stat_compare_means Error must have same length

General
1

Hi, we are trying to compute a Kruskal Wallis test on both indexes (Chao1, Shannon) through the following code using the function stat_compare_means (that by default uses wilkoxon) from ggpubr.

Code:

my_comparisons <- list(c("gut C. decolorata female","larva"), c("larva","gut C. decolorata male"), c("gut C. decolorata female", "gut C. decolorata male"), c("gut C. decolorata male", "pollen provision"), c("gut C. decolorata female", "pollen provision"), c("larva", "pollen provision"))

p <- plot_richness(physeq, x = "sample_type", measures = c("Chao1", "Shannon"), scales="free_y")


p+ geom_boxplot(aes(fill = sample_type), alpha=0.8)+ guides(fill = guide_legend(title = "Sample type of Centris decolorata and pollen provision"))+
  scale_fill_manual(values = color_cdpp, labels=c("gut C. decolorata female", "gut C. decolorata male", "larva", "pollen provision"))+
  scale_x_discrete(labels=c("gut C. decolorata female", "gut C. decolorata male", "larva", "pollen provision"))+
  xlab("Sample type")+
  theme(axis.title.x =element_text(size=15), axis.title.y =element_text(size=15), axis.text.y = element_text(size=15),
        legend.text = element_text(size=15), 
        strip.text = element_text(size=15),
        legend.title=element_markdown(size=15), axis.text.x = element_text(size=15), 
        legend.justification = "center",
        legend.text.align = 0) -> p1


p1 + stat_compare_means(comparisons = my_comparisons, label="p.signif", method = 'kruskal.test',
                        hide.ns = FALSE,
                        symnum.args = list(cutpoints = c(0, 0.0001, 0.001, 0.01, 0.05, 1), 
                                           symbols = c("*", "*", "", "", "ns")))

We receive the following error:

Warning messages:

1: Computation failed in stat_signif():
'x' and 'g' must have the same length
2: Computation failed in stat_signif():
'x' and 'g' must have the same length

We would greatly appreciate any insight on to why we receive this error message and how we could fix it.

2

Could you supply some sample data ? Without knowing what "physeq" is it can be difficult to check things.

A handy way to supply some sample data is the dput() function. In the case of a large dataset something like dput(head(mydata, 100)) should supply the data we need. Just do dput(mydata) where mydata is your data. Copy the output and paste it here.

3

Hello @jrkrideau,

Thanks for answering this thread.

physeq stores all related phylogenetic sequencing data as single object (S4 classes).

So here physeq merged OTU (a table with 19 samples were 900 taxa of bacteria as DNA bases are enumerated, too long to show here) + SAM (table with the 19 samples with their 27 variables, shown down here) + TAX (a table with the correspondance between the DNA bases and their taxonomic ranks, shown down here).

Please let me know if you need further info.

physeq
phyloseq-class experiment-level object
otu_table()   OTU Table:         [ 900 taxa and 19 samples ]
sample_data() Sample Data:       [ 19 samples by 27 sample variables ]
tax_table()   Taxonomy Table:    [ 900 taxa by 8 taxonomic ranks ]

> dput(head(TAX, 25))
new("taxonomyTable", .Data = structure(c("d__Bacteria", "d__Bacteria", 
"d__Bacteria", "d__Bacteria", "d__Bacteria", "d__Bacteria", "d__Bacteria", 
"d__Bacteria", "d__Bacteria", "d__Bacteria", "d__Bacteria", "d__Bacteria", 
"d__Bacteria", "d__Bacteria", "d__Bacteria", "d__Archaea", "d__Bacteria", 
"d__Bacteria", "d__Bacteria", "d__Bacteria", "d__Bacteria", "d__Bacteria", 
"d__Bacteria", "d__Bacteria", "d__Bacteria", " p__Proteobacteria", 
" p__Firmicutes", " p__Proteobacteria", " p__Actinobacteriota", 
" p__Proteobacteria", " p__Proteobacteria", " p__Actinobacteriota", 
" p__Proteobacteria", " p__Actinobacteriota", " p__Proteobacteria", 
" p__Proteobacteria", " p__Firmicutes", " p__Proteobacteria", 
" p__Proteobacteria", " p__Verrucomicrobiota", " p__Crenarchaeota", 
" p__Cyanobacteria", " p__Actinobacteriota", "", " p__Actinobacteriota", 
" p__Actinobacteriota", " p__Planctomycetota", " p__Proteobacteria", 
" p__Actinobacteriota", " p__Actinobacteriota", " c__Alphaproteobacteria", 
" c__Bacilli", " c__Gammaproteobacteria", " c__Actinobacteria", 
" c__Gammaproteobacteria", " c__Gammaproteobacteria", " c__Actinobacteria", 
" c__Alphaproteobacteria", " c__Actinobacteria", " c__Alphaproteobacteria", 
" c__Gammaproteobacteria", " c__Bacilli", " c__Gammaproteobacteria", 
" c__Gammaproteobacteria", " c__Verrucomicrobiae", " c__Nitrososphaeria", 
" c__Cyanobacteriia", " c__Actinobacteria", "", " c__Actinobacteria", 
" c__Actinobacteria", " c__Planctomycetes", " c__Gammaproteobacteria", 
" c__Actinobacteria", " c__Actinobacteria", " o__Rhizobiales", 
" o__Bacillales", " o__Enterobacterales", " o__Micrococcales", 
" o__Enterobacterales", " o__Burkholderiales", " o__Micrococcales", 
" o__Rhizobiales", " o__Micrococcales", " o__Rhizobiales", " o__Xanthomonadales", 
" o__Lactobacillales", " o__Enterobacterales", " o__Oceanospirillales", 
" o__Verrucomicrobiales", " o__Nitrosopumilales", " o__Chloroplast", 
" o__Streptomycetales", "", " o__Streptomycetales", " o__Streptomycetales", 
" o__Gemmatales", " o__Burkholderiales", " o__Bifidobacteriales", 
" o__Propionibacteriales", " f__Rhizobiaceae", " f__Bacillaceae", 
" f__Enterobacteriaceae", " f__Micrococcaceae", " f__Yersiniaceae", 
" f__Alcaligenaceae", " f__Cellulomonadaceae", " f__Rhizobiaceae", 
" f__Promicromonosporaceae", " f__Rhizobiaceae", " f__Xanthomonadaceae", 
" f__Lactobacillaceae", " f__Enterobacteriaceae", " f__Halomonadaceae", 
" f__Rubritaleaceae", " f__Nitrosopumilaceae", " f__Chloroplast", 
" f__Streptomycetaceae", "", " f__Streptomycetaceae", " f__Streptomycetaceae", 
" f__Gemmataceae", " f__Burkholderiaceae", " f__Bifidobacteriaceae", 
" f__Nocardioidaceae", " g__Ochrobactrum", " g__Bacillus", "", 
" g__Kocuria", " g__Serratia", " g__Achromobacter", " g__Cellulomonas", 
" g__Allo-, Neo-, Para- Rhizobium", " g__Cellulosimicrobium", 
" g__Allo-, Neo-, Para- Rhizobium", " g__Pseudoxanthomonas", 
"", "", " g__Zymobacter", " g__Luteolibacter", " g__Nitrosopumilaceae", 
" g__Chloroplast", " g__Streptomyces", "", " g__Streptomyces", 
" g__Streptomyces", " g__Fimbriiglobus", " g__Burkholderia-Caballeronia-Paraburkholderia", 
" g__Bifidobacterium", " g__Nocardioides", "", "", "", "", "", 
"", "", "", "", "", "", "", "", " s__Zymobacter_palmae", "", 
"", "", "", "", "", "", "", "", "", "", "0.9980083", "0.9969887", 
"0.9594749", "0.9900304", "0.8022131", "0.7508866", "0.9165790", 
"0.9805537", "0.9939179", "0.9922785", "0.9997184", "0.9999752", 
"0.8967849", "0.7509968", "0.9999999", "0.8692432", "1.0000000", 
"0.9996909", "0.9999977", "0.9999614", "0.9999141", "0.9999992", 
"0.9941682", "0.9999998", "0.9999886"), .Dim = c(25L, 8L), .Dimnames = list(
    c("TACGAAGGGGGCTAGCGTTGTTCGGATTTACTGGGCGTAAAGCGCACGTAGGCGGGCTAATAAGTCAGGGGTGAAATCCCGGGGCTCAACCCCGGAACTGCCTTTGATACTGTTAGTCTTGAGTATGGTAGAGGTGAGTGGAATTCCGAGTGTAGAGGTGAAATTCGTAGATATTCGGAGGAACACCAGTGGCGAAGGCG", 
    "TACGTAGGTGGCAAGCGTTGTCCGGAATTATTGGGCGTAAAGGGCTCGCAGGCGGTTTCTTAAGTCTGATGTGAAAGCCCCCGGCTCAACCGGGGAGGGTCATTGGAAACTGGGAAACTTGAGTGCAGAAGAGGAGAGTGGAATTCCACGTGTAGCGGTGAAATGCGTAGAGATGTGGAGGAACACCAGTGGCGAAGGCG", 
    "TACGGAGGGTGCAAGCGTTAATCGGAATTACTGGGCGTAAAGCGCACGCAGGCGGTCTGTCAAGTCGGATGTGAAATCCCCGGGCTCAACCTGGGAACTGCATTCGAAACTGGCAGGCTGGAGTCTTGTAGAGGGGGGTAGAATTCCAGGTGTAGCGGTGAAATGCGTAGAGATCTGGAGGAATACCGGTGGCGAAGGCG", 
    "TACGTAGGGCGCAAGCGTTGTCCGGAATTATTGGGCGTAAAGAGCTCGTAGGCGGCTTGTCGCGTCTGCTGTGAAAGCCCGGGGCTTAACCCCGGGTGTGCAGTGGGTACGGGCAGGCTAGAGTGCAGTAGGGGAGACTGGAATTCCTGGTGTAGCGGTGAAATGCGCAGATATCAGGAGGAACACCGATGGCGAAGGCA", 
    "TACGGAGGGTGCAAGCGTTAATCGGAATTACTGGGCGTAAAGCGCACGCAGGCGGTTTGTTAAGTCAGATGTGAAATCCCCGGGCTCAACCTGGGAACTGCATTTGAAACTGGCAAGCTAGAGTCTCGTAGAGGGGGGTAGAATTCCAGGTGTAGCGGTGAAATGCGTAGAGATCTGGAGGAATACCGGTGGCGAAGGCG", 
    "TACGTAGGGTGCAAGCGTTAATCGGAATTACTGGGCGTAAAGCGTGCGCAGGCGGTTCGGAAAGAAAGATGTGAAATCCCAGAGCTTAACTTTGGAACTGCATTTTTAACTACCGGGCTAGAGTGTGTCAGAGGGAGGTGGAATTCCGCGTGTAGCAGTGAAATGCGTAGATATGCGGAGGAACACCGATGGCGAAGGCA", 
    "TACGTAGGGCGCAAGCGTTGTCCGGAATTATTGGGCGTAAAGAGCTCGTAGGCGGTCTGTCGCGTCTGCTGTGAAAACTCGAGGCTCAACCTCGGGCTTGCAGTGGGTACGGGCAGACTAGAGTGCGGTAGGGGAGACTGGAATTCCTGGTGTAGCGGTGGAATGCGCAGATATCAGGAGGAACACCGATGGCGAAGGCA", 
    "TACGAAGGGGGCTAGCGTTGTTCGGAATTACTGGGCGTAAAGCGCACGTAGGCGGATATTTAAGTCAGGGGTGAAATCCCAGAGCTCAACTCTGGAACTGCCTTTGATACTGGGTATCTTGAGTATGGAAGAGGTAAGTGGAATTCCGAGTGTAGAGGTGAAATTCGTAGATATTCGGAGGAACACCAGTGGCGAAGGCG", 
    "TACGTAGGGCGCAAGCGTTGTCCGGAATTATTGGGCGTAAAGAGCTCGTAGGCGGTTTGTCGCGTCTGGTGTGAAAACTCGAGGCTCAACCTCGAGCTTGCATCGGGTACGGGCAGACTAGAGTGCGGTAGGGGAGACTGGAATTCCTGGTGTAGCGGTGGAATGCGCAGATATCAGGAGGAACACCGATGGCGAAGGCA", 
    "TACGAAGGGGGCTAGCGTTGTTCGGAATTACTGGGCGTAAAGCGCACGTAGGCGGATATTTAAGTCAGGGGTGAAATCCCGCAGCTCAACTGCGGAACTGCCTTTGATACTGGGTATCTTGAGTATGGAAGAGGTAAGTGGAATTCCGAGTGTAGAGGTGAAATTCGTAGATATTCGGAGGAACACCAGTGGCGAAGGCG", 
    "TACGAAGGGTGCAAGCGTTACTCGGAATTACTGGGCGTAAAGCGTGCGTAGGTGGTGGTTTAAGTCTGCTGTGAAAGCCCTGGGCTCAACCTGGGAATTGCAGTGGATACTGGGTCACTAGAGTGTGGTAGAGGGATGCGGAATTTCCGGTGTAGCAGTGAAATGCGTAGAGATCGGAAGGAACATCCGTGGCGAAGGCG", 
    "TACGTAGGTGGCAAGCGTTGTCCGGATTTATTGGGCGTAAAGTGAGCGCAGGCGGTTTTTTAAGTCTAATGTGAAAGCCTTCGGCTTAACCGAAGAAGTGCATTGGAAACTAAAAAACTTGAGTGCAGAAAAGGATAGTGGAACTCCATGTGTAGCGGTGAAATGCGTAGATATATGGAAGAACACCAGTGGCGAAGGCG", 
    "TACGAAGGGTGCAAGCGTTAATCGGAATTACTGGGCGTAAAGCGCACGCAGGCGGTCTGTCAAGTCGGATGTGAAATCCCTGGGCTCAACCTGGGAACTGCATTCGAAACTGGCAGGCTTGAGTCTCGTAGAGGGGGGTAGAATTCCAGGTGTAGCGGTGAAATGCGTAGAGATCTGGAGGAATACCGGTGGCGAAGGCG", 
    "TACGGAGGGTGCGAGCGTTAATCGGAATTACTGGGCGTAAAGGGCGCGTAGGCGGTGCGTTAAGCCAGATGTGAAAGCCCCGGGCTTAACCTGGGAACGGCATTTGGAACTGGCGGACTTGAGTGCAGGAGAGGAAGGTAGAATTCCAGGTGTAGCGGTGAAATGCGTAGAGATCTGGAGGAATACCAGTGGCGAAGGCG", 
    "TACGAAGGTCCCGAGCGTTGTTCGGAATCACTGGGCGTAAAGGGAGCGTAGGCGGCGTGGTAAGTCAGATGTGAAATCCCGGGGCTCAACCCCGGAACTGCATCCGATACTGCCGTGCTAGAGGATTGGAGAGGTAGCTGGAATTCTTGGTGTAGCAGTGAAATGCGTGGAGATCAAGAGGAACACTCGTGGCGAAAGCG", 
    "AACCAGCACCTCAAGTGGTCAGGAGGATTATTGGGCCTAAAGCATCCGTAGCCGGCTCTGTAAGTTTTCGGTTAAATCTATATGCTCAACATATGGGCTGCCGGGAATACTGCATAGCTAGGGAGTGGGAGAGGTAGACGGTACTCCGTAGGAAGGGGTAAAATCCTTTGATCTATGGATGACCACCTGTGGCGAAGGCG", 
    "TACAGAGGATGCAAGCGTTATCCGGAATGATTGGGCGTAAAGCGTCTGTAGGTGGCTTTTTAAGTCCGCCGTCAAATCCCAGGGCTCAACCCTGGACAGGCGGTGGAAACTGCCAAGCTGGAGTACGGTAGGGGCAGAGGGAATTTCCGGTGGAGCGGTGAAATGCGTAGAGATCGGAAAGAACACCAACGGCGAAAGCA", 
    "TACGTAGGGCGCAAGCGTTGTCCGGAATTATTGGGCGTAAAGAGCTCGTAGGCGGCTTGTCGCGTCGGTTGTGAAAGCCCGGGGCTTAACCCCGGGTCTGCATTCGATACGGGCTAGCTAGAGTGTGGTAGGGGAGATCGGAATTCCTGGTGTAGCGGTGAAATGCGCAGATATCAGGAGGAACACCGGTGGCGAAGGCG", 
    "TACGTAGGATCCAAGCGTTATCCGGAATCACTGGGCGTAAAGCGTGCGTAGGCGGCGCGTTAAGTGCAACGCGAAATCCGGTGGCTCAACCATTTGGACTGTGTTGCATACTGGCGCGCTTGAGGATACGAGAGGTACATGGAATTAGCGGTGTAGCAGTGAAATGCGTAGATATCGCTAGGAACACCAATGGCGAAGGC", 
    "TACGTAGGGCGCGAGCGTTGTCCGGGATTATTGGGCGTAAAGAGCTCGTAGGCGGCTTGTCGCGTCGGTTGTGAAAGCCCGGGGCTTAACCCCGGGTCTGCAGTCGATACGGGCAGGCTAGAGTTCGGTAGGGGAGATCGGAATTCCTGGTGTAGCGGTGAAATGCGCAGATATCAGGAGGAACACCGGTGGCGAAGGCG", 
    "TACGTAGGGCGCAAGCGTTGTCCGGAATTATTGGGCGTAAAGAGCTCGTAGGCGGCTTGTCACGTCGGGTGTGAAAGCCCGGGGCTTAACCCCGGGTCTGCATCCGATACGGGCAGGCTAGAGTGTGGTAGGGGAGATCGGAATTCCTGGTGTAGCGGTGAAATGCGCAGATATCAGGAGGAACACCGGTGGCGAAGGCG", 
    "GACGAACCGTGCGAACGTTGTTCGGAATCACTGGGCTTAAAGGGCGCGTAGGCGGGCTATCAAGTCCGGGGTGAAATCCTCCAGCTCAACTGGAGAACTGCCTCGGATACTGATGGTCTCGAGGAGGATAGGGGCACACGGAACTGTGGGTGGAGCGGTGAAATGCGTTGATATCCATAGGAACTCCGGTGGCGAAAGCG", 
    "TACGTAGGGTGCGAGCGTTAATCGGAATTACTGGGCGTAAAGCGTGCGCAGGCGGTTTGCTAAGACCGATGTGAAATCCCCGGGCTCAACCTGGGAACTGCATTGGTGACTGGCAGGCTAGAGTATGGCAGAGGGGGGTAGAATTCCACGTGTAGCAGTGAAATGCGTAGAGATGTGGAGGAATACCGATGGCGAAGGCA", 
    "TACGTAGGGTGCAAGCGTTATCCGGATTTATTGGGCGTAAAGAGCTCGTAGGCGGTTCGTCGCGTCTGGTGTGAAAGTCCATCGCTTAACGGTGGATCGGCGCCGGGTACGGGCGGACTGGAGTGCGGTAGGGGAGACTGGAATTCCCGGTGTAACGGTGGAATGTGTAGATATCGGGAAGAACACCGATGGCGAAGGCA", 
    "TACGTAGGGTGCGAGCGTTGTCCGGAATTATTGGGCGTAAAGGGCTCGTAGGCGGTTTGTCGCGTCGGGAGTGAAAACATCCAGCTTAACTGGGTGCTTGCTTTCGATACGGGCAGACTTGAGGCATGCAGGGGAGAATGGAATTCCTGGTGTAGCGGTGAAATGCGCAGATATCAGGAGGAACACCGGTGGCGAAGGCG"
    ), c("kingdom", "phylum", "class", "order", "family", "genus", 
    "species", "confidence"))))

dput(head(SAM, 25))
new("sample_data", .Data = list(c("BEEPR.PP.10", "BEEPR.GM.17", 
"BEEPR.PP.22", "BEEPR.GM.45", "BEEPR.GM.49", "BEEPR.PP.19", "BEEPR.PP.20", 
"BEEPR.GM.22", "BEEPR.PP.45A", "BEEPR.PP.45B", "BEEPR.PP.47", 
"BEEPR.PP.50", "C.BEEPR.GM.7", "C.BEEPR.GM.8", "C.BEEPR.GM.9", 
"C.BEEPR.GM.11", "C.BEEPR.GM.13", "C.BEEPR.GM.14", "C.BEEPR.GM.16", 
"C.BEEPR.GM.18", "C.BEEPR.GM.21", "C.BEEPR.GM.23", "C.BEEPR.GM.31", 
"C.BEEPR.GM.32", "C.BEEPR.GM.33"), c(384, 9.3, 354, 171, 328, 
83.4, 396, 350, 240, 142, 414, 370, 44.2, 74.4, 57, 76.8, 80.8, 
82, 94.6, 94, 124, 98.8, 97.8, 103, 82.6), c("EKA89", "EKA93", 
"EKA96", "EKA121", "EKA129", "EKA95", "EKA95", "EKA96", "EKA121", 
"EKA122", "EKA123", "EKA129", "EKA85", "EKA86", "EKA87", "EKA89", 
"EKA90", "EKA91", "EKA92", "EKA93", "EKA95", "EKA96", "EKA103", 
"EKA103", "EKA103"), c("pollen_prov", "body", "pollen_prov", 
"body", "body", "pollen_prov", "pollen_prov", "body", "pollen_prov", 
"pollen_prov", "pollen_prov", "pollen_prov", "gut", "gut", "gut", 
"gut", "gut", "gut", "gut", "gut", "gut", "gut", "gut", "gut", 
"gut"), c(15L, 15L, 15L, 22L, 22L, 15L, 15L, 15L, 22L, 22L, 22L, 
22L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 
15L), c(5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 
5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L), c(2022L, 2022L, 
2022L, 2022L, 2022L, 2022L, 2022L, 2022L, 2022L, 2022L, 2022L, 
2022L, 2022L, 2022L, 2022L, 2022L, 2022L, 2022L, 2022L, 2022L, 
2022L, 2022L, 2022L, 2022L, 2022L), c("15.IV.2022", "15.IV.2022", 
"15.IV.2022", "22.V.2022", "22.V.2022", "15.IV.2022", "15.IV.2022", 
"15.IV.2022", "22.V.2022", "22.V.2023", "22.V.2022", "22.V.2022", 
"15.IV.2022", "15.IV.2022", "15.IV.2022", "15.IV.2022", "15.IV.2022", 
"15.IV.2022", "15.IV.2022", "15.IV.2022", "15.IV.2022", "15.IV.2022", 
"15.IV.2022", "15.IV.2022", "15.IV.2022"), c("2:45PM", "3:10PM", 
"3:25PM", "11:30AM", "12:20PM", "3:20PM", "3:20PM", "3:25PM", 
"11:30AM", "11:30AM", "11:45AM", "12:30PM", "2:30PM", "2:30PM", 
"2:30PM", "2:45PM", "3:00PM", "3:05PM", "3:10PM", "3:15PM", "3:20PM", 
"3:25PM", "4:15PM", "4:15PM", "4:15PM"), c("MayagŸez, PR, USA", 
"MayagŸez, PR, USA", "MayagŸez, PR, USA", "MayagŸez, PR, USA", 
"MayagŸez, PR, USA", "MayagŸez, PR, USA", "MayagŸez, PR, USA", 
"MayagŸez, PR, USA", "MayagŸez, PR, USA", "MayagŸez, PR, USA", 
"MayagŸez, PR, USA", "MayagŸez, PR, USA", "MayagŸez, PR, USA", 
"MayagŸez, PR, USA", "MayagŸez, PR, USA", "MayagŸez, PR, USA", 
"MayagŸez, PR, USA", "MayagŸez, PR, USA", "MayagŸez, PR, USA", 
"MayagŸez, PR, USA", "MayagŸez, PR, USA", "MayagŸez, PR, USA", 
"MayagŸez, PR, USA", "MayagŸez, PR, USA", "MayagŸez, PR, USA"
), c(1L, 1L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 1L, 1L, 1L), c(18.250797, 18.250797, 
18.251412, 18.251412, 18.250797, 18.251412, 18.251412, 18.251412, 
18.251412, 18.251412, 18.251412, 18.250797, 18.250797, 18.250797, 
18.250797, 18.250797, 18.250797, 18.250797, 18.250797, 18.251412, 
18.251412, 18.251412, 18.250797, 18.250797, 18.250797), c(-67.177461, 
-67.177461, -67.178063, -67.178063, -67.177461, -67.178063, -67.178063, 
-67.178063, -67.178063, -67.178063, -67.178063, -67.177461, -67.177461, 
-67.177461, -67.177461, -67.177461, -67.177461, -67.177461, -67.177461, 
-67.178063, -67.178063, -67.178063, -67.177461, -67.177461, -67.177461
), c(28.5, 28.5, 28.5, 28, 28, 28.5, 28.5, 28.5, 28, 28, 28, 
28, 28.5, 28.5, 28.5, 28.5, 28.5, 28.5, 28.5, 28.5, 28.5, 28.5, 
28.5, 28.5, 28.5), c("excavation", "excavation", "excavation", 
"excavation", "excavation", "excavation", "excavation", "excavation", 
"excavation", "excavation", "excavation", "excavation", "insect net", 
"insect net", "insect net", "excavation", "excavation", "excavation", 
"excavation", "excavation", "excavation", "excavation", "insect net", 
"insect net", "insect net"), c("sand", "sand", "sand", "sand", 
"sand", "sand", "sand", "sand", "sand", "sand", "sand", "sand", 
"branch", "branch", "air", "sand", "sand", "sand", "sand", "sand", 
"sand", "sand", "entrance nest", "entrance nest", "entrance nest"
), c("pollen provision", "larva", "pollen provision", "larva", 
"larva", "pollen provision", "pollen provision", "larva", "pollen provision", 
"pollen provision", "pollen provision", "pollen provision", "gut C. decolorata male", 
"gut C. decolorata female", "gut C. decolorata male", "gut C. decolorata female", 
"gut C. decolorata female", "gut C. decolorata female", "gut C. decolorata female", 
"gut C. decolorata female", "gut C. decolorata female", "gut C. decolorata female", 
"gut C. decolorata female", "gut C. decolorata female", "gut C. decolorata female"
), c("brood cell content", "brood cell content", "brood cell content", 
"brood cell content", "brood cell content", "brood cell content", 
"brood cell content", "brood cell content", "brood cell content", 
"brood cell content", "brood cell content", "brood cell content", 
"gut C. decolorata male", "gut C. decolorata female", "gut C. decolorata male", 
"gut C. decolorata female", "gut C. decolorata female", "gut C. decolorata female", 
"gut C. decolorata female", "gut C. decolorata female", "gut C. decolorata female", 
"gut C. decolorata female", "gut C. decolorata female", "gut C. decolorata female", 
"gut C. decolorata female"), c("Centris decolorata", "Centris decolorata", 
"Centris decolorata", "Centris decolorata", "Centris decolorata", 
"Centris decolorata", "Centris decolorata", "Centris decolorata", 
"Centris decolorata", "Centris decolorata", "Centris decolorata", 
"Centris decolorata", "Centris decolorata", "Centris decolorata", 
"Centris decolorata", "Centris decolorata", "Centris decolorata", 
"Centris decolorata", "Centris decolorata", "Centris decolorata", 
"Centris decolorata", "Centris decolorata", "Centris decolorata", 
"Centris decolorata", "Centris decolorata"), c("", "larva", "", 
"larva", "larva", "", "", "larva", "", "", "", "", "male", "female", 
"male", "female", "female", "female", "female", "female", "female", 
"female", "female", "female", "female"), c("pollen_prov_Centris_decolorata", 
"gut_Cd_larva_Centris_decolorata", "pollen_prov_Centris_decolorata", 
"gut_Cd_larva_Centris_decolorata", "gut_Cd_larva_Centris_decolorata", 
"pollen_prov_Centris_decolorata", "pollen_prov_Centris_decolorata", 
"gut_Cd_larva_Centris_decolorata", "pollen_prov_Centris_decolorata", 
"pollen_prov_Centris_decolorata", "pollen_prov_Centris_decolorata", 
"pollen_prov_Centris_decolorata", "gut_Cd_male_Centris_decolorata", 
"gut_Cd_female_Centris_decolorata", "gut_Cd_male_Centris_decolorata", 
"gut_Cd_female_Centris_decolorata", "gut_Cd_female_Centris_decolorata", 
"gut_Cd_female_Centris_decolorata", "gut_Cd_female_Centris_decolorata", 
"gut_Cd_female_Centris_decolorata", "gut_Cd_female_Centris_decolorata", 
"gut_Cd_female_Centris_decolorata", "gut_Cd_female_Centris_decolorata", 
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), .S3Class = "data.frame")
4

Great, thanks. I see I am completely out of my depth as I have never used any of the Bioconductor packages.

Hopefully we have some experts here who do . Another resource may be the Bioconductor forum https://support.bioconductor.org

Sorry not to be more help.

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