## 565
## Aleru Divine,AishatBolarinwa
## 25
## Aleru Divine,Folakunmi
## 13
## Aleru Divine,KateRasheed
## 1
## Aleru Divine,MyleeeA
## 1
## Aleru Divine,Peace Sandy
## 1
## Aleru Divine,Scholastica
## 11
## Aleru Divine,Svetlana up
## 1
## Aleru002
## 10
## Aleru002,Folakunmi
## 2
## Aleru002,Peace Sandy
## 2
## AlishaM
## 9
## Amara,Ayibatari,Peace Sandy
## 1
## Amara,Welile,Peace Sandy
## 1
## Andre
## 28
## Andre,ChiomaBlessing
## 2
## Andre,Chloe
## 1
## Andre,Deacme,ChiomaBlessing
## 2
## Andre,Folakunmi
## 9
## Andre,Folakunmi,Peace Sandy
## 3
## Andre,MyleeeA
## 1
## Andre,Peace Sandy
## 4
## Andre,Peace Sandy,Folakunmi
## 2
## Andre,Tolulopeo
## 2
## Annabelcute,Aiyshaaaa,Atrayees
## 1
## Appleeyes
## 4
## Ardeybisi,Adenike Oladimeji-Kasumu
## 2
## Assel
## 1
## Assel,Ayibatari
## 1
## Atrayees
## 63
## Atrayees,Aiyshaaaa
## 1
## Atrayees,Aiyshaaaa,Claregrieve1
## 1
## Atrayees,Aiyshaaaa,Deacme,ChiomaBlessing
## 1
## Atrayees,ChiomaBlessing
## 18
## Atrayees,ChiomaBlessing,Chinelsy
## 1
## Atrayees,Claregrieve1
## 6
## Atrayees,Folakunmi
## 17
## Atrayees,Lwaldron
## 2
## Atrayees,Lwaldron,Claregrieve1
## 1
## Atrayees,Peace Sandy
## 4
## Atrayees,WikiWorks
## 9
## Atrayees,WikiWorks,ChiomaBlessing
## 1
## Atrayees,WikiWorks,Folakunmi
## 3
## Atrayees,WikiWorks,Folakunmi,ChiomaBlessing
## 2
## Atrayees,WikiWorks,Merit
## 2
## Ayibatari
## 11
## Ayibatari,Scholastica
## 15
## Ayibatari,Svetlana up
## 1
## Balogun adekemi,Folakunmi
## 4
## Barakat Dindi,Chloe
## 2
## Barrakat
## 6
## Barrakat,Deacme,KateRasheed
## 10
## Barrakat,KateRasheed
## 5
## Barrakat,MyleeeA,KateRasheed
## 2
## Barrakat,Peace Sandy
## 2
## Barrakat,Scholastica
## 5
## Barrakat,Svetlana up
## 3
## Blessing Kaz,Aiyshaaaa,Atrayees
## 1
## BLESSING123
## 9
## BLESSING123,Chloe
## 2
## BLESSING123,Folakunmi
## 2
## Boadiwaa
## 1
## Boadiwaa,Chloe
## 1
## Boadiwaa,Chloe,Hodan Issah
## 1
## Boadiwaa,Chloe,Peace Sandy,Hodan Issah
## 1
## Boadiwaa,Chloe,Tolulopeo
## 1
## Boadiwaa,Folakunmi
## 1
## Boadiwaa,Idiaru angela
## 1
## Boadiwaa,Welile
## 1
## Bolanle
## 11
## Bolanle,Aleru Divine
## 5
## Bolanle,Fiddyhamma
## 8
## Brian,Suwaiba
## 1
## Brian,Suwaiba,Atrayees
## 1
## BSpac126,Victoria
## 1
## BSpac126,Victoria,Scholastica
## 2
## Busayo
## 1
## Busayo,Fatima
## 1
## Busayo,Mcarlson,ChiomaBlessing
## 2
## Cateline Ouma
## 1
## Cateline Ouma,Peace Sandy
## 5
## Cateline Ouma,Rahila
## 1
## Cateline Ouma,Rahila,Peace Sandy
## 1
## Chikamso
## 2
## Chikamso,ChiomaBlessing
## 2
## Chikamso,OdigiriGreat,Chinelsy,Peace Sandy,Folakunmi
## 1
## Chikamso,Peace Sandy,Folakunmi
## 1
## Chinelsy
## 7
## Chinelsy,ChiomaBlessing
## 9
## Chinelsy,ChiomaBlessing,Idiaru angela
## 1
## Chinelsy,ChiomaBlessing,Welile
## 2
## Chinelsy,Folakunmi
## 12
## Chinelsy,MyleeeA,ChiomaBlessing
## 2
## Chinelsy,MyleeeA,Folakunmi
## 1
## Chinelsy,Peace Sandy
## 2
## Chinelsy,Peace Sandy,ChiomaBlessing
## 1
## Chinelsy,Peace Sandy,Davvve,Chloe
## 1
## Chioma
## 4
## Chioma,Fatima
## 2
## ChiomaBlessing
## 111
## ChiomaBlessing,Atrayees
## 1
## ChiomaBlessing,Folakunmi
## 13
## ChiomaBlessing,Folakunmi,Joan Chuks
## 1
## ChiomaBlessing,Iram jamshed,Folakunmi
## 1
## ChiomaBlessing,Joan Chuks
## 4
## ChiomaBlessing,Peace Sandy
## 3
## ChiomaBlessing,Scholastica,Joan Chuks
## 1
## ChiomaBlessing,WikiWorks
## 1
## Chisom
## 2
## Chiwendeee,Folakunmi
## 1
## Chloe
## 12
## Chloe 256
## 3
## Chloe 256,Iram jamshed
## 1
## Chloe 256,MyleeeA,Folakunmi
## 3
## Chloe 256,MyleeeA,Folakunmi,Joan Chuks
## 1
## Chloe 256,Peace Sandy
## 1
## Chloe 256,Peace Sandy,Folakunmi
## 1
## Chloe,Kwekuamoo
## 1
## Chloe,Lorakasselman,Aiyshaaaa,Peace Sandy
## 1
## Chloe,Lwaldron,Chinelsy
## 1
## Chloe,Merit
## 1
## Chloe,WikiWorks
## 4
## Chrisawoke
## 5
## Chrisawoke,Chloe
## 1
## Claregrieve1
## 139
## Claregrieve1,Aiyshaaaa,Atrayees
## 2
## Claregrieve1,Aleru002,Peace Sandy
## 1
## Claregrieve1,Atrayees
## 1
## Claregrieve1,Atrayees,WikiWorks
## 2
## Claregrieve1,Atrayees,WikiWorks,Merit
## 1
## Claregrieve1,Chloe
## 1
## Claregrieve1,Chloe,WikiWorks,Merit
## 1
## Claregrieve1,Davvve
## 1
## Claregrieve1,Davvve,Peace Sandy
## 1
## Claregrieve1,Fatima
## 10
## Claregrieve1,Fatima,LGeistlinger
## 1
## Claregrieve1,Fatima,Yu Wang
## 1
## Claregrieve1,Folakunmi
## 5
## Claregrieve1,Iram jamshed
## 1
## Claregrieve1,Lwaldron
## 2
## Claregrieve1,Lwaldron,Suwaiba
## 1
## Claregrieve1,Merit
## 8
## Claregrieve1,Merit,WikiWorks
## 1
## Claregrieve1,Merit,WikiWorks,ChiomaBlessing,Davvve
## 1
## Claregrieve1,Peace Sandy
## 9
## Claregrieve1,Rukky,WikiWorks
## 1
## Claregrieve1,Suwaiba
## 1
## Claregrieve1,Suwaiba,Merit
## 1
## Claregrieve1,WikiWorks
## 252
## Claregrieve1,WikiWorks,Atrayees
## 1
## Claregrieve1,WikiWorks,ChiomaBlessing
## 3
## Claregrieve1,WikiWorks,Chloe
## 1
## Claregrieve1,WikiWorks,Folakunmi
## 3
## Claregrieve1,WikiWorks,Merit
## 6
## Claregrieve1,WikiWorks,OdigiriGreat
## 2
## Cyberian,Chloe,Aiyshaaaa,Folakunmi
## 1
## Cyberian,Chloe,Folakunmi
## 1
## Cyberian,Folakunmi
## 2
## Cynthia Anderson
## 17
## Cynthia Anderson,Atrayees
## 4
## Cynthia Anderson,Claregrieve1
## 2
## Cynthia Anderson,Fatima
## 2
## Cynthia Anderson,Folakunmi
## 1
## Cynthia Anderson,LGeistlinger,WikiWorks
## 2
## Cynthia Anderson,Lwaldron,WikiWorks,ChiomaBlessing
## 1
## Cynthia Anderson,Peace Sandy
## 1
## Danyab56
## 2
## Danyab56,Aiyshaaaa,Claregrieve1
## 5
## Davvve
## 3
## Davvve,Chinelsy,Peace Sandy,Folakunmi
## 1
## Davvve,ChiomaBlessing
## 1
## Davvve,Folakunmi
## 1
## Deacme
## 8
## Deacme,Aiyshaaaa,Atrayees,ChiomaBlessing
## 3
## Deacme,Atrayees,ChiomaBlessing
## 4
## Deacme,Chinelsy
## 2
## Deacme,ChiomaBlessing
## 9
## Deacme,Davvve,Folakunmi
## 1
## Deacme,Folakunmi
## 13
## Deacme,KateRasheed
## 41
## Deacme,Scholastica
## 3
## Deacme,Yjung24,Davvve,Folakunmi
## 1
## Dupe
## 1
## Dupe,Aiyshaaaa,Atrayees
## 1
## Dupe,Atrayees
## 2
## Dupe,Mcarlson,Peace Sandy
## 2
## Ebere,Peace Sandy
## 2
## EGO,Scholastica
## 4
## EGO,Welile,Folakunmi
## 1
## Ehi,Deacme
## 3
## Ehi,Deacme,Scholastica
## 6
## Ehi,Folakunmi
## 2
## Ellajessica
## 2
## Ellajessica,Aiyshaaaa
## 2
## EniolaAde,Ayibatari,Scholastica
## 1
## EniolaAde,Folakunmi
## 2
## EniolaAde,Peace Sandy
## 2
## EniolaAde,Peace Sandy,ChiomaBlessing
## 1
## EniolaAde,Scholastica
## 8
## Eve10111,Folakunmi
## 2
## Eve10111,Scholastica
## 4
## FaithAlexander
## 20
## FaithAlexander,Peace Sandy
## 1
## Fatima
## 20
## Fatima,Aiyshaaaa
## 2
## Fatima,Claregrieve1
## 2
## Fatima,Claregrieve1,WikiWorks
## 11
## Fatima,Kwekuamoo,WikiWorks
## 2
## Fatima,LGeistlinger,WikiWorks
## 1
## Fatima,Lwaldron,Joan Chuks
## 1
## Fatima,Lwaldron,WikiWorks
## 3
## Fatima,Merit,WikiWorks
## 1
## Fatima,Merit,WikiWorks,Lwaldron,Davvve
## 1
## Fatima,Peace Sandy
## 2
## Fatima,WikiWorks
## 32
## Fatima,WikiWorks,ChiomaBlessing
## 3
## Fatima,WikiWorks,Folakunmi
## 3
## Fatima,WikiWorks,Merit,ChiomaBlessing
## 3
## Fcuevas3
## 21
## Fcuevas3,Aiyshaaaa,Atrayees
## 1
## Fcuevas3,Aiyshaaaa,Peace Sandy
## 2
## Fcuevas3,Atrayees
## 22
## Fcuevas3,Claregrieve1
## 5
## Fcuevas3,Claregrieve1,Atrayees
## 1
## Fcuevas3,Fatima
## 1
## Fcuevas3,Fatima,Atrayees
## 1
## Fcuevas3,Folakunmi,ChiomaBlessing
## 5
## Fcuevas3,Lwaldron,Aiyshaaaa
## 2
## Fcuevas3,Peace Sandy
## 3
## Fcuevas3,Rimsha
## 8
## Fiddyhamma
## 60
## Fiddyhamma,ChiomaBlessing
## 4
## Fiddyhamma,Folakunmi
## 1
## Fiddyhamma,Ifeanyisam
## 3
## Fiddyhamma,KateRasheed
## 13
## Fiddyhamma,Omojokunoluwatomisin,ChiomaBlessing
## 1
## Fiddyhamma,Scholastica
## 12
## Fiddyhamma,Svetlana up
## 2
## Fiddyhamma,Victoria
## 1
## Fiddyhamma,Victoria,Ifeanyisam
## 6
## Fiddyhamma,Welile,ChiomaBlessing
## 1
## Flo
## 1
## Flo,Scholastica
## 7
## Folakunmi
## 112
## Folakunmi,Aananditaa
## 1
## Folakunmi,Chinelsy,ChiomaBlessing
## 1
## Folakunmi,ChiomaBlessing
## 24
## Folakunmi,ChiomaBlessing,MyleeeA
## 1
## Folakunmi,Davvve,ChiomaBlessing
## 1
## Folakunmi,Joan Chuks
## 2
## Folakunmi,KateRasheed
## 1
## Folakunmi,MyleeeA
## 1
## Folakunmi,Peace Sandy,Hodan Issah,ChiomaBlessing
## 1
## Fortunehechi,Folakunmi
## 1
## Gina
## 14
## Glorious,Fiddyhamma
## 2
## Glorious,Fiddyhamma,Folakunmi
## 2
## Grace og,Hodan Issah,Peace Sandy
## 1
## Grace og,Peace Sandy
## 1
## Graycepaul,Welile,Folakunmi
## 1
## Graycepaul,Welile,Muqtadirat,Folakunmi
## 1
## Greatman,LGeistlinger,Peace Sandy
## 1
## Hamza,Scholastica
## 2
## Haoyanzh
## 20
## Haoyanzh,Lwaldron
## 2
## Hodan Issah
## 1
## Hodan Issah,Folakunmi
## 1
## Idiaru angela
## 55
## Idiaru angela,Folakunmi
## 2
## Idiaru angela,Scholastica
## 4
## Idiat,Ayibatari,Victoria
## 1
## Idiat,Folakunmi,Aananditaa
## 1
## Idiat,Victoria
## 1
## Idiat,Welile,Folakunmi
## 1
## Ifeanyisam
## 41
## Ifeanyisam,Rahila
## 1
## Ifeanyisam,Svetlana up
## 1
## Ifeanyisam,Victoria
## 5
## Ifyohondu
## 1
## Ifyohondu,Folakunmi
## 1
## Ifyohondu,Folakunmi,ChiomaBlessing
## 5
## Ikehdarlington,ChiomaBlessing
## 3
## Ikehdarlington,Scholastica
## 2
## Iman-Ngwepe,Aleru Divine,Scholastica
## 2
## Iman-Ngwepe,Fiddyhamma
## 3
## Iman-Ngwepe,Fiddyhamma,MyleeeA
## 1
## Imaspecial
## 1
## Imaspecial,Fiddyhamma
## 10
## Imaspecial,Peace Sandy
## 2
## Imaspecial,Scholastica
## 4
## InimfonD
## 3
## InimfonD,KateRasheed
## 1
## InimfonD,MyleeeA
## 2
## InimfonD,Rahila
## 1
## InimfonD,Rahila,MyleeeA
## 3
## Iram jamshed,Hodan Issah,ChiomaBlessing
## 1
## Iram jamshed,Tolulopeo,ChiomaBlessing
## 4
## Itslanapark
## 24
## Itslanapark,Adanwa,Peace Sandy,Folakunmi
## 1
## Itslanapark,Aiyshaaaa
## 1
## Itslanapark,Aiyshaaaa,Atrayees
## 1
## Itslanapark,Aiyshaaaa,Davvve,Peace Sandy
## 2
## Itslanapark,Aiyshaaaa,Peace Sandy
## 1
## Itslanapark,Atrayees
## 1
## Itslanapark,Chloe
## 3
## Itslanapark,Chloe,Aiyshaaaa,Merit
## 1
## Itslanapark,Claregrieve1
## 3
## Itslanapark,Claregrieve1,Aiyshaaaa
## 1
## Itslanapark,Claregrieve1,Atrayees
## 1
## Itslanapark,Claregrieve1,ChiomaBlessing
## 1
## Itslanapark,Fatima
## 2
## Itslanapark,Fatima,Chloe,Merit
## 1
## Itslanapark,Peace Sandy
## 1
## Itslanapark,Peace Sandy,Atrayees,Folakunmi
## 1
## Itslanapark,Rimsha
## 1
## Jacob A. De Jesus
## 17
## Jacob A. De Jesus,Scholastica
## 10
## Jacquelynshevin
## 25
## Jacquelynshevin,Aleru002
## 1
## Jacquelynshevin,Chloe
## 1
## Jacquelynshevin,Chloe,WikiWorks
## 1
## Jacquelynshevin,Fatima
## 1
## Jacquelynshevin,Fatima,WikiWorks
## 6
## Jacquelynshevin,Folakunmi
## 3
## Jacquelynshevin,Peace Sandy
## 4
## Jayybb,Peace Sandy
## 2
## Jeshudy
## 34
## Jeshudy,Aiyshaaaa
## 3
## Jeshudy,Atrayees
## 7
## Jeshudy,Atrayees,Folakunmi
## 1
## Jeshudy,ChiomaBlessing
## 1
## Jeshudy,Claregrieve1
## 34
## Jeshudy,Fatima
## 4
## Jeshudy,Folakunmi
## 1
## Jeshudy,Peace Sandy
## 1
## Jeshudy,Suwaiba
## 2
## Joan Chuks
## 25
## Joan Chuks,Adeitan,Aleru Divine
## 4
## Joan Chuks,Aleru Divine
## 4
## Joan Chuks,ChiomaBlessing
## 5
## Joan Chuks,ChiomaBlessing,Peace Sandy
## 1
## Joan Chuks,Iram jamshed,Peace Sandy
## 1
## Joan Chuks,Peace Sandy
## 1
## Joan Chuks,Peace Sandy,Welile
## 1
## Johnpaul,Aleru Divine,Scholastica
## 2
## Joiejoie
## 16
## Joiejoie,Aleru Divine
## 6
## Joiejoie,KateRasheed
## 19
## Joiejoie,MyleeeA,KateRasheed
## 4
## Joiejoie,Taofeecoh,Svetlana up
## 1
## Joju
## 1
## Joju,Iram jamshed,MyleeeA
## 1
## JoyceQ,MyleeeA
## 2
## JoyceQ,Rahila,Victoria
## 1
## JoyceQ,Scholastica
## 2
## JoyceQ,Victoria
## 1
## Joyessa,Aiyshaaaa,Peace Sandy,ChiomaBlessing
## 1
## Joyessa,Claregrieve1
## 18
## Joyessa,Claregrieve1,Merit
## 1
## Joyessa,Fatima,Claregrieve1
## 2
## Junie
## 1
## Junie,Peace Sandy
## 2
## Junie,Svetlana up
## 1
## Kadeniyi,Peace Sandy
## 6
## Kahvecirem,Aiyshaaaa,Claregrieve1
## 2
## Kahvecirem,Aiyshaaaa,Merit,Claregrieve1
## 3
## Kahvecirem,Atrayees
## 1
## Kahvecirem,Atrayees,Boadiwaa
## 1
## Kahvecirem,Atrayees,Merit,Claregrieve1
## 1
## Kahvecirem,Merit,Claregrieve1
## 2
## Kaluifeanyi101
## 31
## Kaluifeanyi101,Aiyshaaaa,Peace Sandy
## 2
## Kaluifeanyi101,Atrayees
## 2
## Kaluifeanyi101,Atrayees,ChiomaBlessing
## 1
## Kaluifeanyi101,Atrayees,Folakunmi
## 1
## Kaluifeanyi101,ChiomaBlessing
## 1
## Kaluifeanyi101,Claregrieve1
## 16
## Kaluifeanyi101,Fatima
## 2
## Kaluifeanyi101,Folakunmi
## 3
## Kaluifeanyi101,Peace Sandy
## 10
## Karen254.,Chloe,Peace Sandy
## 2
## Karima
## 9
## Karima,KateRasheed
## 1
## KateRasheed
## 466
## KateRasheed,Aleru Divine
## 4
## KateRasheed,Chrisawoke
## 7
## KateRasheed,Folakunmi
## 2
## KateRasheed,MyleeeA
## 8
## KateRasheed,Svetlana up
## 1
## KathyWaldron,WikiWorks
## 1
## KathyWaldron,WikiWorks,ChiomaBlessing,Folakunmi
## 2
## KathyWaldron,WikiWorks,Merit,ChiomaBlessing,Folakunmi
## 1
## Kavyaayala
## 51
## Kaycee,Peace Sandy
## 2
## Keamy
## 4
## Keamy,ChiomaBlessing
## 3
## Keamy,Glorious,KateRasheed
## 1
## Keamy,Glorious,Victoria
## 5
## Keamy,Joan Chuks
## 1
## Keamy,Joan Chuks,MyleeeA,Victoria
## 2
## Keamy,Joan Chuks,Victoria
## 3
## Keamy,Scholastica
## 5
## Kelvin Joseph,Atrayees
## 6
## Kelvin Joseph,Claregrieve1,WikiWorks
## 2
## Khadeeejah,Aiyshaaaa,Atrayees
## 3
## Khadeeejah,Aiyshaaaa,Chloe,Atrayees
## 1
## Khadeeejah,Atrayees,Chloe,Aiyshaaaa
## 1
## Khadeeejah,Atrayees,Claregrieve1
## 2
## Kwekuamoo
## 14
## Kwekuamoo,Aiyshaaaa
## 1
## Kwekuamoo,Atrayees
## 4
## Kwekuamoo,Claregrieve1
## 4
## Kwekuamoo,Merit,WikiWorks
## 1
## Kwekuamoo,MyleeeA
## 5
## KwennB
## 2
## KwennB,Ayibatari,Rahila,Folakunmi
## 2
## Leenaa
## 7
## Leenaa,Fiddyhamma
## 4
## Levitest,WikiWorks,Merit,Atrayees
## 1
## LGeistlinger
## 1
## LiliGC,KateRasheed
## 2
## Linda Uchenwoke
## 2
## Lorakasselman,Aiyshaaaa,Merit,Peace Sandy
## 1
## Lorakasselman,Chloe
## 2
## Lorakasselman,Claregrieve1
## 2
## Lwaldron
## 13
## Lwaldron,Atrayees,WikiWorks,Aiyshaaaa
## 1
## Lwaldron,Claregrieve1,WikiWorks
## 5
## Lwaldron,Claregrieve1,WikiWorks,Merit
## 2
## Lwaldron,Fatima,WikiWorks
## 1
## Lwaldron,WikiWorks
## 26
## Lwaldron,WikiWorks,Atrayees
## 2
## Lwaldron,WikiWorks,ChiomaBlessing
## 1
## Lwaldron,WikiWorks,LGeistlinger
## 1
## Lwaldron,WikiWorks,Merit
## 4
## Lwaldron,WikiWorks,Peace Sandy
## 1
## Madhubani Dey
## 8
## Madhubani Dey,Aiyshaaaa,Peace Sandy
## 1
## Madhubani Dey,Atrayees
## 3
## Madhubani Dey,Chloe,Merit
## 1
## Madhubani Dey,Claregrieve1
## 24
## Madhubani Dey,Claregrieve1,Davvve
## 2
## Madhubani Dey,Fatima,Claregrieve1
## 2
## Madhubani Dey,Lwaldron,Peace Sandy
## 1
## Madhubani Dey,Merit
## 2
## Madhubani Dey,Peace Sandy
## 2
## Manisha28,KateRasheed
## 6
## Manisha28,Svetlana up
## 4
## Manuela
## 11
## Mariposa
## 4
## Martha KJ,Aleru Divine
## 2
## Mary Bearkland
## 38
## Mary Bearkland,Aiyshaaaa,Claregrieve1
## 1
## Mary Bearkland,Aiyshaaaa,Peace Sandy
## 2
## Mary Bearkland,Aleru002,Folakunmi
## 1
## Mary Bearkland,Atrayees
## 4
## Mary Bearkland,Boadiwaa
## 1
## Mary Bearkland,ChiomaBlessing
## 10
## Mary Bearkland,Claregrieve1
## 20
## Mary Bearkland,Fatima
## 3
## Mary Bearkland,Fatima,Merit
## 1
## Mary Bearkland,Folakunmi
## 15
## Mary Bearkland,Merit,Atrayees
## 4
## Mary Bearkland,Muqtadirat
## 1
## Mary Bearkland,Peace Sandy
## 9
## Mary Bearkland,Peace Sandy,Folakunmi
## 1
## MaryAgekameh,MyleeeA
## 11
## Maryemzaki,Lwaldron
## 2
## Merit,Claregrieve1
## 1
## Merit,WikiWorks
## 15
## Merit,WikiWorks,ChiomaBlessing
## 1
## Merit,WikiWorks,Lwaldron,Iram jamshed,Folakunmi
## 1
## Miss Lulu
## 13
## Mmarin
## 15
## Mmarin,Atrayees
## 3
## Mmarin,Claregrieve1
## 13
## Mmarin,Folakunmi
## 2
## Mmarin,Peace Sandy
## 2
## ModinatG
## 4
## ModinatG,Folakunmi
## 3
## Mojisayo Awolesi,Welile,Fiddyhamma,Scholastica
## 2
## Muqtadirat
## 1
## Muqtadirat,MyleeeA
## 2
## Muqtadirat,Victoria
## 2
## MyleeeA
## 208
## MyleeeA,Aleru Divine
## 5
## MyleeeA,ChiomaBlessing
## 3
## MyleeeA,Chrisawoke
## 1
## MyleeeA,Folakunmi
## 18
## MyleeeA,KateRasheed
## 7
## MyleeeA,Mariposa,ChiomaBlessing
## 3
## MyleeeA,MaryAgekameh
## 1
## MyleeeA,Scholastica
## 13
## MyleeeA,Tosin
## 22
## MyleeeA,Welile,Scholastica
## 1
## Nathcynthia,Rahila,Tosin
## 4
## Nathcynthia,Tosin
## 5
## Ndruscilla,Ayibatari,Joan Chuks
## 2
## Ndruscilla,Scholastica
## 4
## Nekembe,Aleru Divine
## 2
## Nekembe,Aleru Divine,Peace Sandy
## 2
## Nice25
## 1
## Nityasinghal 14,Junie
## 2
## Nityasinghal 14,Scholastica
## 9
## Nityasinghal 14,Svetlana up
## 3
## Nnadichioma,Aiyshaaaa,Atrayees
## 3
## Nnadichioma,Aiyshaaaa,Merit,Atrayees
## 2
## Nnadichioma,Atrayees,Aiyshaaaa,Merit
## 1
## Nwajei Edgar,Ayibatari,Keamy
## 2
## Nwajei Edgar,Deacme
## 1
## Nwajei Edgar,Deacme,Folakunmi
## 1
## Nwajei Edgar,Peace Sandy,Folakunmi
## 2
## OdigiriGreat
## 2
## OdigiriGreat,ChiomaBlessing
## 8
## OdigiriGreat,Folakunmi
## 13
## Ojotuleonalo
## 2
## Ojotuleonalo,Peace Sandy,Folakunmi
## 2
## Ombati,Atrayees
## 3
## Ombati,Chloe,Atrayees
## 1
## Omojokunoluwatomisin
## 2
## Omojokunoluwatomisin,Ayibatari
## 1
## Omojokunoluwatomisin,KateRasheed
## 5
## Omojokunoluwatomisin,Peace Sandy
## 2
## Omojokunoluwatomisin,Scholastica
## 10
## Paavni Goyal,KateRasheed
## 2
## Patience Onah
## 6
## Peace Sandy
## 92
## Peace Sandy,Atrayees
## 1
## Peace Sandy,ChiomaBlessing
## 2
## Peace Sandy,Folakunmi
## 2
## PraiseAgbetuyi
## 2
## PraiseAgbetuyi,Peace Sandy
## 2
## PreciousMike,Ayibatari
## 2
## Princess Ben
## 1
## Princess Ben,KateRasheed
## 2
## Princess Ben,MyleeeA
## 1
## Princess Ben,Svetlana up
## 2
## Prolific
## 2
## Prolific,Aleru Divine
## 2
## Prolific,KateRasheed
## 5
## Rahila
## 49
## Rahila,Aleru Divine
## 26
## Rahila,ChiomaBlessing
## 2
## Rahila,Folakunmi
## 6
## Rahila,KateRasheed
## 6
## Rahila,MyleeeA,KateRasheed
## 1
## Rahila,Scholastica
## 33
## Raihanat
## 1
## Raihanat,Peace Sandy
## 3
## Rimsha
## 4
## Rimsha,Fatima,LGeistlinger,WikiWorks
## 1
## Rimsha,Fatima,WikiWorks
## 1
## Rimsha,Lwaldron
## 1
## Rukaya-lab,Rahila,Chrisawoke
## 1
## Rukaya-lab,Rahila,Chrisawoke,Chloe
## 1
## Rukaya-lab,Rahila,Chrisawoke,MyleeeA
## 3
## Rukaya-lab,Rahila,Chrisawoke,MyleeeA,Chloe
## 2
## Samara.Khan
## 13
## Samara.Khan,Atrayees
## 3
## Samara.Khan,Claregrieve1
## 8
## Samara.Khan,Claregrieve1,Folakunmi
## 1
## Samara.Khan,Fatima
## 1
## Samara.Khan,Folakunmi
## 3
## Samara.Khan,Folakunmi,Welile,Idiaru angela
## 1
## Samara.Khan,Peace Sandy
## 1
## Samreen-19
## 14
## Samreen-19,ChiomaBlessing
## 6
## Samreen-19,Scholastica
## 5
## Scholastica
## 195
## Scholastica,Ayibatari
## 1
## Scholastica,ChiomaBlessing
## 2
## Scholastica,MyleeeA
## 2
## Scholastica,Peace Sandy
## 2
## Scholastica,Welile
## 2
## Sharmilac
## 4
## Sharmilac,Aiyshaaaa
## 1
## Sharmilac,Claregrieve1
## 2
## Sharmilac,Fatima
## 6
## Sharmilac,Fatima,Aiyshaaaa
## 1
## Sharmilac,Merit
## 2
## Sharmilac,Peace Sandy
## 1
## Shulamite
## 3
## Shulamite,Aleru Divine
## 2
## Shulamite,Deacme,Scholastica
## 2
## Shulamite,Ifeanyisam
## 2
## Shulamite,Peace Sandy
## 2
## Shulamite,Rahila
## 3
## Shulamite,Rahila,Peace Sandy
## 2
## Shulamite,Scholastica
## 1
## Sinmisoluwa Adesanya,Chinelsy,Folakunmi
## 3
## Sinmisoluwa Adesanya,Chinelsy,Folakunmi,Welile
## 1
## Sinmisoluwa Adesanya,Chinelsy,Peace Sandy,Folakunmi
## 1
## Sinmisoluwa Adesanya,Chinelsy,Peace Sandy,Folakunmi,Welile
## 1
## Sneha6003,Peace Sandy
## 1
## Snehhumann,Idiaru angela
## 2
## Sophy
## 1
## Sophy,Aiyshaaaa,Claregrieve1
## 4
## Sophy,Atrayees
## 4
## Sophy,Chloe
## 1
## Sophy,Claregrieve1
## 4
## Sophy,Mcarlson,Atrayees,Peace Sandy
## 2
## Sproff,Tosin
## 2
## Spykelionel,Peace Sandy
## 2
## Suwaiba
## 14
## Suwaiba,Atrayees
## 6
## Suwaiba,Atrayees,ChiomaBlessing
## 1
## Suwaiba,Atrayees,Peace Sandy
## 2
## Svetlana up
## 4
## Svetlana up,Omojokunoluwatomisin
## 1
## Taofeecoh
## 2
## Tayk26,Svetlana up
## 4
## Temi,Scholastica
## 2
## Temitayo,Peace Sandy
## 2
## Testuser,Peace Sandy
## 1
## Testuser,Tolulopeo,Peace Sandy
## 1
## Tino
## 3
## Tino,KateRasheed
## 3
## Tino,Rahila
## 2
## Tislam
## 10
## Tislam,Aiyshaaaa,Claregrieve1
## 1
## Tislam,Aiyshaaaa,Peace Sandy
## 2
## Tislam,Atrayees
## 7
## Tislam,Atrayees,Peace Sandy
## 2
## Tislam,Claregrieve1
## 6
## Tislam,Fatima
## 8
## Tislam,Fatima,Claregrieve1
## 1
## Tislam,Lwaldron,Aiyshaaaa,Peace Sandy,Chloe,Chikamso,Folakunmi
## 1
## Tislam,Peace Sandy
## 12
## Tislam,Rimsha,Claregrieve1,Merit
## 2
## Titas
## 3
## Titas,Atrayees,Chloe
## 1
## Titas,Chloe
## 1
## Titas,Fatima
## 1
## Tolulopeo,Chinelsy,ChiomaBlessing
## 1
## Tolulopeo,Chinelsy,Chloe,ChiomaBlessing
## 1
## Tolulopeo,ChiomaBlessing
## 1
## Tolulopeo,Davvve,Peace Sandy
## 1
## Tolulopeo,OdigiriGreat,ChiomaBlessing
## 1
## Tolulopeo,Peace Sandy
## 4
## ToluwalaseA,Aleru Divine
## 2
## ToluwalaseA,Tosin
## 2
## Tosin
## 88
## Tosin,Aleru Divine
## 4
## Tosin,KateRasheed
## 2
## Tosin,MyleeeA
## 1
## Tosin,Nathcynthia
## 4
## Toyosiolann,Svetlana up
## 2
## Uchechukwu,Davvve
## 1
## Uchechukwu,Davvve,MyleeeA
## 1
## Ufuoma Ejite
## 1
## Ufuoma Ejite,Atrayees
## 8
## Ufuoma Ejite,Chloe,Aiyshaaaa
## 1
## Ufuoma Ejite,Chloe,Aiyshaaaa,Atrayees
## 1
## Ufuoma Ejite,Lwaldron,WikiWorks
## 7
## Uhabiba14,Fiddyhamma,MyleeeA
## 1
## Uhabiba14,KateRasheed
## 1
## Uhabiba14,MyleeeA,Fiddyhamma
## 1
## Uhabiba14,Scholastica
## 1
## Uyokeeswaran,Peace Sandy
## 2
## Valentina
## 1
## Valentina,Atrayees
## 1
## Vandana Maddi,KateRasheed
## 8
## Victoria
## 75
## Victoria,Aleru Divine
## 1
## Victoria,ChiomaBlessing
## 2
## Victoria,Fiddyhamma
## 1
## Victoria,Ifeanyisam
## 1
## Wendy640,KateRasheed
## 12
## Wendy640,Shulamite
## 1
## WikiWorks
## 753
## WikiWorks,Aiyshaaaa
## 2
## WikiWorks,Aiyshaaaa,Atrayees
## 1
## WikiWorks,Atrayees
## 77
## WikiWorks,Atrayees,ChiomaBlessing
## 15
## WikiWorks,Atrayees,Folakunmi
## 2
## WikiWorks,Atrayees,Folakunmi,MyleeeA
## 1
## WikiWorks,Atrayees,Joan Chuks
## 2
## WikiWorks,Atrayees,Merit
## 4
## WikiWorks,Chinelsy,ChiomaBlessing
## 1
## WikiWorks,ChiomaBlessing
## 131
## WikiWorks,Chloe,ChiomaBlessing
## 1
## WikiWorks,Claregrieve1
## 13
## WikiWorks,Davvve
## 1
## WikiWorks,Davvve,ChiomaBlessing
## 2
## WikiWorks,Fatima
## 2
## WikiWorks,Folakunmi
## 37
## WikiWorks,Folakunmi,ChiomaBlessing
## 1
## WikiWorks,Folakunmi,MyleeeA
## 1
## WikiWorks,Folakunmi,Scholastica,Welile
## 1
## WikiWorks,Folakunmi,Welile
## 1
## WikiWorks,Jeshudy
## 1
## WikiWorks,Merit
## 13
## WikiWorks,Merit,Atrayees
## 4
## WikiWorks,Merit,Atrayees,Folakunmi
## 2
## WikiWorks,Merit,ChiomaBlessing
## 3
## WikiWorks,Merit,ChiomaBlessing,Folakunmi
## 1
## WikiWorks,Merit,Folakunmi
## 2
## WikiWorks,Merit,Folakunmi,Aleru Divine
## 1
## WikiWorks,Peace Sandy
## 32
## WikiWorks,Peace Sandy,MyleeeA
## 1
## WikiWorks,Rukky
## 2
## WikiWorks,Rukky,ChiomaBlessing,Joan Chuks
## 1
## WikiWorks,Suwaiba,Atrayees
## 1
## Winnie,Davvve
## 1
## Winnie,Iram jamshed
## 1
## Yjung24
## 30
## Yjung24,Atrayees
## 4
## Yjung24,Atrayees,Peace Sandy
## 1
## Yjung24,ChiomaBlessing
## 2
## Yjung24,ChiomaBlessing,Folakunmi
## 1
## Yjung24,Davvve,Folakunmi
## 1
## Yjung24,Folakunmi
## 4
## Yjung24,Peace Sandy
## 14
## YokoC
## 69
## YokoC,Aleru Divine
## 2
## YokoC,KateRasheed
## 1
## YokoC,Rahila,Scholastica
## 1
## YokoC,Scholastica
## 2
## Yu Wang,Fatima
## 1
## Yu Wang,Fatima,Claregrieve1
## 4
## Zheeburg,Aleru Divine
## 2
## Zheeburg,Scholastica
## 2Study stats
Study design
spl <- split(dat[["Study"]], dat[["Study design"]])
sds <- lapply(spl, unique)
sort(lengths(sds), decreasing = FALSE)## case-control,prospective cohort
## 1
## cross-sectional observational, not case-control,laboratory experiment
## 1
## prospective cohort,time series / longitudinal observational
## 1
## cross-sectional observational, not case-control,prospective cohort
## 2
## laboratory experiment,meta-analysis
## 2
## case-control,time series / longitudinal observational
## 3
## case-control,laboratory experiment
## 4
## case-control,meta-analysis
## 5
## laboratory experiment,time series / longitudinal observational
## 5
## meta-analysis
## 11
## randomized controlled trial
## 46
## prospective cohort
## 102
## laboratory experiment
## 109
## time series / longitudinal observational
## 117
## cross-sectional observational, not case-control
## 333
## case-control
## 505Experiment stats
Columns of the full dataset that describe experiments:
# Experiment ID
exp.cols <- c("Study", "Experiment")
# Subjects
sub.cols <- c("Host species",
"Location of subjects",
"Body site",
"Condition",
"Antibiotics exclusion",
"Group 0 sample size",
"Group 1 sample size")
# Lab analysis
lab.cols <- c("Sequencing type",
"16S variable region",
"Sequencing platform")
# Statistical analysis
stat.cols <- c("Statistical test",
"MHT correction",
"Significance threshold")
# Alpha diversity
div.cols <- c("Pielou",
"Shannon",
"Chao1",
"Simpson",
"Inverse Simpson",
"Richness")Restrict dataset to experiment information:
Subjects
Number of experiments for the top 10 categories for each subjects column:
## $`Host species`
##
## Homo sapiens Mus musculus Canis lupus familiaris
## 3413 410 69
## Sus scrofa domesticus Rattus norvegicus Not specified
## 69 38 23
## Capra hircus Macaca mulatta Bos taurus
## 14 13 12
## Chlorocebus pygerythrus
## 12
##
## $`Location of subjects`
##
## China United States of America Denmark
## 1152 846 150
## Japan Italy Germany
## 138 106 100
## Australia South Korea Canada
## 89 88 86
## Spain
## 84
##
## $`Body site`
##
## Feces Saliva Vagina
## 2461 275 88
## Mouth Nasopharynx Skin of body
## 62 48 47
## Subgingival dental plaque Uterine cervix Throat
## 45 44 36
## Colon
## 35
##
## $Condition
##
## Parkinson's disease Obesity Colorectal cancer Diet
## 165 136 119 118
## COVID-19 Atopic eczema Antimicrobial agent Alzheimer's disease
## 116 90 85 76
## Extraction protocol HIV infection
## 69 63
##
## $`Antibiotics exclusion`
##
## 3 months 1 month 2 months 6 months 2 weeks 4 weeks N/A 30 days
## 409 317 191 140 116 83 39 24
## 6 Months 1 week
## 22 15Proportions instead:
sub.tab <- lapply(sub.cols[1:5], tabCol, df = exps, n = 10, perc = TRUE)
names(sub.tab) <- sub.cols[1:5]
sub.tab## $`Host species`
##
## Homo sapiens Mus musculus Canis lupus familiaris
## 0.81500 0.09790 0.01650
## Sus scrofa domesticus Rattus norvegicus Not specified
## 0.01650 0.00908 0.00549
## Capra hircus Macaca mulatta Bos taurus
## 0.00334 0.00310 0.00287
## Chlorocebus pygerythrus
## 0.00287
##
## $`Location of subjects`
##
## China United States of America Denmark
## 0.2750 0.2020 0.0359
## Japan Italy Germany
## 0.0330 0.0253 0.0239
## Australia South Korea Canada
## 0.0213 0.0210 0.0206
## Spain
## 0.0201
##
## $`Body site`
##
## Feces Saliva Vagina
## 0.58800 0.06570 0.02100
## Mouth Nasopharynx Skin of body
## 0.01480 0.01150 0.01120
## Subgingival dental plaque Uterine cervix Throat
## 0.01070 0.01050 0.00860
## Colon
## 0.00836
##
## $Condition
##
## Parkinson's disease Obesity Colorectal cancer Diet
## 0.0394 0.0325 0.0284 0.0282
## COVID-19 Atopic eczema Antimicrobial agent Alzheimer's disease
## 0.0277 0.0215 0.0203 0.0182
## Extraction protocol HIV infection
## 0.0165 0.0150
##
## $`Antibiotics exclusion`
##
## 3 months 1 month 2 months 6 months 2 weeks 4 weeks N/A 30 days
## 0.20300 0.15700 0.09470 0.06940 0.05750 0.04120 0.01930 0.01190
## 6 Months 1 week
## 0.01090 0.00744Sample size:
ssize <- apply(exps[,sub.cols[6:7]], 2, summary)
ssize## Group 0 sample size Group 1 sample size
## Min. 0.0000 1.00000
## 1st Qu. 12.0000 11.00000
## Median 25.0000 22.00000
## Mean 510.9824 67.08279
## 3rd Qu. 50.0000 44.00000
## Max. 344569.0000 9623.00000
## NA's 325.0000 322.00000Lab analysis
Number of experiments for the top 10 categories for each lab analysis column:
## $`Sequencing type`
##
## 16S WMS PCR ITS / ITS2 18S
## 3504 573 52 25 1
##
## $`16S variable region`
##
## 34 4 12 123 45 345 3 56
## 1279 1026 277 204 130 129 52 27
## 23 23456789
## 21 17
##
## $`Sequencing platform`
##
## Illumina Roche454
## 3370 306
## Ion Torrent RT-qPCR
## 192 103
## MGISEQ-2000 PacBio RS
## 37 23
## Human Intestinal Tract Chip BGISEQ-500 Sequencing
## 17 13
## Illumina,Roche454 Mass spectrometry
## 11 10Proportions instead:
lab.tab <- lapply(lab.cols, tabCol, df = exps, n = 10, perc = TRUE)
names(lab.tab) <- lab.cols
lab.tab## $`Sequencing type`
##
## 16S WMS PCR ITS / ITS2 18S
## 0.843000 0.138000 0.012500 0.006020 0.000241
##
## $`16S variable region`
##
## 34 4 12 123 45 345 3 56
## 0.39300 0.31500 0.08510 0.06270 0.03990 0.03960 0.01600 0.00829
## 23 23456789
## 0.00645 0.00522
##
## $`Sequencing platform`
##
## Illumina Roche454
## 0.81800 0.07430
## Ion Torrent RT-qPCR
## 0.04660 0.02500
## MGISEQ-2000 PacBio RS
## 0.00898 0.00559
## Human Intestinal Tract Chip BGISEQ-500 Sequencing
## 0.00413 0.00316
## Illumina,Roche454 Mass spectrometry
## 0.00267 0.00243Statistical analysis
Number of experiments for the top 10 categories for each statistical analysis column:
## $`Statistical test`
##
## LEfSe Mann-Whitney (Wilcoxon) DESeq2
## 1352 683 498
## Linear Regression Kruskall-Wallis ANOVA
## 205 196 173
## ANCOM T-Test MaAsLin2
## 155 142 106
## Metastats
## 62
##
## $`MHT correction`
##
## TRUE FALSE
## 2231 1568
##
## $`Significance threshold`
##
## 0.05 0.1 0.01 0.001 0.25 0.2 0.15 2 0.005 1e-04
## 3583 255 99 28 27 22 19 15 13 6Proportions instead:
stat.tab <- lapply(stat.cols, tabCol, df = exps, n = 10, perc = TRUE)
names(stat.tab) <- stat.cols
stat.tab## $`Statistical test`
##
## LEfSe Mann-Whitney (Wilcoxon) DESeq2
## 0.3290 0.1660 0.1210
## Linear Regression Kruskall-Wallis ANOVA
## 0.0499 0.0477 0.0421
## ANCOM T-Test MaAsLin2
## 0.0377 0.0346 0.0258
## Metastats
## 0.0151
##
## $`MHT correction`
##
## TRUE FALSE
## 0.587 0.413
##
## $`Significance threshold`
##
## 0.05 0.1 0.01 0.001 0.25 0.2 0.15 2 0.005 1e-04
## 0.87700 0.06240 0.02420 0.00685 0.00661 0.00538 0.00465 0.00367 0.00318 0.00147Alpha diversity
Overall distribution:
apply(exps[,div.cols], 2, table)## Pielou Shannon Chao1 Simpson Inverse Simpson Richness
## decreased 36 598 369 173 56 365
## increased 27 471 254 130 30 271
## unchanged 132 1556 728 583 170 745Correspondence of Shannon diversity and Richness:
table(exps$Shannon, exps$Richness)##
## decreased increased unchanged
## decreased 198 11 41
## increased 9 136 46
## unchanged 75 74 593Conditions with consistently increased or decreased alpha diversity:
tabDiv(exps, "Shannon", "Condition")## increased decreased
## COVID-19 9 24
## Obesity 3 16
## HIV infection 1 12
## Clostridium difficile infection 10 0
## Dry eye syndrome 1 11
## Systemic inflammatory response syndrome 5 15
## Human papilloma virus infection 10 1
## Gastric cancer 6 14
## Treatment outcome measurement 3 11
## Ulcerative colitis 0 8
## Age 5 12
## Aging 0 7
## Alzheimer's disease 2 9
## Polycystic ovary syndrome 0 7
## Atopic eczema 5 11
## Autism spectrum disorder 7 1
## Cesarean section 6 0
## Epilepsy 6 0
## Lung cancer 2 8
## Response to allogeneic hematopoietic stem cell transplant 0 6
## Urinary tract infection 0 6
## Cervical cancer 5 0
## Diet 14 19
## Helminthiasis 5 0
## Population 2 7
## Spontaneous preterm birth 12 7
## Acute lymphoblastic leukemia 0 4
## Acute pancreatitis 0 4
## Colorectal cancer 10 14
## Crohn's disease 0 4
## Endometrial cancer 4 0
## Ethnic group 3 7
## Food allergy 6 2
## Human immunodeficiency virus 0 4
## Hypertension 7 3
## Irritable bowel syndrome 1 5
## Parkinson's disease 18 14
## Periodontitis 5 1
## Pregnancy 4 0
## Alcohol drinking 3 0
## Atopic asthma 4 1
## Chronic obstructive pulmonary disease 3 0
## Delivery method 1 4
## Diarrhea 6 3
## Extraction protocol 23 26
## Male homosexuality 3 0
## Oral lichen planus 3 0
## Schizophrenia 1 4
## Age at assessment 3 1
## Antimicrobial agent 8 10
## Breed 0 2
## Cervical glandular intraepithelial neoplasia 2 0
## Chronic kidney disease 2 4
## Cognitive impairment 1 3
## Depressive disorder 0 2
## Eczema 0 2
## Esophageal adenocarcinoma 0 2
## Iron biomarker measurement 1 3
## Milk allergic reaction 2 0
## Oral squamous cell carcinoma 2 0
## Papillary thyroid carcinoma 2 0
## Phenylketonuria 1 3
## Response to anti-tuberculosis drug 8 10
## Response to antibiotic 0 2
## Response to antiviral drug 2 4
## Response to immunochemotherapy 3 1
## Response to ketogenic diet 0 2
## Sampling site 3 1
## Smoking behavior 10 8
## Squamous cell carcinoma 2 0
## Streptococcus pneumoniae 0 2
## Stroke 2 0
## Acute respiratory failure 6 5
## Air pollution 7 6
## Anxiety disorder 0 1
## Breast cancer 3 4
## Breastfeeding duration 2 3
## Chlamydia trachomatis 1 2
## Chronic fatigue syndrome 0 1
## Chronic hepatitis B virus infection 0 1
## Diabetes mellitus 0 1
## Endometriosis 2 3
## Esophageal cancer 1 2
## Gestational diabetes 1 0
## Hepatocellular carcinoma 0 1
## Hypertrophy 1 0
## Lifestyle measurement 0 1
## Multiple sclerosis 0 1
## Oral cavity carcinoma 0 1
## Pancreatic carcinoma 0 1
## Psoriasis 1 0
## Response to transplant 3 2
## Response to vaccine 1 0
## Rheumatoid arthritis 5 4
## Sample treatment protocol 1 0
## Sampling time 4 3
## Social interaction measurement 2 1
## Socioeconomic status 3 4
## Vesicle membrane 3 2
## Vitiligo 0 1
## Acute myeloid leukemia 1 1
## Arthritis 0 0
## Asthma 1 1
## Bipolar disorder 0 0
## Celiac disease 0 0
## Colorectal adenoma 2 2
## Contraception 0 0
## COVID-19 symptoms measurement 0 0
## Disease progression measurement 0 0
## Health study participation 2 2
## HIV mother to child transmission 0 0
## Lactose intolerance 0 0
## Lung transplantation 2 2
## Obsessive-compulsive disorder 0 0
## Ovarian cancer 3 3
## Phenotype 2 2
## Response to diet 6 6
## SARS coronavirus 0 0
## Simian immunodeficiency virus infection 0 0
## Type II diabetes mellitus 2 2
## Viral load 0 0
## Waist circumference 0 0
## unchanged
## COVID-19 42
## Obesity 55
## HIV infection 24
## Clostridium difficile infection 1
## Dry eye syndrome 11
## Systemic inflammatory response syndrome 4
## Human papilloma virus infection 26
## Gastric cancer 26
## Treatment outcome measurement 25
## Ulcerative colitis 3
## Age 8
## Aging 0
## Alzheimer's disease 24
## Polycystic ovary syndrome 8
## Atopic eczema 72
## Autism spectrum disorder 8
## Cesarean section 16
## Epilepsy 5
## Lung cancer 5
## Response to allogeneic hematopoietic stem cell transplant 0
## Urinary tract infection 8
## Cervical cancer 5
## Diet 36
## Helminthiasis 8
## Population 25
## Spontaneous preterm birth 5
## Acute lymphoblastic leukemia 5
## Acute pancreatitis 2
## Colorectal cancer 43
## Crohn's disease 4
## Endometrial cancer 3
## Ethnic group 6
## Food allergy 18
## Human immunodeficiency virus 5
## Hypertension 6
## Irritable bowel syndrome 12
## Parkinson's disease 70
## Periodontitis 10
## Pregnancy 2
## Alcohol drinking 2
## Atopic asthma 7
## Chronic obstructive pulmonary disease 2
## Delivery method 2
## Diarrhea 6
## Extraction protocol 20
## Male homosexuality 6
## Oral lichen planus 4
## Schizophrenia 14
## Age at assessment 1
## Antimicrobial agent 25
## Breed 7
## Cervical glandular intraepithelial neoplasia 9
## Chronic kidney disease 3
## Cognitive impairment 8
## Depressive disorder 4
## Eczema 10
## Esophageal adenocarcinoma 4
## Iron biomarker measurement 2
## Milk allergic reaction 5
## Oral squamous cell carcinoma 3
## Papillary thyroid carcinoma 10
## Phenylketonuria 4
## Response to anti-tuberculosis drug 13
## Response to antibiotic 6
## Response to antiviral drug 5
## Response to immunochemotherapy 3
## Response to ketogenic diet 4
## Sampling site 7
## Smoking behavior 20
## Squamous cell carcinoma 4
## Streptococcus pneumoniae 4
## Stroke 15
## Acute respiratory failure 0
## Air pollution 3
## Anxiety disorder 7
## Breast cancer 16
## Breastfeeding duration 5
## Chlamydia trachomatis 2
## Chronic fatigue syndrome 4
## Chronic hepatitis B virus infection 5
## Diabetes mellitus 5
## Endometriosis 11
## Esophageal cancer 2
## Gestational diabetes 31
## Hepatocellular carcinoma 6
## Hypertrophy 4
## Lifestyle measurement 8
## Multiple sclerosis 15
## Oral cavity carcinoma 7
## Pancreatic carcinoma 4
## Psoriasis 4
## Response to transplant 8
## Response to vaccine 5
## Rheumatoid arthritis 9
## Sample treatment protocol 4
## Sampling time 5
## Social interaction measurement 6
## Socioeconomic status 8
## Vesicle membrane 1
## Vitiligo 4
## Acute myeloid leukemia 4
## Arthritis 6
## Asthma 14
## Bipolar disorder 5
## Celiac disease 6
## Colorectal adenoma 10
## Contraception 5
## COVID-19 symptoms measurement 5
## Disease progression measurement 5
## Health study participation 18
## HIV mother to child transmission 8
## Lactose intolerance 5
## Lung transplantation 2
## Obsessive-compulsive disorder 5
## Ovarian cancer 27
## Phenotype 19
## Response to diet 19
## SARS coronavirus 6
## Simian immunodeficiency virus infection 5
## Type II diabetes mellitus 23
## Viral load 6
## Waist circumference 5
tabDiv(exps, "Shannon", "Condition", perc = TRUE)## increased decreased
## COVID-19 0.120 0.320
## Obesity 0.041 0.220
## HIV infection 0.027 0.320
## Clostridium difficile infection 0.910 0.000
## Dry eye syndrome 0.043 0.480
## Systemic inflammatory response syndrome 0.210 0.620
## Human papilloma virus infection 0.270 0.027
## Gastric cancer 0.130 0.300
## Treatment outcome measurement 0.077 0.280
## Ulcerative colitis 0.000 0.730
## Age 0.200 0.480
## Aging 0.000 1.000
## Alzheimer's disease 0.057 0.260
## Polycystic ovary syndrome 0.000 0.470
## Atopic eczema 0.057 0.120
## Autism spectrum disorder 0.440 0.062
## Cesarean section 0.270 0.000
## Epilepsy 0.550 0.000
## Lung cancer 0.130 0.530
## Response to allogeneic hematopoietic stem cell transplant 0.000 1.000
## Urinary tract infection 0.000 0.430
## Cervical cancer 0.500 0.000
## Diet 0.200 0.280
## Helminthiasis 0.380 0.000
## Population 0.059 0.210
## Spontaneous preterm birth 0.500 0.290
## Acute lymphoblastic leukemia 0.000 0.440
## Acute pancreatitis 0.000 0.670
## Colorectal cancer 0.150 0.210
## Crohn's disease 0.000 0.500
## Endometrial cancer 0.570 0.000
## Ethnic group 0.190 0.440
## Food allergy 0.230 0.077
## Human immunodeficiency virus 0.000 0.440
## Hypertension 0.440 0.190
## Irritable bowel syndrome 0.056 0.280
## Parkinson's disease 0.180 0.140
## Periodontitis 0.310 0.062
## Pregnancy 0.670 0.000
## Alcohol drinking 0.600 0.000
## Atopic asthma 0.330 0.083
## Chronic obstructive pulmonary disease 0.600 0.000
## Delivery method 0.140 0.570
## Diarrhea 0.400 0.200
## Extraction protocol 0.330 0.380
## Male homosexuality 0.330 0.000
## Oral lichen planus 0.430 0.000
## Schizophrenia 0.053 0.210
## Age at assessment 0.600 0.200
## Antimicrobial agent 0.190 0.230
## Breed 0.000 0.220
## Cervical glandular intraepithelial neoplasia 0.180 0.000
## Chronic kidney disease 0.220 0.440
## Cognitive impairment 0.083 0.250
## Depressive disorder 0.000 0.330
## Eczema 0.000 0.170
## Esophageal adenocarcinoma 0.000 0.330
## Iron biomarker measurement 0.170 0.500
## Milk allergic reaction 0.290 0.000
## Oral squamous cell carcinoma 0.400 0.000
## Papillary thyroid carcinoma 0.170 0.000
## Phenylketonuria 0.120 0.380
## Response to anti-tuberculosis drug 0.260 0.320
## Response to antibiotic 0.000 0.250
## Response to antiviral drug 0.180 0.360
## Response to immunochemotherapy 0.430 0.140
## Response to ketogenic diet 0.000 0.330
## Sampling site 0.270 0.091
## Smoking behavior 0.260 0.210
## Squamous cell carcinoma 0.330 0.000
## Streptococcus pneumoniae 0.000 0.330
## Stroke 0.120 0.000
## Acute respiratory failure 0.550 0.450
## Air pollution 0.440 0.380
## Anxiety disorder 0.000 0.120
## Breast cancer 0.130 0.170
## Breastfeeding duration 0.200 0.300
## Chlamydia trachomatis 0.200 0.400
## Chronic fatigue syndrome 0.000 0.200
## Chronic hepatitis B virus infection 0.000 0.170
## Diabetes mellitus 0.000 0.170
## Endometriosis 0.120 0.190
## Esophageal cancer 0.200 0.400
## Gestational diabetes 0.031 0.000
## Hepatocellular carcinoma 0.000 0.140
## Hypertrophy 0.200 0.000
## Lifestyle measurement 0.000 0.110
## Multiple sclerosis 0.000 0.062
## Oral cavity carcinoma 0.000 0.120
## Pancreatic carcinoma 0.000 0.200
## Psoriasis 0.200 0.000
## Response to transplant 0.230 0.150
## Response to vaccine 0.170 0.000
## Rheumatoid arthritis 0.280 0.220
## Sample treatment protocol 0.200 0.000
## Sampling time 0.330 0.250
## Social interaction measurement 0.220 0.110
## Socioeconomic status 0.200 0.270
## Vesicle membrane 0.500 0.330
## Vitiligo 0.000 0.200
## Acute myeloid leukemia 0.170 0.170
## Arthritis 0.000 0.000
## Asthma 0.062 0.062
## Bipolar disorder 0.000 0.000
## Celiac disease 0.000 0.000
## Colorectal adenoma 0.140 0.140
## Contraception 0.000 0.000
## COVID-19 symptoms measurement 0.000 0.000
## Disease progression measurement 0.000 0.000
## Health study participation 0.091 0.091
## HIV mother to child transmission 0.000 0.000
## Lactose intolerance 0.000 0.000
## Lung transplantation 0.330 0.330
## Obsessive-compulsive disorder 0.000 0.000
## Ovarian cancer 0.091 0.091
## Phenotype 0.087 0.087
## Response to diet 0.190 0.190
## SARS coronavirus 0.000 0.000
## Simian immunodeficiency virus infection 0.000 0.000
## Type II diabetes mellitus 0.074 0.074
## Viral load 0.000 0.000
## Waist circumference 0.000 0.000
## unchanged
## COVID-19 0.560
## Obesity 0.740
## HIV infection 0.650
## Clostridium difficile infection 0.091
## Dry eye syndrome 0.480
## Systemic inflammatory response syndrome 0.170
## Human papilloma virus infection 0.700
## Gastric cancer 0.570
## Treatment outcome measurement 0.640
## Ulcerative colitis 0.270
## Age 0.320
## Aging 0.000
## Alzheimer's disease 0.690
## Polycystic ovary syndrome 0.530
## Atopic eczema 0.820
## Autism spectrum disorder 0.500
## Cesarean section 0.730
## Epilepsy 0.450
## Lung cancer 0.330
## Response to allogeneic hematopoietic stem cell transplant 0.000
## Urinary tract infection 0.570
## Cervical cancer 0.500
## Diet 0.520
## Helminthiasis 0.620
## Population 0.740
## Spontaneous preterm birth 0.210
## Acute lymphoblastic leukemia 0.560
## Acute pancreatitis 0.330
## Colorectal cancer 0.640
## Crohn's disease 0.500
## Endometrial cancer 0.430
## Ethnic group 0.380
## Food allergy 0.690
## Human immunodeficiency virus 0.560
## Hypertension 0.380
## Irritable bowel syndrome 0.670
## Parkinson's disease 0.690
## Periodontitis 0.620
## Pregnancy 0.330
## Alcohol drinking 0.400
## Atopic asthma 0.580
## Chronic obstructive pulmonary disease 0.400
## Delivery method 0.290
## Diarrhea 0.400
## Extraction protocol 0.290
## Male homosexuality 0.670
## Oral lichen planus 0.570
## Schizophrenia 0.740
## Age at assessment 0.200
## Antimicrobial agent 0.580
## Breed 0.780
## Cervical glandular intraepithelial neoplasia 0.820
## Chronic kidney disease 0.330
## Cognitive impairment 0.670
## Depressive disorder 0.670
## Eczema 0.830
## Esophageal adenocarcinoma 0.670
## Iron biomarker measurement 0.330
## Milk allergic reaction 0.710
## Oral squamous cell carcinoma 0.600
## Papillary thyroid carcinoma 0.830
## Phenylketonuria 0.500
## Response to anti-tuberculosis drug 0.420
## Response to antibiotic 0.750
## Response to antiviral drug 0.450
## Response to immunochemotherapy 0.430
## Response to ketogenic diet 0.670
## Sampling site 0.640
## Smoking behavior 0.530
## Squamous cell carcinoma 0.670
## Streptococcus pneumoniae 0.670
## Stroke 0.880
## Acute respiratory failure 0.000
## Air pollution 0.190
## Anxiety disorder 0.880
## Breast cancer 0.700
## Breastfeeding duration 0.500
## Chlamydia trachomatis 0.400
## Chronic fatigue syndrome 0.800
## Chronic hepatitis B virus infection 0.830
## Diabetes mellitus 0.830
## Endometriosis 0.690
## Esophageal cancer 0.400
## Gestational diabetes 0.970
## Hepatocellular carcinoma 0.860
## Hypertrophy 0.800
## Lifestyle measurement 0.890
## Multiple sclerosis 0.940
## Oral cavity carcinoma 0.880
## Pancreatic carcinoma 0.800
## Psoriasis 0.800
## Response to transplant 0.620
## Response to vaccine 0.830
## Rheumatoid arthritis 0.500
## Sample treatment protocol 0.800
## Sampling time 0.420
## Social interaction measurement 0.670
## Socioeconomic status 0.530
## Vesicle membrane 0.170
## Vitiligo 0.800
## Acute myeloid leukemia 0.670
## Arthritis 1.000
## Asthma 0.880
## Bipolar disorder 1.000
## Celiac disease 1.000
## Colorectal adenoma 0.710
## Contraception 1.000
## COVID-19 symptoms measurement 1.000
## Disease progression measurement 1.000
## Health study participation 0.820
## HIV mother to child transmission 1.000
## Lactose intolerance 1.000
## Lung transplantation 0.330
## Obsessive-compulsive disorder 1.000
## Ovarian cancer 0.820
## Phenotype 0.830
## Response to diet 0.610
## SARS coronavirus 1.000
## Simian immunodeficiency virus infection 1.000
## Type II diabetes mellitus 0.850
## Viral load 1.000
## Waist circumference 1.000
tabDiv(exps, "Richness", "Condition")## increased decreased
## Diet 4 19
## Helminthiasis 13 0
## HIV infection 3 16
## Parkinson's disease 15 27
## Treatment outcome measurement 2 14
## COVID-19 9 20
## Phenotype 9 1
## Diarrhea 8 1
## Response to allogeneic hematopoietic stem cell transplant 0 6
## Alcohol drinking 5 0
## Antimicrobial agent 2 7
## Gestational diabetes 1 6
## Human immunodeficiency virus 1 6
## Human papilloma virus infection 7 2
## Irritable bowel syndrome 0 5
## Polycystic ovary syndrome 0 5
## Acute lymphoblastic leukemia 5 1
## Age 1 5
## Air pollution 9 5
## Cervical glandular intraepithelial neoplasia 4 0
## Dry eye syndrome 0 4
## Endometriosis 4 0
## Epilepsy 4 0
## Periodontitis 5 1
## Schizophrenia 1 5
## Vesicle membrane 5 1
## Atopic asthma 4 1
## Delivery method 4 1
## Food allergy 0 3
## Gastric cancer 5 8
## Hypertrophy 3 0
## Iron biomarker measurement 1 4
## Asthma 2 0
## Autism spectrum disorder 4 6
## Breast cancer 2 0
## Esophageal adenocarcinoma 0 2
## Hypertension 1 3
## Phenylketonuria 1 3
## Smoking behavior 6 8
## Streptococcus pneumoniae 0 2
## Alzheimer's disease 6 5
## Atopic eczema 2 1
## Breastfeeding duration 1 0
## Cesarean section 3 2
## Colorectal adenoma 1 2
## Head and neck squamous cell carcinoma 0 1
## Health study participation 1 0
## Inflammatory bowel disease 2 3
## Lung cancer 0 1
## Obesity 8 7
## Obsessive-compulsive disorder 0 1
## Ovarian cancer 1 0
## Psoriasis 0 1
## Response to transplant 0 1
## Rheumatoid arthritis 3 4
## Sampling site 1 2
## Socioeconomic status 2 1
## Transport 1 2
## Type II diabetes mellitus 2 3
## Urinary tract infection 0 1
## Chlamydia trachomatis 1 1
## Colorectal cancer 6 6
## Ethnic group 2 2
## HIV mother to child transmission 0 0
## Male homosexuality 0 0
## Multiple sclerosis 0 0
## Papillary thyroid carcinoma 0 0
## Physical activity 2 2
## Stroke 2 2
## Viral load 0 0
## unchanged
## Diet 12
## Helminthiasis 0
## HIV infection 10
## Parkinson's disease 23
## Treatment outcome measurement 21
## COVID-19 24
## Phenotype 11
## Diarrhea 4
## Response to allogeneic hematopoietic stem cell transplant 0
## Alcohol drinking 0
## Antimicrobial agent 10
## Gestational diabetes 23
## Human immunodeficiency virus 2
## Human papilloma virus infection 12
## Irritable bowel syndrome 9
## Polycystic ovary syndrome 1
## Acute lymphoblastic leukemia 0
## Age 1
## Air pollution 6
## Cervical glandular intraepithelial neoplasia 2
## Dry eye syndrome 3
## Endometriosis 6
## Epilepsy 1
## Periodontitis 6
## Schizophrenia 8
## Vesicle membrane 0
## Atopic asthma 7
## Delivery method 1
## Food allergy 9
## Gastric cancer 14
## Hypertrophy 2
## Iron biomarker measurement 1
## Asthma 10
## Autism spectrum disorder 0
## Breast cancer 7
## Esophageal adenocarcinoma 4
## Hypertension 6
## Phenylketonuria 4
## Smoking behavior 8
## Streptococcus pneumoniae 3
## Alzheimer's disease 22
## Atopic eczema 6
## Breastfeeding duration 5
## Cesarean section 10
## Colorectal adenoma 11
## Head and neck squamous cell carcinoma 4
## Health study participation 11
## Inflammatory bowel disease 0
## Lung cancer 8
## Obesity 19
## Obsessive-compulsive disorder 4
## Ovarian cancer 30
## Psoriasis 5
## Response to transplant 8
## Rheumatoid arthritis 1
## Sampling site 2
## Socioeconomic status 2
## Transport 3
## Type II diabetes mellitus 9
## Urinary tract infection 6
## Chlamydia trachomatis 3
## Colorectal cancer 19
## Ethnic group 1
## HIV mother to child transmission 8
## Male homosexuality 9
## Multiple sclerosis 17
## Papillary thyroid carcinoma 12
## Physical activity 1
## Stroke 16
## Viral load 5
tabDiv(exps, "Richness", "Condition", perc = TRUE)## increased decreased
## Diet 0.110 0.540
## Helminthiasis 1.000 0.000
## HIV infection 0.100 0.550
## Parkinson's disease 0.230 0.420
## Treatment outcome measurement 0.054 0.380
## COVID-19 0.170 0.380
## Phenotype 0.430 0.048
## Diarrhea 0.620 0.077
## Response to allogeneic hematopoietic stem cell transplant 0.000 1.000
## Alcohol drinking 1.000 0.000
## Antimicrobial agent 0.110 0.370
## Gestational diabetes 0.033 0.200
## Human immunodeficiency virus 0.110 0.670
## Human papilloma virus infection 0.330 0.095
## Irritable bowel syndrome 0.000 0.360
## Polycystic ovary syndrome 0.000 0.830
## Acute lymphoblastic leukemia 0.830 0.170
## Age 0.140 0.710
## Air pollution 0.450 0.250
## Cervical glandular intraepithelial neoplasia 0.670 0.000
## Dry eye syndrome 0.000 0.570
## Endometriosis 0.400 0.000
## Epilepsy 0.800 0.000
## Periodontitis 0.420 0.083
## Schizophrenia 0.071 0.360
## Vesicle membrane 0.830 0.170
## Atopic asthma 0.330 0.083
## Delivery method 0.670 0.170
## Food allergy 0.000 0.250
## Gastric cancer 0.190 0.300
## Hypertrophy 0.600 0.000
## Iron biomarker measurement 0.170 0.670
## Asthma 0.170 0.000
## Autism spectrum disorder 0.400 0.600
## Breast cancer 0.220 0.000
## Esophageal adenocarcinoma 0.000 0.330
## Hypertension 0.100 0.300
## Phenylketonuria 0.120 0.380
## Smoking behavior 0.270 0.360
## Streptococcus pneumoniae 0.000 0.400
## Alzheimer's disease 0.180 0.150
## Atopic eczema 0.220 0.110
## Breastfeeding duration 0.170 0.000
## Cesarean section 0.200 0.130
## Colorectal adenoma 0.071 0.140
## Head and neck squamous cell carcinoma 0.000 0.200
## Health study participation 0.083 0.000
## Inflammatory bowel disease 0.400 0.600
## Lung cancer 0.000 0.110
## Obesity 0.240 0.210
## Obsessive-compulsive disorder 0.000 0.200
## Ovarian cancer 0.032 0.000
## Psoriasis 0.000 0.170
## Response to transplant 0.000 0.110
## Rheumatoid arthritis 0.380 0.500
## Sampling site 0.200 0.400
## Socioeconomic status 0.400 0.200
## Transport 0.170 0.330
## Type II diabetes mellitus 0.140 0.210
## Urinary tract infection 0.000 0.140
## Chlamydia trachomatis 0.200 0.200
## Colorectal cancer 0.190 0.190
## Ethnic group 0.400 0.400
## HIV mother to child transmission 0.000 0.000
## Male homosexuality 0.000 0.000
## Multiple sclerosis 0.000 0.000
## Papillary thyroid carcinoma 0.000 0.000
## Physical activity 0.400 0.400
## Stroke 0.100 0.100
## Viral load 0.000 0.000
## unchanged
## Diet 0.34
## Helminthiasis 0.00
## HIV infection 0.34
## Parkinson's disease 0.35
## Treatment outcome measurement 0.57
## COVID-19 0.45
## Phenotype 0.52
## Diarrhea 0.31
## Response to allogeneic hematopoietic stem cell transplant 0.00
## Alcohol drinking 0.00
## Antimicrobial agent 0.53
## Gestational diabetes 0.77
## Human immunodeficiency virus 0.22
## Human papilloma virus infection 0.57
## Irritable bowel syndrome 0.64
## Polycystic ovary syndrome 0.17
## Acute lymphoblastic leukemia 0.00
## Age 0.14
## Air pollution 0.30
## Cervical glandular intraepithelial neoplasia 0.33
## Dry eye syndrome 0.43
## Endometriosis 0.60
## Epilepsy 0.20
## Periodontitis 0.50
## Schizophrenia 0.57
## Vesicle membrane 0.00
## Atopic asthma 0.58
## Delivery method 0.17
## Food allergy 0.75
## Gastric cancer 0.52
## Hypertrophy 0.40
## Iron biomarker measurement 0.17
## Asthma 0.83
## Autism spectrum disorder 0.00
## Breast cancer 0.78
## Esophageal adenocarcinoma 0.67
## Hypertension 0.60
## Phenylketonuria 0.50
## Smoking behavior 0.36
## Streptococcus pneumoniae 0.60
## Alzheimer's disease 0.67
## Atopic eczema 0.67
## Breastfeeding duration 0.83
## Cesarean section 0.67
## Colorectal adenoma 0.79
## Head and neck squamous cell carcinoma 0.80
## Health study participation 0.92
## Inflammatory bowel disease 0.00
## Lung cancer 0.89
## Obesity 0.56
## Obsessive-compulsive disorder 0.80
## Ovarian cancer 0.97
## Psoriasis 0.83
## Response to transplant 0.89
## Rheumatoid arthritis 0.12
## Sampling site 0.40
## Socioeconomic status 0.40
## Transport 0.50
## Type II diabetes mellitus 0.64
## Urinary tract infection 0.86
## Chlamydia trachomatis 0.60
## Colorectal cancer 0.61
## Ethnic group 0.20
## HIV mother to child transmission 1.00
## Male homosexuality 1.00
## Multiple sclerosis 1.00
## Papillary thyroid carcinoma 1.00
## Physical activity 0.20
## Stroke 0.80
## Viral load 1.00Body sites with consistently increased or decreased alpha diversity:
tabDiv(exps, "Shannon", "Body site")## increased decreased unchanged
## Feces 239 375 877
## Vagina 15 6 25
## Skin of body 7 15 8
## Uterine cervix,Vaginal fluid 9 1 0
## Posterior fornix of vagina 7 0 3
## Uterine cervix 8 1 20
## Subgingival dental plaque 9 3 20
## Buccal mucosa 5 0 2
## Meconium 5 0 10
## Space surrounding organism 2 7 13
## Stomach 5 10 5
## Tongue 0 5 12
## Axilla skin 5 1 11
## Tear film 0 4 1
## Throat 0 4 8
## Caecum 1 4 10
## Colorectal mucosa 0 3 8
## Dental plaque 0 3 3
## Duodenum 0 3 5
## Skin of forearm 3 0 3
## Small intestine 1 4 1
## Bile 2 0 3
## Brachialis muscle 0 2 3
## Cecum mucosa 1 3 2
## Conjunctiva 1 3 6
## Conjunctival sac 1 3 1
## Esophagus 0 2 4
## Forelimb skin 2 0 4
## Lung 2 4 7
## Mouth 8 6 26
## Nasopharynx 3 5 28
## Saliva 34 36 115
## Supragingival dental plaque 1 3 1
## Thyroid gland 2 0 10
## Uterus 3 1 11
## Blood 0 1 6
## Breast 3 4 4
## Breast,Milk 1 0 4
## Bulbar conjunctiva 3 2 5
## Colon 3 2 14
## Ileum 1 0 9
## Nasal cavity 0 1 5
## Oral cavity 4 3 5
## Oropharynx 1 2 3
## Vagina,Uterine cervix 3 2 7
## Vaginal fluid 1 0 5
## Bronchus 0 0 6
## Endothelium of trachea 3 3 0
## Intestine 1 1 14
## Jejunum 0 0 8
## Milk 0 0 7
## Ovary 0 0 7
## Peritoneal fluid 0 0 6
## Posterior wall of oropharynx 2 2 1
## Rectum 0 0 12
## Skin of abdomen 0 0 5
## Sputum 6 6 8
## Surface of tongue 2 2 3
## Urine 1 1 16
## Ventral side of post-anal tail 0 0 6
tabDiv(exps, "Shannon", "Body site", perc = TRUE)## increased decreased unchanged
## Feces 0.160 0.250 0.59
## Vagina 0.330 0.130 0.54
## Skin of body 0.230 0.500 0.27
## Uterine cervix,Vaginal fluid 0.900 0.100 0.00
## Posterior fornix of vagina 0.700 0.000 0.30
## Uterine cervix 0.280 0.034 0.69
## Subgingival dental plaque 0.280 0.094 0.62
## Buccal mucosa 0.710 0.000 0.29
## Meconium 0.330 0.000 0.67
## Space surrounding organism 0.091 0.320 0.59
## Stomach 0.250 0.500 0.25
## Tongue 0.000 0.290 0.71
## Axilla skin 0.290 0.059 0.65
## Tear film 0.000 0.800 0.20
## Throat 0.000 0.330 0.67
## Caecum 0.067 0.270 0.67
## Colorectal mucosa 0.000 0.270 0.73
## Dental plaque 0.000 0.500 0.50
## Duodenum 0.000 0.380 0.62
## Skin of forearm 0.500 0.000 0.50
## Small intestine 0.170 0.670 0.17
## Bile 0.400 0.000 0.60
## Brachialis muscle 0.000 0.400 0.60
## Cecum mucosa 0.170 0.500 0.33
## Conjunctiva 0.100 0.300 0.60
## Conjunctival sac 0.200 0.600 0.20
## Esophagus 0.000 0.330 0.67
## Forelimb skin 0.330 0.000 0.67
## Lung 0.150 0.310 0.54
## Mouth 0.200 0.150 0.65
## Nasopharynx 0.083 0.140 0.78
## Saliva 0.180 0.190 0.62
## Supragingival dental plaque 0.200 0.600 0.20
## Thyroid gland 0.170 0.000 0.83
## Uterus 0.200 0.067 0.73
## Blood 0.000 0.140 0.86
## Breast 0.270 0.360 0.36
## Breast,Milk 0.200 0.000 0.80
## Bulbar conjunctiva 0.300 0.200 0.50
## Colon 0.160 0.110 0.74
## Ileum 0.100 0.000 0.90
## Nasal cavity 0.000 0.170 0.83
## Oral cavity 0.330 0.250 0.42
## Oropharynx 0.170 0.330 0.50
## Vagina,Uterine cervix 0.250 0.170 0.58
## Vaginal fluid 0.170 0.000 0.83
## Bronchus 0.000 0.000 1.00
## Endothelium of trachea 0.500 0.500 0.00
## Intestine 0.062 0.062 0.88
## Jejunum 0.000 0.000 1.00
## Milk 0.000 0.000 1.00
## Ovary 0.000 0.000 1.00
## Peritoneal fluid 0.000 0.000 1.00
## Posterior wall of oropharynx 0.400 0.400 0.20
## Rectum 0.000 0.000 1.00
## Skin of abdomen 0.000 0.000 1.00
## Sputum 0.300 0.300 0.40
## Surface of tongue 0.290 0.290 0.43
## Urine 0.056 0.056 0.89
## Ventral side of post-anal tail 0.000 0.000 1.00
tabDiv(exps, "Richness", "Body site")## increased decreased unchanged
## Feces 134 207 420
## Mouth 10 3 9
## Posterior fornix of vagina 8 1 2
## Uterine cervix 8 1 11
## Oropharynx 0 6 3
## Skin of body 3 9 6
## Saliva 18 23 36
## Uterine cervix,Vaginal fluid 7 2 1
## Nasopharynx 5 9 19
## Stomach 4 8 3
## Throat 1 5 5
## Cecum mucosa 1 4 1
## Small intestine 1 4 0
## Subgingival dental plaque 5 2 15
## Colon 6 4 10
## Ear 2 0 3
## Esophagus 0 2 4
## Rectum 0 2 7
## Surface of tongue 4 2 1
## Vagina 4 2 11
## Caecum 2 3 1
## Ileum 2 1 7
## Meconium 2 3 7
## Milk 0 1 5
## Nasal cavity 1 2 10
## Urine 3 2 12
## Vagina,Uterine cervix 1 0 11
## Breast 1 1 7
## Bronchus 0 0 6
## Conjunctiva 1 1 5
## Intestine 0 0 13
## Ovary 0 0 7
## Peritoneal fluid 0 0 6
## Thyroid gland 0 0 12
## Tongue 2 2 7
tabDiv(exps, "Richness", "Body site", perc = TRUE)## increased decreased unchanged
## Feces 0.180 0.270 0.55
## Mouth 0.450 0.140 0.41
## Posterior fornix of vagina 0.730 0.091 0.18
## Uterine cervix 0.400 0.050 0.55
## Oropharynx 0.000 0.670 0.33
## Skin of body 0.170 0.500 0.33
## Saliva 0.230 0.300 0.47
## Uterine cervix,Vaginal fluid 0.700 0.200 0.10
## Nasopharynx 0.150 0.270 0.58
## Stomach 0.270 0.530 0.20
## Throat 0.091 0.450 0.45
## Cecum mucosa 0.170 0.670 0.17
## Small intestine 0.200 0.800 0.00
## Subgingival dental plaque 0.230 0.091 0.68
## Colon 0.300 0.200 0.50
## Ear 0.400 0.000 0.60
## Esophagus 0.000 0.330 0.67
## Rectum 0.000 0.220 0.78
## Surface of tongue 0.570 0.290 0.14
## Vagina 0.240 0.120 0.65
## Caecum 0.330 0.500 0.17
## Ileum 0.200 0.100 0.70
## Meconium 0.170 0.250 0.58
## Milk 0.000 0.170 0.83
## Nasal cavity 0.077 0.150 0.77
## Urine 0.180 0.120 0.71
## Vagina,Uterine cervix 0.083 0.000 0.92
## Breast 0.110 0.110 0.78
## Bronchus 0.000 0.000 1.00
## Conjunctiva 0.140 0.140 0.71
## Intestine 0.000 0.000 1.00
## Ovary 0.000 0.000 1.00
## Peritoneal fluid 0.000 0.000 1.00
## Thyroid gland 0.000 0.000 1.00
## Tongue 0.180 0.180 0.64Signature stats
sigs <- bugsigdbr::getSignatures(dat, tax.id.type = "metaphlan")Unique microbes
Number unique microbes contained in the signatures:
## [1] 7199Development of unique microbes captured over time:
Microbe set size distribution
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 1.000 2.000 5.000 8.618 10.000 470.000
gghistogram(lengths(sigs), bins = 30, ylab = "number of signatures",
xlab = "signature size", fill = "#00AFBB", ggtheme = theme_bw())
## [1] 3524Microbe co-occurrence
dat.feces <- subset(dat, `Body site` == "Feces")
cooc.mat <- microbeHeatmap(dat.feces, tax.level = "genus", anno = "genus")## Loading required namespace: safe
antag.mat <- microbeHeatmap(dat.feces, tax.level = "genus", anno = "genus", antagonistic = TRUE)
Get the top 20 genera most frequently reported as differentially abundant:
sigs.feces <- getSignatures(dat.feces, tax.id.type = "taxname",
tax.level = "genus", exact.tax.level = FALSE)
top20 <- sort(table(unlist(sigs.feces)), decreasing = TRUE)[1:20]
top20##
## Bacteroides Bifidobacterium Faecalibacterium Blautia
## 727 454 445 402
## Ruminococcus Clostridium Streptococcus Prevotella
## 391 380 374 365
## Roseburia Parabacteroides Lactobacillus Alistipes
## 362 352 321 315
## Coprococcus Dorea Eubacterium Veillonella
## 266 252 238 235
## Akkermansia Enterococcus Anaerostipes Lachnospira
## 230 226 219 208Subset heatmaps to the top 20 genera most frequently reported as differentially abundant:
## [1] TRUE## [1] TRUEDistinguish by direction of abundance change (increased / decreased):
# increased
sub.dat.feces <- subset(dat.feces, `Abundance in Group 1` == "increased")
sigs.feces.up <- getSignatures(sub.dat.feces, tax.id.type = "taxname",
tax.level = "genus", exact.tax.level = FALSE)
top20.up <- table(unlist(sigs.feces.up))[names(top20)]
top20.up##
## Bacteroides Bifidobacterium Faecalibacterium Blautia
## 322 219 157 182
## Ruminococcus Clostridium Streptococcus Prevotella
## 152 185 235 170
## Roseburia Parabacteroides Lactobacillus Alistipes
## 111 176 210 126
## Coprococcus Dorea Eubacterium Veillonella
## 94 107 103 145
## Akkermansia Enterococcus Anaerostipes Lachnospira
## 137 167 90 57
# decreased
sub.dat.feces <- subset(dat.feces, `Abundance in Group 1` == "decreased")
sigs.feces.down <- getSignatures(sub.dat.feces, tax.id.type = "taxname",
tax.level = "genus", exact.tax.level = FALSE)
top20.down <- table(unlist(sigs.feces.down))[names(top20)]
top20.down##
## Bacteroides Bifidobacterium Faecalibacterium Blautia
## 398 227 282 214
## Ruminococcus Clostridium Streptococcus Prevotella
## 234 190 131 192
## Roseburia Parabacteroides Lactobacillus Alistipes
## 245 170 109 183
## Coprococcus Dorea Eubacterium Veillonella
## 166 139 129 87
## Akkermansia Enterococcus Anaerostipes Lachnospira
## 89 57 123 145Plot the heatmap
# annotation
mat <- matrix(nc = 2, cbind(top20.up, top20.down))
bp <- ComplexHeatmap::anno_barplot(mat, gp = gpar(fill = c("#D55E00", "#0072B2"),
col = c("#D55E00", "#0072B2")),
height = unit(2, "cm"))
banno <- ComplexHeatmap::HeatmapAnnotation(`Abundance in Group 1` = bp)
lgd_list <- list(
Legend(labels = c("increased", "decreased"),
title = "Abundance in Group 1",
type = "grid",
legend_gp = gpar(col = c("#D55E00", "#0072B2"), fill = c("#D55E00", "#0072B2"))))
# same direction
# lcm <- sweep(cooc.mat, 2, matrixStats::colMaxs(cooc.mat), FUN = "/")
# we need to dampen the maximum here a bit down,
# otherwise 100% self co-occurrence takes up a large fraction of the colorscale,
sec <- apply(cooc.mat, 2, function(x) sort(x, decreasing = TRUE)[2])
cooc.mat2 <- cooc.mat
for(i in 1:ncol(cooc.mat2)) cooc.mat2[i,i] <- min(cooc.mat2[i,i], 1.4 * sec[i])
lcm <- sweep(cooc.mat2, 2, matrixStats::colMaxs(cooc.mat2), FUN = "/")
col <- circlize::colorRamp2(c(0,1), c("#EEEEEE", "red"))
ht1 <- ComplexHeatmap::Heatmap(lcm,
col = col,
name = "Relative frequency (top)",
cluster_columns = FALSE,
row_km = 3,
row_title = "same direction",
column_names_rot = 45,
row_names_gp = gpar(fontsize = 8),
column_names_gp = gpar(fontsize = 8))
# opposite direction
acm <- sweep(antag.mat, 2, matrixStats::colMaxs(antag.mat), FUN = "/")
col <- circlize::colorRamp2(c(0,1), c("#EEEEEE", "blue"))
ht2 <- ComplexHeatmap::Heatmap(acm,
col = col,
name = "Relative frequency (bottom)",
cluster_columns = FALSE,
row_title = "opposite direction",
row_km = 3,
column_names_rot = 45,
row_names_gp = gpar(fontsize = 8),
column_names_gp = gpar(fontsize = 8))
# phylum
sfp <- bugsigdbr::getSignatures(dat.feces, tax.id.type = "metaphlan",
tax.level = "genus", exact.tax.level = FALSE)
sfp20 <- sort(table(unlist(sfp)), decreasing = TRUE)[1:20]
uanno <- bugsigdbr::extractTaxLevel(names(sfp20),
tax.id.type = "taxname",
tax.level = "phylum",
exact.tax.level = FALSE)
phyla.grid <- seq_along(unique(uanno))
panno <- ComplexHeatmap::HeatmapAnnotation(phylum = uanno)
uanno <- matrix(uanno, nrow = 1)
colnames(uanno) <- names(top20)
pcols <- c("#CC79A7", "#F0E442", "#009E73", "#56B4E9", "#E69F00")
uanno <- ComplexHeatmap::Heatmap(uanno, name = "Phylum",
col = pcols[phyla.grid],
cluster_columns = FALSE,
column_names_rot = 45,
column_names_gp = gpar(fontsize = 8))
# put everything together
ht_list <- ht1 %v% banno %v% ht2 %v% uanno
ComplexHeatmap::draw(ht_list, annotation_legend_list = lgd_list, merge_legend = TRUE)
decorate_annotation("Abundance in Group 1", {
grid.text("# signatures", x = unit(-1, "cm"), rot = 90, just = "bottom", gp = gpar(fontsize = 8))
grid.text("*", x = unit(2.45, "cm"), y = unit(1.2, "cm"))
grid.text("*", x = unit(5.18, "cm"), y = unit(1, "cm"))
grid.text("*", x = unit(6.55, "cm"), y = unit(0.95, "cm"))
grid.text("*", x = unit(8.6, "cm"), y = unit(0.85, "cm"))
grid.text("*", x = unit(10, "cm"), y = unit(0.7, "cm"))
grid.text("*", x = unit(10.7, "cm"), y = unit(0.7, "cm"))
})
Signature similarity
Jaccard index
Inspect signature similarity for signatures from stomach samples based on Jaccard index:
stomachsub <- subset(dat, `Body site` == "Stomach")
sigsub <- bugsigdbr::getSignatures(stomachsub)
pair.jsim <- calcJaccardSimilarity(sigsub)Create a dendrogram of Jaccard dissimilarities (1.0 has no overlap, 0.0 are identical signatures).
