issues with fill color in geom_fruit

[Matteo Ungaro]

As per this git issue, I'm struggling with adding fill colors to the box-plot generated by 

geom_fruit.

​. 

I post below the code I'm using, but essentially I need to color box-plots based on the location field of my data-frame (see figure at the end); however, upon doing so I'm getting prompted with the following:

Error in geom_boxplot():
! Problem while computing aesthetics.
ℹ Error occurred in the 7th layer.
Caused by error in check_aesthetics():
! Aesthetics must be either length 1 or the same as the data
(300).
✖ Fix the following mappings: fill.
Run rlang::last_trace() to see where the error occurred.

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Now, since then I've tried to add an extra colum for the group argument but it appears to not having any effect on the final result...

Anyway, this is the code — I'm trying to closely follow this guide:

CODE

library(ape) library(dplyr) library(tibble) library(treeio) library(janitor) library(ggtree) library(ggplot2) library(tidytree) library(phytools) library(phangorn) library(phylobase) library(ggtreeExtra) library(RColorBrewer) ###LOAD DATA AND WRANGLING ibs_matrix = read.delim("/path/to/phylo_tree_header.phy", sep="\t", header=TRUE) colnames(ibs_matrix)[1] <- "" ibs_matrix[1] <- NULL box_plot = read.delim("/path/to/box_plot.txt", sep="\t", header=FALSE) box_plot[1,1] <- "id" #ibs_matrix ibs_matrix_t <- t(ibs_matrix) box_plot_t <- t(box_plot); box_plot_t <- janitor::row_to_names(box_plot_t, 1) #ibs_matrix_t ###ADD META INFO AND DF FORMATTING variety <- c("wt", "lr", "wt", "wt", "lr", "wt", "wt", "wt", "lr", "lr", "lr", "lr") location <- c("ESP", "ESP", "ITA", "ITA", "JOR", "TUR", "PAL", "GRC", "GRC", "ESP", "ESP", "ITA") meta_df <- data.frame(ibs_matrix_t[, 1], variety, location); meta_df <- meta_df[ -c(1) ] meta_df$id <- rownames(meta_df); meta_df <- meta_df[,c(3,1,2)] rownames(meta_df) <- NULL ###COMPUTE AND CALCULATE PIRWISE DISTANCES, PLUS CONVERSION TO PHYLO pdist <- dist(ibs_matrix_t, method="euclidean", diag=TRUE, upper=TRUE, p=2) distances <- distanceHadamard(as.matrix(pdist)) #lento(distances) phylo <- as.phylo(distances) ###GGTREE PERSONALIZATION meta_df$variety <- factor(meta_df$variety, levels=c('wt', 'lr')) t1 <- ggtree(phylo, branch.length='none', layout='circular') %<+% meta_df + geom_tippoint(aes(color=variety)) + #, shape=21, size=3) + #scale_color_manual(values=c("black", "black")) + #scale_fill_manual(values=brewer.pal(9, "Greens")[c(7, 3)]) + scale_color_manual(values=brewer.pal(9, "Greens")[c(7, 3)]) + geom_tiplab(size=3, hjust=-.1) t1 box_plot <- janitor::row_to_names(box_plot, 1); box_plot=subset(box_plot, select=-c(id)) box_plot_t <- data.frame(values=matrix(t(box_plot)), id=colnames(box_plot)); box_plot_t <- box_plot_t[order(box_plot_t[["id"]]),] box_plot_t <- full_join(box_plot_t, meta_df, by="id") t1_box <- t1 + geom_fruit( data=box_plot_t, geom=geom_boxplot, mapping = aes( y=id, x=as.numeric(as.character(values)) ), offset=.4, size=.2, outlier.size=.5, outlier.stroke=.08, outlier.shape=21, axis.params = list( axis="x", text.size=1.8, hjust=1, vjust=0.5, nbreak=3 ), grid.params=list() ) t1_box <- rotate_tree(t1_box, -90) t1_box

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as well as the dput for the data, thanks in advance:

IBS_MATRIX

structure(list(INLUP00165 = c(1.53578, -0.105267, -0.0945413, -0.083604, -0.209443, -0.139285, -0.208677, -0.199941, -0.209932, -0.130887, -0.082297, -0.0719018), INLUP00169 = c(-0.105267, 1.60124, -0.142996, -0.023115, -0.243876, -0.0435319, -0.243711, -0.256835, -0.255688, -0.132416, -0.102566, -0.0512363), INLUP00208 = c(-0.0945413, -0.142996, 1.70865, -0.00168153, -0.229154, -0.0920099, -0.201994, -0.278662, -0.210596, -0.190707, -0.164444, -0.101866), INLUP00214 = c(-0.083604, -0.023115, -0.00168153, 1.36444, -0.176534, -0.0313074, -0.178905, -0.256911, -0.220043, -0.199516, -0.16628, -0.0265423), INLUP00228 = c(-0.209443, -0.243876, -0.229154, -0.176534, 1.66881, -0.223521, 0.672806, -0.346079, -0.25505, -0.243328, -0.219959, -0.194674), INLUP00233 = c(-0.139285, -0.0435319, -0.0920099, -0.0313074, -0.223521, 1.6054, -0.209163, -0.304027, -0.216554, -0.225491, -0.186448, 0.0659375), INLUP00245 = c(-0.208677, -0.243711, -0.201994, -0.178905, 0.672806, -0.209163, 1.63191, -0.329851, -0.252808, -0.252563, -0.233733, -0.193315), INLUP00325 = c(-0.199941, -0.256835, -0.278662, -0.256911, -0.346079, -0.304027, -0.329851, 2.72659, -0.253858, -0.0673777, -0.158547, -0.274507), INLUP00332 = c(-0.209932, -0.255688, -0.210596, -0.220043, -0.25505, -0.216554, -0.252808, -0.253858, 2.45426, -0.233602, -0.159556, -0.186578), INLUP00393 = c(-0.130887, -0.132416, -0.190707, -0.199516, -0.243328, -0.225491, -0.252563, -0.0673777, -0.233602, 1.91195, -0.0165982, -0.219464), INLUP00418 = c(-0.082297, -0.102566, -0.164444, -0.16628, -0.219959, -0.186448, -0.233733, -0.158547, -0.159556, -0.0165982, 1.64659, -0.156163), INLUP00496 = c(-0.0719018, -0.0512363, -0.101866, -0.0265423, -0.194674, 0.0659375, -0.193315, -0.274507, -0.186578, -0.219464, -0.156163, 1.41031)), row.names = c(NA, -12L), class = "data.frame")

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BOX_PLOT

structure(list(INLUP00165 = c("71247", "46097", "64492", "56344", "45840", "55882", "53758", "54010", "46585", "48590", "56855", "60986", "52021", "51466", "63630", "40707", "39995", "45744", "50270", "51680", "46447", "44447", "58687", "51386", "48827" ), INLUP00169 = c("52201", "41279", "54405", "42242", "44539", "53794", "42223", "34697", "34368", "29109", "39310", "51673", "40718", "34476", "41809", "36536", "39560", "43025", "46098", "53332", "37042", "49219", "57686", "41765", "42885"), INLUP00208 = c("16628", "12529", "22011", "15841", "14072", "19491", "13796", "17956", "12269", "19643", "17267", "14894", "17428", "21028", "14427", "12621", "12243", "13858", "14986", "17584", "16875", "12470", "22386", "20701", "14384"), INLUP00214 = c("6491", "5005", "9796", "5728", "4567", "6823", "6793", "6042", "4116", "8757", "6534", "7075", "6861", "11437", "8627", "5811", "5040", "5795", "7812", "8108", "4953", "8151", "11226", "6558", "1493"), INLUP00228 = c("66954", "49763", "61616", "53745", "47684", "52729", "51194", "53530", "46432", "52910", "50143", "50145", "47138", "51653", "62836", "39766", "45045", "48115", "15", "53038", "54870", "49241", "41094", "66164", "43308"), INLUP00233 = c("10543", "7371", "12433", "4465", "8059", "9989", "12389", "10893", "4609", "11799", "10143", "9525", "7503", "13011", "9711", "7854", "7143", "9792", "7914", "11623", "11173", "9082", "13972", "15058", "8268"), INLUP00245 = c("52870", "38910", "51872", "43726", "37511", "45524", "41920", "42543", "37332", "44934", "42060", "41015", "39371", "38787", "54069", "31060", "37420", "42669", "41404", "49921", "40529", "33367", "53711", "38905", "40467"), INLUP00325 = c("47797", "30812", "48732", "32561", "29759", "46370", "34187", "36516", "32158", "36628", "35471", "43933", "36857", "35275", "50396", "25007", "30359", "38817", "18", "33558", "48311", "35956", "35634", "48511", "47230"), INLUP00332 = c("52227", "40933", "50193", "43050", "33053", "48781", "40596", "37521", "34667", "52567", "41589", "39315", "45442", "43160", "54746", "31881", "35051", "38912", "39364", "48679", "40634", "42024", "45438", "38130", "43506" ), INLUP00393 = c("82244", "61652", "73363", "58533", "58709", "68165", "61546", "65897", "51179", "63922", "59164", "54743", "57061", "81867", "49679", "53079", "60428", "314", "57889", "63260", "56838", "56178", "68247", "50214", "56837"), INLUP00418 = c("16513", "14388", "20001", "16319", "10966", "19256", "13421", "16286", "11389", "18051", "12827", "17798", "17970", "19369", "12898", "11340", "14178", "174", "18573", "14752", "17577", "20905", "21986", "13596", "2354"), INLUP00496 = c("98447", "92995", "94249", "88604", "58761", "91335", "79049", "81218", "74616", "90049", "78279", "95932", "74531", "69362", "100019", "69923", "75383", "57086", "32", "80715", "102201", "71007", "77709", "55065", "45288")), row.names = 2:26, class = "data.frame")

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