problems with facet_plot

[pedres]

I have the most recent version of ggtree (1.6.11), but I still have problems to reproduce the output of example from facet_plot for stacked barplots. This is what I get, which is strange, if I type the code from http://guangchuangyu.github.io/2016/10/facet_plot-a-general-solution-to-associate-data-with-phylogenetic-tree/

I am trying to join a tree (a hc object formatted as ggtree object) with an stacked barplot of abundances. My tree has 30 tips, and my dataset to stack as 180 rows, each tip has 6 values,like

 id          filos abundancias

1 AB10C Actinobacteria 2.228632578
2 AB10C Bacteroidetes 3.730753128
3 AB10C Firmicutes 3.904868286
4 AB10C Proteobacteria 3.734883721
5 AB10C Verrucomicrobia 4.807334326
6 AB10C lowabundance 3.043275942

When I type the code below I obtain the example2, in which appears the tree but not the barplot
arbolbarplot<-facet_plot(arbolbien, panel = 'Stacked Barplot', data = meltedfilosXXX, geom = geom_bar, mapping = aes(x = abundancias, fill = as.factor(filos)), stat='identity' )

The barplot I would like to join to the tree is
ggplot(meltedfilosXXX, aes(x=id, y=abundancias, fill=filos)) + geom_bar(stat="identity") + coord_flip() + ylab("Relative abundance")

Thank you very much for your help

Below I paste R session info

R version 3.3.3 (2017-03-06)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 7 x64 (build 7601) Service Pack 1

locale:
[1] LC_COLLATE=Spanish_Spain.1252 LC_CTYPE=Spanish_Spain.1252 LC_MONETARY=Spanish_Spain.1252 LC_NUMERIC=C LC_TIME=Spanish_Spain.1252

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

other attached packages:
[1] car_2.1-4 phangorn_2.1.1 data.table_1.10.4 multcomp_1.4-6 TH.data_1.0-8 MASS_7.3-45 survival_2.40-1 mvtnorm_1.0-6 nortest_1.0-4 picante_1.6-2 ape_4.1
[12] nlme_3.1-131 vegan_2.4-2 lattice_0.20-34 permute_0.9-4 plyr_1.8.4 phyloseq_1.14.0 tidyr_0.6.1 gridExtra_2.2.1 betapart_1.4-1 reshape2_1.4.2 cowplot_0.7.0
[23] ggtree_1.6.11 ggplot2_2.2.1 phylobase_0.8.2

loaded via a namespace (and not attached):
[1] minqa_1.2.4 colorspace_1.3-2 htmlTable_1.9 futile.logger_1.4.3 XVector_0.10.0 RcppArmadillo_0.7.700.0.0 GenomicRanges_1.22.4
[8] base64enc_0.1-3 MatrixModels_0.4-1 AnnotationDbi_1.32.3 xml2_1.1.1 codetools_0.2-15 splines_3.3.3 bold_0.4.0
[15] geneplotter_1.48.0 knitr_1.15.1 ade4_1.7-5 Formula_1.2-1 jsonlite_1.3 nloptr_1.0.4 pbkrtest_0.4-7
[22] annotate_1.48.0 cluster_2.0.5 httr_1.2.1 backports_1.0.5 assertthat_0.1 Matrix_1.2-8 lazyeval_0.2.0
[29] acepack_1.4.1 htmltools_0.3.5 quantreg_5.29 prettyunits_1.0.2 tools_3.3.3 igraph_1.0.1 gtable_0.2.0
[36] taxize_0.8.4 dplyr_0.5.0 fastmatch_1.1-0 Rcpp_0.12.9 Biobase_2.30.0 Biostrings_2.38.4 RJSONIO_1.3-0
[43] multtest_2.26.0 biom_0.3.12 iterators_1.0.8 stringr_1.2.0 lme4_1.1-12 XML_3.98-1.5 zlibbioc_1.16.0
[50] zoo_1.7-14 scales_0.4.1 rcdd_1.1-11 parallel_3.3.3 SummarizedExperiment_1.0.2 sandwich_2.3-4 SparseM_1.76
[57] lambda.r_1.1.9 RColorBrewer_1.1-2 memoise_1.0.0 rpart_4.1-10 reshape_0.8.6 latticeExtra_0.6-28 stringi_1.1.2
[64] RSQLite_1.1-2 genefilter_1.52.1 S4Vectors_0.8.11 foreach_1.4.3 checkmate_1.8.2 BiocGenerics_0.16.1 BiocParallel_1.4.3
[71] geometry_0.3-6 GenomeInfoDb_1.6.3 rncl_0.8.2 labeling_0.3 htmlwidgets_0.8 magrittr_1.5 DESeq2_1.10.1
[78] R6_2.2.0 IRanges_2.4.8 Hmisc_4.0-2 DBI_0.6 foreign_0.8-67 mgcv_1.8-17 nnet_7.3-12
[85] tibble_1.2 futile.options_1.0.0 uuid_0.1-2 progress_1.1.2 RNeXML_2.0.7 locfit_1.5-9.1 digest_0.6.12
[92] xtable_1.8-2 stats4_3.3.3 munsell_0.4.3 magic_1.5-6 quadprog_1.5-5

[GuangchuangYu]

1. if you really follow https://guangchuangyu.github.io/2016/10/facet_plot-a-general-solution-to-associate-data-with-phylogenetic-tree/ you will find that you need to use geom_barh instead of geom_bar.

2. don't ignore my message to create a reproducible example, otherwise I don't know how to help.

[pedres]

Re: [GuangchuangYu/ggtree] problems with facet_plot (#120) If a paste the code tr <- rtree(30) p <- ggtree(tr) d1 <- data.frame(id=tr$tip.label, location=sample(c("GZ", "HK", "CZ"), 30, replace=TRUE)) p1 <- p %<+% d1 + geom_tippoint(aes(color=location)) d2 <- data.frame(id=tr$tip.label, val=rnorm(30, sd=3)) p2 <- facet_plot(p1, panel="dot", data=d2, geom=geom_point,                aes(x=val), color='firebrick') + theme_tree2()                                 d3 <- data.frame(id = rep(tr$tip.label, each=2),                    value = abs(rnorm(60, mean=100, sd=50)),                    category = rep(LETTERS[1:2], 30)) p3 <- facet_plot(p2, panel = 'Stacked Barplot', data = d3,                geom = geom_barh,                mapping = aes(x = value, fill = as.factor(category)),                stat='identity' ) I get "Error in facet_plot(p2, panel = "Stacked Barplot", data = d3, geom = geom_barh,  :  object 'geom_barh' not found", and I do not know why. That was the reason to switch to geom_bar instead. Apologies. I am using ggtree 1.6.11 Manuel Aira Grupo de Ecologia Animal Departamento de Ecoloxia e Bioloxia Animal Universidade de Vigo mailto:aira@uvigo.es ===8<==============Texto del mensaje original=============== Closed #120. — You are receiving this because you authored the thread. Reply to this email directly, view it on GitHub, or mute the thread. ===8<===========Fin del texto del mensaje original===========

[AEgit]

Version: ggtree 1.6.11

I can confirm the issues reported by @pedres. When using the example code provided on https://guangchuangyu.github.io/2016/10/facet_plot-a-general-solution-to-associate-data-with-phylogenetic-tree/ you get an error message:

library(ggtree)

tr <- rtree(30)
p <- ggtree(tr)
d1 <- data.frame(id=tr$tip.label, location=sample(c("GZ", "HK", "CZ"), 30, replace=TRUE))
p1 <- p %<+% d1 + geom_tippoint(aes(color=location))
d2 <- data.frame(id=tr$tip.label, val=rnorm(30, sd=3))
p2 <- facet_plot(p1, panel="dot", data=d2, geom=geom_point, 
                 aes(x=val), color='firebrick') + theme_tree2()

d3 <- data.frame(id = rep(tr$tip.label, each=2),
                 value = abs(rnorm(60, mean=100, sd=50)),
                 category = rep(LETTERS[1:2], 30))
p3 <- facet_plot(p2, panel = 'Stacked Barplot', data = d3, 
                 geom = geom_barh, 
                 mapping = aes(x = value, fill = as.factor(category)), 
                 stat='identity' ) 

The following error message is displayed:

Error in facet_plot(p2, panel = "Stacked Barplot", data = d3, geom = geom_barh,  : 
  object 'geom_barh' not found

If we use geom_bar instead, no error message is displayed, but the plot looks as reported by @pedres.

[GuangchuangYu]

an excerpt from the post http://guangchuangyu.github.io/2016/10/facet_plot-a-general-solution-to-associate-data-with-phylogenetic-tree/

Most of the geom in ggplot2 draw vertical graph object, while for associating graph object with phylogenetic tree, we need horizontal versions. Luckily, we have ggstance which provides horizontal versions of geoms, including:

• geom_barh()
• geom_histogramh()
• geom_linerangeh()
• geom_pointrangeh()
• geom_errorbarh()
• geom_crossbarh()
• geom_boxploth()
• geom_violinh()

With ggstance, we can associate barplot, boxplot or other graphs to phylogenetic trees.

Did both of you really read the post? AND you also ignore my guidance of reporting an issue.

[AEgit]

Ok, my fault - indeed, if the library "ggstance" is loaded, the posted coded runs smoothly. So here again the code that should run (directly taken from http://guangchuangyu.github.io/2016/10/facet_plot-a-general-solution-to-associate-data-with-phylogenetic-tree/):

library(ggtree)
library(ggstance) #Without this library the code won't work

tr <- rtree(30)
p <- ggtree(tr)
d1 <- data.frame(id=tr$tip.label, location=sample(c("GZ", "HK", "CZ"), 30, replace=TRUE))
p1 <- p %<+% d1 + geom_tippoint(aes(color=location))
d2 <- data.frame(id=tr$tip.label, val=rnorm(30, sd=3))
p2 <- facet_plot(p1, panel="dot", data=d2, geom=geom_point, 
                 aes(x=val), color='firebrick') + theme_tree2()

d3 <- data.frame(id = rep(tr$tip.label, each=2),
                 value = abs(rnorm(60, mean=100, sd=50)),
                 category = rep(LETTERS[1:2], 30))
p3 <- facet_plot(p2, panel = 'Stacked Barplot', data = d3, 
                 geom = geom_barh, 
                 mapping = aes(x = value, fill = as.factor(category)), 
                 stat='identity' ) 
p3

Apologies for any inconvenience.

[pedres]

Re: [GuangchuangYu/ggtree] problems with facet_plot (#120) Thanks four your help. Not your fault, it was completely mine. Manuel Aira Grupo de Ecologia Animal Departamento de Ecoloxia e Bioloxia Animal Universidade de Vigo mailto:aira@uvigo.es ===8<==============Texto del mensaje original=============== Ok, my fault - indeed, if the library ggstance is loaded, the posted coded runs smoothly. So here again the code that should run (directly taken from http://guangchuangyu.github.io/2016/10/facet_plot-a-general-solution-to-associate-data-with-phylogenetic-tree/): library(ggtree) library(ggstance) #Without this library the code won't work tr <- rtree(30) p <- ggtree(tr) d1 <- data.frame(id=tr$tip.label, location=sample(c("GZ", "HK", "CZ"), 30, replace=TRUE)) p1 <- p %<+% d1 + geom_tippoint(aes(color=location)) d2 <- data.frame(id=tr$tip.label, val=rnorm(30, sd=3)) p2 <- facet_plot(p1, panel="dot", data=d2, geom=geom_point,                 aes(x=val), color='firebrick') + theme_tree2() d3 <- data.frame(id = rep(tr$tip.label, each=2),                 value = abs(rnorm(60, mean=100, sd=50)),                 category = rep(LETTERS[1:2], 30)) p3 <- facet_plot(p2, panel = 'Stacked Barplot', data = d3,                 geom = geom_barh,                 mapping = aes(x = value, fill = as.factor(category)),                 stat='identity' ) p3 Apologies for any inconvenience. — You are receiving this because you were mentioned. Reply to this email directly, view it on GitHub, or mute the thread. ===8<===========Fin del texto del mensaje original===========

[pedres]

rm(list=ls(all=TRUE));library(ggstance);library(phylobase);library(ggtree);library(cowplot);library(reshape2);library(betapart);library(grid);library(gridExtra);library(tidyr);library(phyloseq);library(ggplot2);library(plyr);library(vegan);library(nlme);library(picante);library(nortest);library(multcomp);library(data.table); library(phangorn);library(car);library(codyn) theme_set(theme_bw()) ### the example form website works tr <- rtree(60) p <- ggtree(tr) d1 <- data.frame(id=tr$tip.label, location=sample(c("GZ", "HK", "CZ"), 60, replace=TRUE)) p1 <- p %<+% d1 + geom_tippoint(aes(color=location)) d2 <- data.frame(id=tr$tip.label, val=rnorm(60, sd=3)) p2 <- facet_plot(p1, panel="dot", data=d2, geom=geom_point,aes(x=val), color='firebrick') + theme_tree2() d3 <- data.frame(id = rep(tr$tip.label, each=2),value = abs(rnorm(60, mean=100, sd=50)),category = rep(LETTERS[1:2], 60)) p3 <- facet_plot(p2, panel = 'Stacked Barplot', data = d3,geom = geom_barh,mapping = aes(x = value, fill = as.factor(category)),stat='identity' ) p3 summary(d3) id value category t1 : 2 Min. : 2.319 A:60 t10 : 2 1st Qu.: 60.910 B:60 t11 : 2 Median : 87.020 t12 : 2 Mean : 95.611 t13 : 2 3rd Qu.:132.496 t14 : 2 Max. :208.377 (Other):108 datosRAREF<-import_biom(file.choose());datosRAREF relabund = transform_sample_counts(datosRAREF, function(x) x / sum(x) ) repet<-c(1,1,2,3,4,5,1,2,3,4,1,5,1,2,3,4,5,2,1,2,3,4,5,3,4,5,2,3,4,5) tiempo<-c("07days","14days","14days","14days","14days","14days","28days","28days","28days","28days","0days","28days","42days","42days","42days","42days","42days","0days","91days","91days","91days","91days","91days","0days","0days","0days","07days","07days","07days","07days") factores<-as.data.frame(cbind(repet,tiempo)); rm(repet);rm(tiempo) summarize_taxa <- function(counts, taxonomy) { if(is.matrix(taxonomy)) { #message('multiple taxonomies') alply(taxonomy, 2, summarize_taxa, counts = counts, .dims = TRUE) } else if(is.matrix(counts)) { #message('multiple counts') require('plyr') apply(counts, 2, summarize_taxa, taxonomy = taxonomy) } else { #message('summarize') tapply(counts, taxonomy, sum) } } ot <- as(otu_table(relabund), 'matrix') tax <- as.data.frame(tax_table(relabund)) tax$phylum<-tax$Rank2 tax <- subset(tax, select = phylum) tax<-as.matrix(tax) abundancias<-summarize_taxa(ot, tax) filos<-data.frame(t(abundancias$phylum*100)) filos1<-filos[,colMeans(filos) < 1]; lowabundance<-rowSums(filos1);rm(filos1) ## los que tienen abundancias menor de 1 filos2<-filos[,colMeans(filos) > 1] ## los que tienen abundancias mayor de 1 filos<-data.frame(cbind(factores,filos2,lowabundance));rm(filos2) meltedfilos <- melt(filos, id.vars=c("repet", "tiempo")) meansfilos <- ddply(meltedfilos, c("tiempo", "variable"), summarise, mean=mean(value)) filosXX<-cbind(muestras=rownames(filos),filos) meltedfilosXX <- gather(filosXX, filos, abundancias, Actinobacteria:lowabundance, factor_key=TRUE) meltedfilosXXX<-cbind(id=meltedfilosXX$muestras,meltedfilosXX);meltedfilosXXX <- subset(meltedfilosXXX, select = c(id,filos,abundancias)) tr2<-rtree(30,tip.label = rownames(filos) tr2gg <- ggtree(tr2) tr2ggbarplot <- facet_plot(tr2gg, panel = 'Stacked Barplot', data = meltedfilosXXX,geom = geom_barh,mapping = aes(x = abundancias, fill = as.factor(filos)),stat='identity' ) summary(meltedfilosXXX) id filos abundancias AB10C : 6 Actinobacteria :30 Min. : 0.0000 AB11 : 6 Bacteroidetes :30 1st Qu.: 0.6001 AB12 : 6 Firmicutes :30 Median : 3.2598 AB13 : 6 Proteobacteria :30 Mean :16.6667 AB14 : 6 Verrucomicrobia:30 3rd Qu.:38.0269 AB15 : 6 lowabundance :30 Max. :66.0884 (Other):144