Trouble making an object in phyloseq - r

I'm trying to make an object that I can use in the package phyloseq, but I can't seem to get it to work. Below is a small subset of my data. First is an otu table, the second has the taxa.
OTUs <- dput(OTU_table[1:5,])
structure(list(OTU_ID = c("OTU_1", "OTU_6", "OTU_16", "OTU_2",
"OTU_216"), V2T4r5Croot = c(3505L, 5L, 124L, 0L, 8L), V2T4r5Broot = c(18880L,
18390L, 1L, 10233L, 0L), R6T2r5Croot = c(82973L, 5195L, 444L,
93L, 7L), V2T2r2Broot = c(13747L, 79L, 1603L, 33L, 0L), R3T2r5Broot = c(11212L,
2L, 462L, 33977L, 0L), V2T2r2Croot = c(63779L, 354L, 5204L, 374L,
0L), R3T4r5Croot = c(60109L, 1518L, 4067L, 875L, 2L), R3T1r5Aroot = c(28412L,
3161L, 626L, 3465L, 131L), R3T4r2Croot = c(40569L, 110L, 575L,
8642L, 0L), V2T2r5Aroot = c(22800L, 2225L, 1334L, 12185L, 4L),
R6T2r5Broot = c(50017L, 5739L, 4199L, 0L, 0L), R6T1r1Broot = c(52756L,
0L, 35L, 490L, 0L), R6T1r2Croot = c(14828L, 10227L, 180L,
3973L, 10L), V2T1r6Aroot = c(40317L, 146L, 543L, 5975L, 36L
), R6T2r1Broot = c(13801L, 524L, 189L, 6121L, 0L), V2T4r1Broot = c(58001L,
21L, 247L, 2359L, 5L), R6T2r6Croot = c(79608L, 715L, 384L,
13121L, 0L), R3T2r1Aroot = c(7938L, 187L, 2305L, 212L, 0L
), R6T2r6Aroot = c(20243L, 1098L, 320L, 10632L, 9L), V2T1r5Broot = c(11102L,
156L, 200L, 8205L, 0L), V2T4r2Aroot = c(7641L, 393L, 53L,
366L, 27L), R6T4r5Croot = c(5L, 68L, 7192L, 4L, 0L), R6T4r5Broot = c(40122L,
92L, 29L, 64631L, 59L), R3T4r6Croot = c(49960L, 101L, 97L,
18846L, 0L), R6T2r2Aroot = c(81204L, 7801L, 1499L, 13245L,
6L), R3T4r5Aroot = c(108839L, 5072L, 1894L, 1957L, 55L),
R3T2r1Broot = c(624L, 0L, 62L, 3687L, 0L), R6T1r5Croot = c(67805L,
0L, 238L, 2L, 0L), V2T4r6Croot = c(43210L, 24L, 0L, 33L,
0L), R3T1r6Aroot = c(6419L, 274L, 1062L, 2411L, 79L), R3T2r2Croot = c(53908L,
34726L, 3497L, 82L, 144L), R3T4r2Aroot = c(10503L, 48L, 23L,
27764L, 0L), R3T2r5Aroot = c(2386L, 79L, 39L, 1805L, 0L),
V2T2r1Croot = c(20324L, 318L, 14L, 1192L, 0L), V2T1r5Aroot = c(3933L,
33L, 6L, 3785L, 0L), V2T1r1Broot = c(99803L, 7377L, 203L,
1098L, 75L), R3T4r6Aroot = c(16601L, 1113L, 217L, 309L, 33L
), R3T2r1Croot = c(135822L, 24308L, 4986L, 219L, 230L), V2T1r5Croot = c(12444L,
139L, 32L, 211L, 0L), R3T1r6Croot = c(3957L, 9L, 117L, 293426L,
0L), R6T1r2Broot = c(92870L, 43L, 625L, 616L, 0L), V2T2r2Aroot = c(26697L,
654L, 130L, 31056L, 0L), R3T2r6Broot = c(82471L, 22990L,
3253L, 955L, 4L), R6T1r1Aroot = c(11187L, 0L, 5L, 0L, 0L),
R6T1r6Broot = c(6016L, 72L, 386L, 3368L, 0L), R3T1r1Aroot = c(55133L,
5854L, 494L, 1694L, 45L), V2T1r2Aroot = c(9346L, 139L, 17L,
64L, 0L), R3T4r1Aroot = c(84510L, 4049L, 1441L, 1193L, 5L
), R6T2r5Aroot = c(38997L, 33L, 273L, 967L, 0L), R3T4r2Broot = c(54402L,
565L, 567L, 9L, 0L), R3T1r2Broot = c(42977L, 24L, 132L, 3L,
7L), R6T1r5Aroot = c(5433L, 39L, 16L, 2L, 0L), R3T1r1Croot = c(4356L,
0L, 0L, 24719L, 0L), R3T4r5Broot = c(39402L, 6424L, 151L,
0L, 0L), R6T1r2Aroot = c(67639L, 14L, 16L, 1L, 0L), R3T2r5Croot = c(12136L,
3420L, 193L, 98L, 0L), R3T1r5Croot = c(21358L, 2876L, 347L,
9850L, 0L), V2T1r6Broot = c(16975L, 2L, 273L, 1397L, 98L),
R6T1r1Croot = c(7403L, 18L, 36L, 2112L, 0L), R3T1r1Broot = c(18301L,
1122L, 276L, 6921L, 7L), V2T2r6Croot = c(59794L, 2560L, 92L,
12437L, 0L), R6T1r5Broot = c(58396L, 1284L, 119L, 21078L,
0L), V2T4r6Broot = c(10496L, 773L, 1603L, 1950L, 19L), V2T1r6Croot = c(34687L,
9560L, 38L, 19L, 1L), R3T4r1Broot = c(23020L, 78L, 276L,
160L, 66L), V2T4r1Aroot = c(32591L, 91L, 197L, 308L, 0L),
V2T4r6Aroot = c(35314L, 3L, 1550L, 1775L, 0L), V2T2r6Aroot = c(12424L,
884L, 149L, 481L, 0L), V2T2r1Aroot = c(6721L, 52L, 203L,
4286L, 0L), R3T2r2Broot = c(26251L, 447L, 326L, 4834L, 0L
), V2T4r2Broot = c(27830L, 2404L, 1131L, 98L, 18L), R6T1r6Aroot = c(11818L,
14L, 34L, 1L, 0L), V2T1r1Croot = c(7961L, 5L, 376L, 2802L,
0L), R6T2r2Croot = c(25329L, 15L, 63L, 76L, 0L), R6T2r2Broot = c(1002L,
0L, 153L, 26L, 0L), R6T2r1Aroot = c(38869L, 11953L, 1987L,
2639L, 0L), V2T4r5Aroot = c(1838L, 18L, 1L, 47981L, 5L),
R6T4r1Aroot = c(3323L, 16L, 3L, 7212L, 0L), V2T2r5Croot = c(22124L,
1037L, 395L, 1515L, 296L), R3T4r6Broot = c(4112L, 0L, 0L,
1L, 0L), R3T1r5Broot = c(4443L, 120L, 528L, 1176L, 0L), V2T2r6Broot = c(2068L,
55L, 11L, 7180L, 0L), R3T2r2Aroot = c(4962L, 277L, 35L, 1L,
7L), V2T1r1Aroot = c(18506L, 0L, 44L, 93L, 0L), R3T1r2Aroot = c(19779L,
2L, 162L, 51355L, 8L), R6T2r1Croot = c(913L, 4L, 26L, 10L,
0L), V2T2r5Broot = c(7309L, 69L, 63L, 38L, 15L), V2T4r1Croot = c(8043L,
231L, 1351L, 787L, 18L), R3T1r6Broot = c(1973L, 1L, 0L, 40482L,
0L), R3T4r1Croot = c(4004L, 326L, 12L, 2020L, 11L), V2T1r2Croot = c(2712L,
21L, 43L, 2127L, 0L), V2T4r2Croot = c(3711L, 118L, 0L, 1487L,
50L), R3T2r6Croot = c(1491L, 290L, 55L, 33L, 0L), R6T1r6Croot = c(8541L,
0L, 0L, 0L, 0L), R6T2r6Broot = c(2561L, 6L, 2L, 387L, 0L),
V2T2r1Broot = c(2128L, 315L, 180L, 1483L, 0L), V2T1r2Broot = c(2363L,
78L, 260L, 2182L, 0L), R3T2r6Aroot = c(486L, 0L, 191L, 1209L,
0L), R3T1r2Croot = c(6014L, 18L, 126L, 587L, 0L), NC1root = c(5L,
0L, 0L, 0L, 0L), R6T4r6Aroot = c(246L, 3L, 7L, 83L, 0L)), row.names = c(NA,
5L), class = "data.frame")
and
taxa <- dput(taxa[c(1,2,6,16,216),])
structure(list(OTU_ID = c("OTU_1", "OTU_2", "OTU_6", "OTU_16",
"OTU_216"), Kingdom = c("Fungi_1", "Fungi_1", "Fungi_1", "Fungi_1",
"Fungi_1"), Phylum = c("Ascomycota_1", "Ascomycota_1", "", "Ascomycota_1",
"Basidiomycota_1"), Class = c("Sordariomycetes_1", "Dothideomycetes_1",
"", "Dothideomycetes_1", "Tremellomycetes_1"), Order = c("Hypocreales_1",
"Pleosporales_1", "", "Pleosporales_1", "Tremellales_1"), Family = c("Nectriaceae_1",
"Corynesporascaceae_1", "", "Pleosporaceae_1", "Trimorphomycetaceae"
), Genus = c("Fusarium_1", "Corynespora_1", "", "Alternaria_1",
"Saitozyma"), Species = c("", "Corynespora cassiicola ", "",
"", "")), row.names = c(1L, 2L, 6L, 16L, 216L), class = "data.frame")
Here's some code I've tried:
OTUs1 <- as.matrix(OTUs)
taxa1 <- as.matrix(taxa)
OTUs2 = otu_table(OTUs1, taxa_are_rows = TRUE)
physeq <- phyloseq(OTUs2, taxa1)
I get this error when I run the code to try and make the object:
Error in phyloseq(OTUs2, taxa1) :
Problem with OTU/taxa indices among those you provided.
Check using intersect() and taxa_names()


I assume that you are getting this error because the row.names between both matrices do not match. The following steps should resolve your error:
require("dplyr")
# Add OTU_IDs as row.names
row.names(taxa) <- taxa[,'OTU_ID']
row.names(OTUs) <- OTUs[,'OTU_ID']
# Remove the OTU_ID column
taxa <- taxa[,colnames(taxa) != 'OTU_ID']
OTUs <- OTUs[,colnames(OTUs) != 'OTU_ID']
# Make sure that OTU_IDs in taxa and OTUs overlap and are in the same order
ids <- dplyr::intersect(row.names(taxa), row.names(OTUs))
taxa <- taxa[ids,]
OTUs <- OTUs[ids,]
# Convert to phyloseq object
taxa <- tax_table(as.matrix(taxa))
OTUs <- otu_table(as.matrix(OTUs), taxa_are_rows = TRUE)
physeq <- phyloseq(taxa, OTUs)

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dds_tmp <- new(
"DESeqDataSet",
design = ~ 1,
dispersionFunction = function ()
NULL,
rowRanges = new(
"CompressedGRangesList",
unlistData = new(
"GRanges",
seqnames = new(
"Rle",
values = structure(integer(0), .Label = character(0), class = "factor"),
lengths = integer(0),
elementMetadata = NULL,
metadata = list()
),
ranges = new(
"IRanges",
start = integer(0),
width = integer(0),
NAMES = NULL,
elementType = "ANY",
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seqlengths = integer(0),
is_circular = logical(0),
genome = character(0)
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elementMetadata = new(
"DFrame",
rownames = NULL,
nrows = 0L,
listData = structure(list(), .Names = character(0)),
elementType = "ANY",
elementMetadata = NULL,
metadata = list()
),
elementType = "ANY",
metadata = list()
),
elementMetadata = new(
"DFrame",
rownames = NULL,
nrows = 50L,
listData = structure(list(), .Names = character(0)),
elementType = "ANY",
elementMetadata = new(
"DFrame",
rownames = NULL,
nrows = 0L,
listData = list(type = character(0), description = character(0)),
elementType = "ANY",
elementMetadata = NULL,
metadata = list()
),
metadata = list()
),
elementType = "GRanges",
metadata = list(),
partitioning = new(
"PartitioningByEnd",
end = c(
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L
),
NAMES = c(
"0610005C13Rik", "0610007C21Rik", "0610007L01Rik", "0610007N19Rik",
"0610007P08Rik", "0610007P14Rik", "0610007P22Rik", "0610008F07Rik",
"0610009B14Rik", "0610009B22Rik", "0610009D07Rik", "0610009L18Rik",
"0610009O20Rik", "0610010B08Rik", "0610010F05Rik", "0610010K14Rik",
"0610010O12Rik", "0610011F06Rik", "0610011L14Rik", "0610012G03Rik",
"0610012H03Rik", "0610030E20Rik", "0610031J06Rik", "0610031O16Rik",
"0610037L13Rik", "0610037P05Rik", "0610038B21Rik", "0610038L08Rik",
"0610039K10Rik", "0610040B10Rik", "0610040F04Rik", "0610040J01Rik",
"0610043K17Rik", "0910001L09Rik", "100043387", "1100001G20Rik",
"1110001A16Rik", "1110001J03Rik", "1110002B05Rik", "1110002L01Rik",
"1110002N22Rik", "1110003E01Rik", "1110004E09Rik", "1110004F10Rik",
"1110005A03Rik", "1110006O24Rik", "1110007C09Rik", "1110008F13Rik",
"1110008J03Rik", "1110008L16Rik"
),
elementType = "ANY",
elementMetadata = NULL,
metadata = list()
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),
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"DFrame",
rownames = c(
"IM_MR30_S30_L001", "IM_MR31_S31_L001", "IM_MR32_S32_L001",
"IM_MR33_S33_L001", "IM_MR34_S34_L001", "IM_MR35_S35_L001",
"IM_MR36_S36_L001", "IM_AR_30", "IM_AR_31", "IM_AR_32", "IM_AR_33"
),
nrows = 11L,
listData = list(
batch = structure(
c(1L, 1L,
1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L),
.Label = c(
"190701_K00242_0579_AH7GFLBBXY",
"180810_K00242_0453_AHVJTJBBXX-IM-AR-RS21+180814_K00242_0456_AHW5LYBBXX-IM-AR-RS21+180817_K00242_0458_AHW57TBBXX-IM-AR-RS21",
"180406_K00242_0385_AHTCCHBBXX-IM-AR-RS8+180412_K00242_0388_AHT7NYBBXX-IM-AR-RS8",
"180814_K00242_0456_AHW5LYBBXX-IM-AR-RS21+180814_K00242_0456_AHW5LYBBXX-IM-AR-RS21+180817_K00242_0458_AHW57TBBXX-IM-AR-RS21",
"190322_K00242_0534_AHYLVWBBXX_IM-AM-RS8-dT"
),
class = "factor"
),
time_label = c( "D8", "D10", "D10", "D10", "D15", "D15", "D15", "D6",
"D6", "D6", "D6"
),
time_value = c(8L, 10L,
10L, 10L, 15L, 15L, 15L, 6L, 6L, 6L, 6L),
user = c("MR",
"MR", "MR", "MR", "MR", "MR", "MR", "AR", "AR", "AR",
"AR"),
treatment = structure(
c(1L, 1L, 1L, 1L, 1L, 1L,
1L, 2L, 2L, 2L, 1L),
.Label = c("ctrl", "OE"),
class = "factor"
),
group = structure(
c(10L, 11L, 11L, 11L, 12L, 12L, 12L,
13L, 13L, 13L, 14L),
.Label = c(
"M_2i_ctrl", "M_D0_ctrl", "M_D1_ctrl", "M_D2_ctrl", "M_D3_ctrl",
"M_D4_ctrl", "M_D5_ctrl", "M_D6_ctrl", "M_D7_ctrl", "M_D8_ctrl",
"M_D10_ctrl", "M_D15_ctrl", "A_D6_OE", "A_D6_ctrl", "A_D7_ctrl",
"A_D7_OE", "A_D8_ctrl", "A_D8_OE", "A_D11_ctrl", "A_D11_OE"
),
class = "factor"
),
group_pca_label = c(
NA, "M_D10_ctrl", NA, NA, "M_D15_ctrl", NA, NA, "A_D6_OE", NA, NA,
"A_D6_ctrl"
),
condition = structure(
c(10L,
11L, 11L, 11L, 13L, 13L, 13L, 14L, 14L, 14L, 8L),
.Label = c(
"2i_ctrl", "D0_ctrl", "D1_ctrl", "D2_ctrl", "D3_ctrl", "D4_ctrl",
"D5_ctrl", "D6_ctrl", "D7_ctrl", "D8_ctrl", "D10_ctrl", "D11_ctrl",
"D15_ctrl", "D6_OE", "D7_OE", "D8_OE", "D11_OE"
),
class = "factor"
),
time = structure(
c(10L, 11L, 11L,
11L, 13L, 13L, 13L, 8L, 8L, 8L, 8L),
.Label = c(
"2i", "D0", "D1", "D2", "D3", "D4", "D5", "D6", "D7", "D8", "D10",
"D11", "D15"
),
class = "factor"
)
),
elementType = "ANY",
elementMetadata = new(
"DFrame",
rownames = NULL,
nrows = 9L,
listData = list(
type = c(
"input", "input", "input", "input", "input", "input", "input",
"input", "input"
),
description = c("",
"", "", "", "", "", "", "", "")
),
elementType = "ANY",
elementMetadata = NULL,
metadata = list()
),
metadata = list()
),
assays = new(
"SimpleAssays",
data = new(
"SimpleList",
listData = list(counts = structure(
c(
0L, 221L, 582L, 60L, 392L, 521L, 88L, 0L, 0L, 99L, 405L, 3L, 345L,
0L, 221L, 151L, 4L, 63L, 227L, 117L, 11L, 376L, 406L, 0L, 143L,
255L, 5L, 0L, 0L, 7L, 5L, 1L, 0L, 182L, 8L, 0L, 87L, 20L, 381L, 71L,
58L, 331L, 56L, 589L, 36L, 2L, 73L, 254L, 55L, 95L, 0L, 381L, 691L,
80L, 353L, 397L, 126L, 0L, 0L, 151L, 434L, 6L, 374L, 0L, 242L, 134L,
43L, 113L, 232L, 130L, 23L, 325L, 458L, 0L, 165L, 358L, 4L, 0L, 0L,
10L, 0L, 0L, 4L, 225L, 7L, 0L, 100L, 52L, 486L, 115L, 73L, 512L,
86L, 639L, 50L, 3L, 108L, 273L, 64L, 105L, 0L, 261L, 588L, 65L,
334L, 367L, 88L, 0L, 0L, 102L, 389L, 8L, 333L, 0L, 216L, 158L, 38L,
87L, 254L, 87L, 24L, 302L, 434L, 0L, 159L, 292L, 4L, 0L, 2L, 7L, 1L,
1L, 0L, 197L, 12L, 0L, 86L, 39L, 482L, 99L, 58L, 408L, 67L, 657L,
43L, 1L, 73L, 242L, 63L, 68L, 0L, 271L, 579L, 88L, 298L, 383L, 80L,
0L, 0L, 95L, 358L, 3L, 271L, 0L, 195L, 143L, 23L, 64L, 200L, 82L,
27L, 334L, 382L, 0L, 170L, 296L, 4L, 0L, 0L, 4L, 0L, 1L, 1L, 171L,
14L, 0L, 122L, 26L, 365L, 86L, 62L, 343L, 67L, 589L, 35L, 1L, 59L,
251L, 39L, 71L, 0L, 332L, 566L, 112L, 330L, 282L, 82L, 0L, 0L, 107L,
318L, 1L, 349L, 0L, 218L, 119L, 122L, 68L, 143L, 111L, 26L, 413L,
540L, 0L, 124L, 315L, 0L, 0L, 1L, 6L, 0L, 1L, 3L, 235L, 13L, 0L,
88L, 66L, 508L, 99L, 71L, 510L, 73L, 532L, 46L, 1L, 145L, 342L, 49L,
60L, 0L, 297L, 598L, 100L, 283L, 278L, 58L, 0L, 0L, 115L, 306L, 4L,
368L, 0L, 208L, 109L, 105L, 81L, 190L, 113L, 13L, 406L, 563L, 0L,
115L, 280L, 5L, 0L, 0L, 4L, 0L, 1L, 2L, 238L, 22L, 0L, 78L, 75L,
532L, 54L, 53L, 484L, 79L, 510L, 35L, 1L, 154L, 361L, 46L, 45L, 0L,
413L, 724L, 102L, 352L, 325L, 77L, 0L, 0L, 87L, 364L, 8L, 398L, 0L,
201L, 130L, 94L, 63L, 227L, 116L, 16L, 398L, 594L, 0L, 127L, 312L,
4L, 0L, 0L, 8L, 0L, 0L, 0L, 285L, 12L, 0L, 99L, 61L, 638L, 56L, 44L,
562L, 80L, 604L, 32L, 3L, 178L, 394L, 51L, 81L, 0L, 342L, 1147L,
136L, 887L, 568L, 197L, 0L, 0L, 192L, 644L, 13L, 653L, 0L, 601L,
286L, 36L, 98L, 478L, 190L, 8L, 706L, 694L, 0L, 229L, 306L, 11L, 0L,
1L, 9L, 0L, 6L, 10L, 221L, 39L, 0L, 132L, 109L, 1132L, 350L, 133L,
567L, 115L, 931L, 61L, 5L, 70L, 561L, 130L, 133L, 0L, 337L, 1162L,
135L, 927L, 578L, 182L, 0L, 0L, 242L, 665L, 21L, 702L, 0L, 674L,
307L, 35L, 122L, 475L, 176L, 8L, 653L, 714L, 0L, 251L, 312L, 11L,
0L, 3L, 15L, 0L, 9L, 10L, 209L, 31L, 0L, 168L, 111L, 1231L, 383L,
150L, 552L, 129L, 980L, 72L, 4L, 52L, 686L, 142L, 130L, 1L, 284L,
1159L, 145L, 861L, 529L, 168L, 0L, 0L, 202L, 688L, 3L, 670L, 0L,
654L, 298L, 27L, 122L, 465L, 197L, 15L, 707L, 657L, 0L, 223L, 284L,
6L, 0L, 1L, 13L, 0L, 3L, 10L, 199L, 31L, 0L, 125L, 88L, 1142L, 397L,
121L, 593L, 128L, 888L, 60L, 7L, 54L, 595L, 117L, 150L, 0L, 224L,
1228L, 68L, 894L, 674L, 213L, 0L, 0L, 197L, 798L, 12L, 758L, 0L,
446L, 285L, 21L, 75L, 458L, 185L, 5L, 738L, 456L, 0L, 261L, 339L,
7L, 0L, 0L, 9L, 0L, 0L, 1L, 180L, 32L, 0L, 110L, 98L, 919L, 249L,
134L, 387L, 188L, 1055L, 64L, 3L, 52L, 630L, 110L, 175L
),
.Dim = c(50L, 11L),
.Dimnames = list(
c(
"0610005C13Rik", "0610007C21Rik", "0610007L01Rik",
"0610007N19Rik", "0610007P08Rik", "0610007P14Rik",
"0610007P22Rik", "0610008F07Rik", "0610009B14Rik",
"0610009B22Rik", "0610009D07Rik", "0610009L18Rik",
"0610009O20Rik", "0610010B08Rik", "0610010F05Rik",
"0610010K14Rik", "0610010O12Rik", "0610011F06Rik",
"0610011L14Rik", "0610012G03Rik", "0610012H03Rik",
"0610030E20Rik", "0610031J06Rik", "0610031O16Rik",
"0610037L13Rik", "0610037P05Rik", "0610038B21Rik",
"0610038L08Rik", "0610039K10Rik", "0610040B10Rik",
"0610040F04Rik", "0610040J01Rik", "0610043K17Rik",
"0910001L09Rik", "100043387", "1100001G20Rik", "1110001A16Rik",
"1110001J03Rik", "1110002B05Rik", "1110002L01Rik",
"1110002N22Rik", "1110003E01Rik", "1110004E09Rik",
"1110004F10Rik", "1110005A03Rik", "1110006O24Rik",
"1110007C09Rik", "1110008F13Rik", "1110008J03Rik", "1110008L16Rik"
),
c(
"IM_MR30_S30_L001", "IM_MR31_S31_L001", "IM_MR32_S32_L001",
"IM_MR33_S33_L001", "IM_MR34_S34_L001", "IM_MR35_S35_L001",
"IM_MR36_S36_L001", "IM_AR_30", "IM_AR_31", "IM_AR_32", "IM_AR_33"
)
)
)),
elementType = "ANY",
elementMetadata = NULL,
metadata = list()
)
),
NAMES = NULL,
elementMetadata = new(
"DFrame",
rownames = NULL,
nrows = 50L,
listData = structure(list(), .Names = character(0)),
elementType = "ANY",
elementMetadata = NULL,
metadata = list()
),
metadata = list(version = structure(
list(c(1L, 30L, 1L)), class = c("package_version",
"numeric_version")
))
)

We can use
data_bec <- dds_tmp %>%
{sva::ComBat_seq(
counts = {.} %>% SummarizedExperiment::assay(),
batch = {.} %>% magrittr::extract2("batch") %>% droplevels(),
covar_mod = cbind(
time = {.} %>% magrittr::extract2("time") %>% droplevels(),
treatment = {.} %>% magrittr::extract2("treatment") %>% droplevels()
)
)}

Widening Data and Changing Columns

I have managed to delete a little bit of code that did the below task and can't for the life of me figure out how I did it before.
I want to widen the data that has two factors spread over 8 different 'waves'. There are four 'Paper' factors, each with the same four internal factors 'Response'. The output from a previously required function gives the following dataframe:
[
And I would like to make it look like this:
The single column of the first tibble has become the single row of the second tibble.
As you can see, the second tibble has extra factors of Paper but these can just be joined row wise.
I really wasn't sure how to attack this, but thought it would be done using the pivot_wider function. When I tried
times_correct <- times_19 %>%
pivot_wider( id_cols = c('Stay/remain in the EU`', 'Leave the EU', 'I would/will not vote', 'Don\'t know'), names_from = eurrefcolnames)
I got the error that I can't subset columns that don't exist which makes sense: I need to manually add the correct 'Waves'. I think this is relatively simple, but can't for the life of me figure out how I did it!
Here is the dput of the various tibbles:
structure(list(resp = structure(c(3L, 2L, 4L, 1L, NA, NA, NA,
NA), .Label = c("Don't Know", "Leave", "Remain", "Will Not Vote"
), class = "factor"), `Stay/remain in the EU` = c(316L, 290L,
313L, 324L, 338L, 320L, 325L, 335L), `Leave the EU` = c(157L,
123L, 159L, 154L, 134L, 189L, 187L, 181L), `I would/will not vote` = c(2L,
3L, 3L, 3L, 2L, 2L, 2L, 0L), `Don't know` = c(56L, 51L, 55L,
50L, 57L, 20L, 17L, 0L), Paper = structure(c(1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L), .Label = "Times", class = "factor")), row.names = c(NA,
-8L), class = c("tbl_df", "tbl", "data.frame"))
structure(list(resp = structure(c(3L, 2L, 4L, 1L, 3L, 2L, 4L,
1L, 3L, 2L, 4L, 1L, 3L, 2L, 4L, 1L, 3L, 2L, 4L, 1L), .Label = c("Don't Know",
"Leave", "Remain", "Will Not Vote"), class = "factor"), euRefVoteW1 = c(316L,
157L, 2L, 56L, 190L, 339L, 4L, 70L, 819L, 79L, 9L, 71L, 1294L,
1311L, 150L, 523L, 1715L, 2587L, 133L, 630L), euRefVoteW2 = c(290L,
123L, 3L, 51L, 175L, 282L, 3L, 62L, 777L, 74L, 5L, 62L, 1091L,
925L, 80L, 371L, 1528L, 2044L, 83L, 517L), euRefVoteW3 = c(313L,
159L, 3L, 55L, 199L, 334L, 4L, 69L, 835L, 81L, 10L, 57L, 1348L,
1289L, 139L, 508L, 1766L, 2563L, 156L, 586L), euRefVoteW4 = c(324L,
154L, 3L, 50L, 215L, 328L, 2L, 61L, 848L, 70L, 10L, 55L, 1397L,
1267L, 128L, 492L, 1853L, 2494L, 143L, 583L), euRefVoteW6 = c(338L,
134L, 2L, 57L, 241L, 286L, 2L, 77L, 853L, 68L, 5L, 57L, 1519L,
1133L, 112L, 520L, 2017L, 2284L, 106L, 667L), euRefVoteW7 = c(320L,
189L, 2L, 20L, 186L, 384L, 2L, 34L, 832L, 109L, 8L, 34L, 1449L,
1456L, 87L, 292L, 1906L, 2785L, 55L, 328L), euRefVoteW8 = c(325L,
187L, 2L, 17L, 187L, 384L, 1L, 34L, 836L, 118L, 5L, 24L, 1462L,
1522L, 72L, 228L, 1898L, 2852L, 56L, 268L), euRefVoteW9 = c(335L,
181L, 0L, 0L, 206L, 385L, 0L, 6L, 844L, 102L, 0L, 4L, 1572L,
1462L, 0L, 21L, 2018L, 2827L, 0L, 20L), Paper = structure(c(1L,
1L, 1L, 1L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 5L,
5L, 5L, 5L), .Label = c("Times", "Telegraph", "Control", "No_Paper",
"Rest"), class = "factor")), row.names = c(NA, -20L), class = c("tbl_df",
"tbl", "data.frame"))
eurrefcolnames = c('euRefVoteW1','euRefVoteW2', 'euRefVoteW3', 'euRefVoteW4', 'euRefVoteW6',' euRefVoteW7', 'euRefVoteW8', 'euRefVoteW9')
EDIT:
Here is the function that create the initial dataframes, is there an edit I could make here perhaps ?
tally_reader_number <- function(input_dataframe,newspaper_name) {
#function takes the input of in_all_waves, tallies the number of different eu ref responses using map_df for a given newspaper factor (defined above)
# and returns a dataframe of responese for each wave with the newspaper factor as a column
returned_dataframe <- input_dataframe %>%
filter(Paper == newspaper_name) %>%
ungroup() %>% #function refuses to work without this
select(-Paper) %>%
map_df(table) %>% # use map_df from the purrr package to "table" each column
rownames_to_column("response") %>% #convert the rownames to a column named response
mutate(resp = case_when(response == 1 ~ "Remain", #change the resulting numbers to the correct responses
response == 2 ~ "Leave",
response ==3 ~ "Will Not Vote",
response == 4 ~ "Don't Know")) %>%
select(resp, everything(), -response) %>% #reorder the columns with resp at the front, removing response
mutate(Paper = newspaper_name)
returned_dataframe$Paper <- as.factor(returned_dataframe$Paper)
returned_dataframe$resp <- as.factor(returned_dataframe$resp)
returned_dataframe
}

Need help in ggplot doing multiple factor barplot with error bar

I have a data for which I like to plot a barplot with error bar.
My data is as below:
dput(level6.top35)
structure(list(patient = structure(c(3L, 3L, 3L, 1L, 1L, 1L,
4L, 4L, 4L, 5L, 5L, 6L, 6L, 6L, 7L, 7L, 7L, 8L, 8L, 8L, 9L, 9L,
9L, 10L, 10L, 10L, 11L, 11L, 11L, 2L, 2L, 2L), .Label = c("P1",
"P10", "P11", "P2", "P3", "P4", "P5", "P6", "P7", "P8", "P9"), class = "factor"),
visit = structure(c(1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L,
2L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L,
3L, 1L, 2L, 3L, 1L, 2L, 3L), .Label = c("V1", "V2", "V3"), class = "factor"),
Bacteroides = c(11095L, 9981L, 2426L, 6107L, 14806L, 785L,
34127L, 27590L, 4699L, 42464L, 32146L, 321L, 611L, 402L,
455L, 5597L, 475L, 2842L, 481L, 11508L, 2125L, 842L, 960L,
3215L, 12118L, 10526L, 517L, 67434L, 82449L, 419L, 25643L,
4455L), Clostridium = c(53693L, 51961L, 89862L, 1122L, 3987L,
3095L, 3083L, 372L, 1628L, 4L, 13L, 11346L, 47803L, 10120L,
939L, 2280L, 11355L, 18642L, 4358L, 53L, 47L, 22L, 44L, 1897L,
9328L, 4394L, 4886L, 7025L, 175L, 1522L, 14776L, 30405L),
Turicibacter = c(25L, 0L, 10L, 9L, 0L, 0L, 4428L, 382L, 827L,
18L, 0L, 370L, 106L, 2180L, 5789L, 422L, 4355L, 1585L, 21205L,
567L, 131028L, 32389L, 14953L, 50692L, 3666L, 9811L, 1694L,
123L, 103L, 475L, 1038L, 0L), Haemophilus = c(31L, 27L, 13L,
2693L, 530L, 908L, 103L, 217L, 22L, 21743L, 7413L, 40763L,
1303L, 40182L, 52L, 67L, 18501L, 7547L, 28384L, 756L, 19L,
43928L, 19930L, 433L, 70L, 952L, 16796L, 4415L, 88L, 0L,
4607L, 507L), Streptococcus = c(303L, 160L, 168L, 1205L,
8360L, 12927L, 8380L, 1341L, 306L, 865L, 3490L, 137L, 428L,
427L, 5215L, 861L, 11635L, 15341L, 7306L, 12963L, 192L, 1646L,
2311L, 645L, 9880L, 9314L, 9091L, 6649L, 7283L, 26253L, 21089L,
39463L), Intestinibacter = c(14L, 16L, 0L, 17L, 11L, 32L,
4991L, 17L, 76L, 13L, 0L, 8182L, 14976L, 8062L, 7529L, 917L,
6612L, 14714L, 23287L, 26558L, 32L, 10L, 46L, 18307L, 7201L,
11970L, 6983L, 2963L, 2172L, 1812L, 0L, 1115L), Ruminococcus = c(3237L,
7853L, 95L, 4209L, 380L, 105L, 4141L, 18344L, 16L, 4000L,
2374L, 17L, 690L, 33L, 3393L, 7285L, 259L, 11344L, 69L, 5175L,
46L, 13L, 64L, 156L, 8923L, 19573L, 60L, 6626L, 7614L, 188L,
998L, 109L), Veillonella = c(630L, 318L, 512L, 302L, 1739L,
420L, 779L, 495L, 11L, 538L, 2857L, 338L, 466L, 1777L, 37L,
423L, 2597L, 1330L, 457L, 1720L, 239L, 4659L, 1864L, 188L,
1062L, 4061L, 279L, 723L, 291L, 11009L, 14337L, 7129L), Sutterella = c(65L,
46L, 25L, 27L, 0L, 62L, 20L, 16L, 38L, 8499L, 7987L, 35L,
78L, 37L, 21L, 84L, 12L, 238L, 39L, 1746L, 26L, 31L, 65L,
383L, 11200L, 565L, 50L, 40L, 17L, 14L, 1407L, 353L), Epulopiscium = c(0L,
0L, 0L, 0L, 0L, 12L, 0L, 0L, 0L, 0L, 0L, 14447L, 8925L, 7733L,
0L, 6L, 20L, 823L, 158L, 84L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L), Faecalibacterium = c(184L, 203L, 154L,
113L, 92L, 135L, 111L, 144L, 102L, 1297L, 21410L, 132L, 185L,
138L, 127L, 151L, 135L, 204L, 173L, 128L, 203L, 148L, 191L,
177L, 169L, 171L, 193L, 150L, 133L, 169L, 4444L, 404L), Bifidobacterium = c(2288L,
8161L, 63L, 605L, 169L, 95L, 46L, 71L, 72L, 876L, 2540L,
60L, 467L, 73L, 578L, 1537L, 79L, 5413L, 73L, 543L, 127L,
86L, 144L, 76L, 775L, 71L, 84L, 80L, 64L, 47L, 49L, 70L),
Tyzzerella = c(18L, 0L, 0L, 559L, 0L, 0L, 1408L, 1666L, 0L,
86L, 373L, 0L, 373L, 0L, 439L, 235L, 107L, 21L, 0L, 0L, 0L,
0L, 25L, 134L, 4126L, 12034L, 4L, 0L, 0L, 0L, 47L, 0L), Lactobacillus = c(0L,
0L, 0L, 0L, 0L, 14L, 0L, 0L, 0L, 0L, 0L, 5L, 11L, 4L, 39L,
25L, 321L, 56L, 0L, 36L, 0L, 5L, 0L, 5L, 848L, 63L, 0L, 138L,
538L, 3801L, 122L, 4373L), Serratia = c(0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 128L, 69L, 0L, 0L, 0L, 0L, 0L, 226L, 0L,
0L, 0L, 0L, 0L, 7828L, 0L, 0L, 0L, 0L, 70L, 0L, 0L, 0L, 0L
), Rothia = c(0L, 0L, 11L, 6L, 16L, 24L, 0L, 0L, 5L, 0L,
0L, 0L, 0L, 10L, 0L, 9L, 11L, 140L, 267L, 175L, 0L, 190L,
4617L, 0L, 0L, 0L, 1362L, 19L, 47L, 518L, 21L, 34L), Anaerosporobacter = c(0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 256L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 31L, 3239L, 3546L, 0L, 0L,
0L, 0L, 0L, 0L), Erysipelatoclostridium = c(19L, 0L, 7L,
184L, 194L, 23L, 320L, 129L, 7L, 1151L, 436L, 20L, 52L, 0L,
862L, 1365L, 88L, 20L, 0L, 263L, 9L, 6L, 71L, 46L, 1175L,
217L, 0L, 190L, 98L, 0L, 72L, 26L), Paeniclostridium = c(0L,
0L, 0L, 0L, 303L, 0L, 0L, 0L, 0L, 0L, 0L, 129L, 9L, 339L,
0L, 0L, 66L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 5167L, 228L,
221L, 0L, 0L, 0L), Blautia = c(526L, 132L, 101L, 87L, 19L,
97L, 93L, 118L, 71L, 204L, 1356L, 70L, 105L, 84L, 71L, 144L,
88L, 649L, 136L, 627L, 156L, 88L, 142L, 83L, 139L, 138L,
134L, 122L, 81L, 99L, 98L, 125L), Anaerostipes = c(27L, 38L,
25L, 20L, 10L, 24L, 17L, 21L, 0L, 709L, 4603L, 23L, 24L,
20L, 0L, 178L, 18L, 30L, 42L, 24L, 29L, 16L, 37L, 23L, 57L,
39L, 29L, 29L, 16L, 26L, 25L, 27L), Enterococcus = c(31L,
32L, 26L, 126L, 68L, 2498L, 70L, 31L, 26L, 0L, 15L, 59L,
57L, 23L, 395L, 758L, 133L, 0L, 0L, 27L, 50L, 36L, 56L, 21L,
39L, 0L, 422L, 159L, 20L, 24L, 96L, 95L), Citrobacter = c(0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 3583L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 37L, 0L, 0L, 0L, 1088L, 0L, 0L, 0L, 0L, 0L, 144L,
0L, 0L, 0L, 0L), Prevotella = c(155L, 168L, 87L, 153L, 95L,
121L, 100L, 125L, 152L, 307L, 124L, 100L, 84L, 117L, 91L,
168L, 128L, 137L, 130L, 98L, 139L, 114L, 252L, 84L, 159L,
106L, 140L, 201L, 114L, 126L, 160L, 125L), Roseburia = c(621L,
19L, 0L, 0L, 0L, 0L, 0L, 18L, 0L, 46L, 32L, 17L, 13L, 0L,
0L, 36L, 17L, 160L, 0L, 109L, 18L, 15L, 22L, 77L, 1505L,
559L, 38L, 26L, 12L, 22L, 849L, 90L), Parabacteroides = c(60L,
18L, 12L, 114L, 9L, 49L, 349L, 593L, 60L, 158L, 162L, 46L,
53L, 42L, 17L, 33L, 29L, 197L, 49L, 458L, 42L, 45L, 83L,
271L, 479L, 429L, 51L, 63L, 76L, 0L, 85L, 47L), Neisseria = c(0L,
0L, 0L, 77L, 0L, 0L, 0L, 12L, 0L, 9L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 454L, 2L, 0L, 0L, 771L, 2662L, 4L, 0L, 11L, 10L,
0L, 0L, 0L, 0L, 0L), Actinobacillus = c(0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 2670L, 149L, 0L, 0L, 0L, 0L, 0L, 0L, 130L,
0L, 0L, 0L, 0L, 0L, 10L, 0L, 60L, 0L, 0L, 0L, 0L, 0L, 0L),
Granulicatella = c(59L, 27L, 22L, 18L, 22L, 14L, 19L, 36L,
76L, 37L, 0L, 0L, 0L, 61L, 60L, 24L, 93L, 90L, 457L, 60L,
52L, 42L, 215L, 0L, 40L, 45L, 665L, 14L, 27L, 260L, 34L,
46L), Actinomyces = c(52L, 27L, 12L, 8L, 8L, 16L, 36L, 16L,
89L, 12L, 23L, 13L, 0L, 53L, 18L, 0L, 30L, 112L, 624L, 89L,
12L, 45L, 116L, 11L, 58L, 12L, 587L, 65L, 47L, 135L, 18L,
35L), Lachnoclostridium = c(21L, 19L, 17L, 37L, 0L, 0L, 211L,
337L, 13L, 361L, 184L, 0L, 12L, 12L, 19L, 91L, 0L, 66L, 0L,
228L, 44L, 9L, 0L, 77L, 293L, 257L, 0L, 0L, 0L, 0L, 28L,
20L), Pediococcus = c(0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 2101L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 9L, 0L, 0L, 0L, 0L, 0L, 0L), Fusobacterium = c(84L,
51L, 55L, 551L, 12L, 19L, 22L, 54L, 23L, 41L, 40L, 21L, 17L,
14L, 14L, 78L, 18L, 228L, 88L, 35L, 75L, 43L, 162L, 24L,
39L, 25L, 90L, 15L, 21L, 56L, 24L, 36L), Alistipes = c(68L,
81L, 24L, 69L, 35L, 66L, 40L, 57L, 60L, 86L, 72L, 48L, 47L,
60L, 51L, 92L, 48L, 67L, 72L, 36L, 40L, 65L, 137L, 21L, 31L,
65L, 84L, 100L, 93L, 42L, 81L, 41L), Eubacterium = c(0L,
7L, 0L, 0L, 0L, 0L, 0L, 0L, 8L, 12L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L)), .Names = c("patient", "visit", "Bacteroides", "Clostridium",
"Turicibacter", "Haemophilus", "Streptococcus", "Intestinibacter",
"Ruminococcus", "Veillonella", "Sutterella", "Epulopiscium",
"Faecalibacterium", "Bifidobacterium", "Tyzzerella", "Lactobacillus",
"Serratia", "Rothia", "Anaerosporobacter", "Erysipelatoclostridium",
"Paeniclostridium", "Blautia", "Anaerostipes", "Enterococcus",
"Citrobacter", "Prevotella", "Roseburia", "Parabacteroides",
"Neisseria", "Actinobacillus", "Granulicatella", "Actinomyces",
"Lachnoclostridium", "Pediococcus", "Fusobacterium", "Alistipes",
"Eubacterium"), class = "data.frame", row.names = c("AA_001_20-4-16",
"AA_001-V2", "AA_001_19-5-16", "AA_ISS-01-V1", "AA_ISS-01-V2",
"AA_ISS-01-V3", "AA_ISS-02-V1", "AA_ISS-02-V2", "AA_ISS-02-V3",
"AA_ISS-03-V1", "AA_ISS-03-V2", "AA_ISS-04-V1", "AA_ISS-04-V2",
"AA_ISS-04-V3", "AA_ISS-05-V1", "AA_ISS-05-V2", "AA_ISS-05-V3",
"AA_ISS-06-V1", "AA_ISS-06-V2", "AA_ISS-06-V3", "AA_ISS-07-V1",
"AA_ISS-07-V2", "AA_ISS-07-V3", "AA_ISS-08-V1", "AA_ISS-08-V2",
"AA_ISS-08-V3", "AA_ISS-09-V1", "AA_ISS-09-V2", "AA_ISS-09-V3",
"AA_ISS-10-V1", "AA_ISS-10-V2", "AA_ISS-10-V3"))
So far I have tried to reshape the data and few tries to plot them properly. But in vain.
library(reshape2)
df1<-melt(level6.top35, id.vars = c("patient","visit"))
ggplot(data=df1,aes(x=variable,y=value, fill=visit))+geom_bar(position="dodge",stat="identity")
+geom_errorbar( aes(x=variable, ymin=value-sd, ymax=value+sd), width=0.4, colour="orange", alpha=0.9, size=1.3)
I have managed to do the plot but not the errorbar. Ideally I like to have a barplot with the error bar.

You need to summarise the data and then add the error bars, e.g. like this:
df1 <- melt(level6.top35, id.vars = c("patient","visit"))
df1 %>% group_by(visit, variable) %>%
summarise(SD = sd(value), value = mean(value)) %>% ungroup() %>%
ggplot(., aes(x=variable, y=value, fill = visit)) +
geom_bar(stat="identity", position = "dodge") +
geom_errorbar(aes(ymin= value - SD, ymax = value + SD, width=0.2),
position=position_dodge(width=0.90)) +
theme(axis.text.x = element_text(angle = 90, hjust = 1))+
labs(x="Species")
It is still up to you to decide whether you want to just plot the positive bars, limit the y axis to avoid negative values, etc..

Plot visreg over an boxplot (GLM with binominal predictor)

I fitted some GLMs with a binominal predictor and would like to plot them with visreg. I usually plot the raw data with par(new=T) as well for better clarity. I don't really like the normal outcome here (x-axis 0-1 in 0.2 steps, a lot of data points just at 0 and 1) and was thinking about plotting the visreg over boxplot since they look much better with binominal data. However, I can't get the two plots to align since there are always two different "starts" and "ends" in the plot. How can I make it so that the visreg line starts at the "No" and ends at the "Yes" of the boxplot?
fit <- glm (Cov.herb ~ Fire, family=gaussian, data=data)
boxplot(data$Cov.herb ~ data$Fire, ylim=c(0,100), axes=F, ylab="Herb cover [%]", xlab="Fire")
axis(1, xaxp=c(1,2,1), xaxt="n")
mtext(text=c("No","Yes"),side=1,line=0.5,at=c(1,2))
axis(2, las=1)
box()
par(new=T)
visreg(fit, scale = "response", type="conditional",line=list(col="red", lwd=1), ylim=c(0,100), xlim=c(0,1), rug=F, axes=F, ann=F)
example plot
Cheers,
Alex
data:
structure(list(Cov.herb = c(40L, 80L, 30L, 2L, 40L, 8L, 5L, 5L,
20L, 45L, 55L, 55L, 35L, 40L, 65L, 70L, 2L, 15L, 1L, 1L, 1L,
25L, 10L, 1L, 10L, 5L, 5L, 15L, 10L, 5L, 15L, 5L, 5L, 35L, 1L,
1L, 35L, 1L, 10L, 5L, 5L, 10L, 5L, 10L, 10L, 20L, 10L, 0L, 3L,
1L, 2L, 4L, 1L, 10L, 30L, 10L, 1L, 2L, 0L, 15L, 25L, 50L, 15L,
35L, 30L, 5L, 5L, 1L, 1L, 1L, 10L, 0L, 0L, 5L, 2L, 1L, 10L, 0L,
2L, 1L, 1L, 5L, 1L, 15L, 1L, 1L, 1L, 0L, 5L, 25L, 3L, 0L, 0L,
1L, 0L, 0L, 0L, 0L, 3L, 1L, 1L, 0L, 5L, 1L, 1L, 1L, 1L, 7L, 1L,
1L, 1L, 1L, 5L, 0L, 2L, 3L, 5L, 3L, 1L, 1L, 2L, 0L, 2L, 0L, 10L,
1L, 20L, 3L, 5L, 20L, 3L, 20L, 5L, 10L, 15L, 30L, 0L, 20L, 45L,
1L, 1L, 2L, 1L, 3L, 0L, 5L, 0L, 35L, 1L, 5L, 25L, 0L, 0L, 40L,
3L, 15L, 10L, 3L, 50L, 30L, 10L, 1L, 0L, 5L, 10L, 10L, 2L, 2L,
5L, 1L, 2L, 1L, 1L, 0L, 0L, 1L, 2L, 5L, 15L, 0L, 1L, 1L, 1L,
1L, 0L, 1L, 5L, 1L, 5L, 35L, 1L, 0L, 1L, 0L, 5L, 1L, 1L, 3L,
15L, 1L, 3L, 1L, 0L, 0L, 0L, 15L, 0L, 1L, 1L, 3L, 35L, 80L, 10L,
2L, 10L, 3L, 3L, 2L, 10L, 50L, 20L, 40L, 2L, 40L, 45L, 25L, 5L,
25L, 50L, 35L, 15L, 45L, 10L, 5L, 15L, 2L, 30L, 2L, 3L, 15L,
5L, 45L, 35L, 20L, 70L, 20L, 10L, 30L, 25L, 8L, 4L, 45L, 60L,
35L, 5L, 40L, 30L, 0L, 30L, 3L, 4L, 25L, 15L, 10L, 15L, 25L,
20L, 7L, 25L, 25L, 40L, 35L, 30L, 40L, 25L, 50L, 30L, 25L, 60L,
15L, 25L, 25L, 50L, 30L, 20L, 2L, 3L, 20L, 25L, 35L, 30L, 10L,
15L, 65L, 10L, 20L, 20L, 2L, 7L, 20L, 25L, 30L, 30L, 9L, 20L,
40L, 7L, 20L, 15L, 15L, 30L, 20L, 35L, 8L, 40L, 20L, 3L, 55L,
35L, 10L, 10L, 65L, 20L, 35L, 60L, 45L, 20L, 10L, 35L, 15L, 20L,
15L, 40L, 10L, 10L, 60L, 60L, 40L, 10L, 10L, 25L, 8L, 20L, 40L,
15L, 25L, 5L, 20L, 20L, 20L, 25L, 30L, 35L, 20L, 110L, 50L, 20L,
20L, 10L, 45L, 25L, 20L, 55L, 10L, 5L, 15L, 15L, 1L, 10L, 15L,
15L, 10L, 30L, 20L, 40L, 55L, 55L, 20L, 30L, 10L, 50L, 40L, 5L,
15L, 10L, 30L, 15L, 20L, 5L, 45L, 50L, 25L, 45L, 30L, 7L, 25L,
30L, 5L, 7L, 50L, 60L, 50L, 10L, 30L, 50L, 15L, 15L, 30L, 15L,
25L, 40L, 10L, 2L, 60L, 20L, 65L, 5L, 15L, 3L, 15L, 40L, 50L,
45L, 30L, 5L, 45L, 15L, 25L, 65L, 15L, 50L, 55L, 30L, 10L, 35L,
15L, 20L, 20L, 10L, 20L, 15L, 45L, 40L, 10L, 7L, 25L, 20L, 60L,
4L, 7L, 40L, 60L, 50L, 50L, 10L, 50L, 5L, 10L, 50L, 20L, 40L,
20L, 25L, 25L, 35L, 10L, 2L, 15L, 60L, 25L, 30L, 20L, 25L, 10L,
10L, 20L, 40L, 40L, 45L, 10L, 35L, 60L, 50L, 10L, 40L, 50L, 25L,
20L, 25L, 25L, 45L, 20L, 30L, 65L, 30L, 35L, 40L, 25L, 15L, 10L,
50L, 25L, 45L, 40L, 20L, 5L, 65L, 5L, 10L, 15L, 7L, 20L, 45L,
15L, 5L, 20L, 20L, 20L, 50L, 15L, 20L, 30L, 25L, 45L, 45L, 35L,
40L, 45L, 4L, 10L, 20L, 20L, 30L, 15L, 30L, 50L, 35L, 45L, 25L,
25L, 10L, 5L, 30L, 30L, 10L, 70L, 25L, 25L, 7L, 20L, 5L, 20L,
8L, 15L, 10L, 20L, 10L, 7L, 15L, 15L, 40L, 50L, 15L, 20L, 8L,
45L, 40L, 15L, 25L, 40L, 20L, 35L, 40L, 70L, 20L, 20L, 40L, 5L,
20L, 7L, 40L, 10L, 5L, 45L, 20L, 10L, 20L, 20L, 45L, 15L, 7L,
30L, 30L, 35L, 10L, 20L, 5L, 15L, 35L, 40L, 40L, 10L, 5L, 15L,
70L, 20L, 85L, 15L, 7L, 55L, 55L, 5L, 20L, 25L, 5L, 30L, 20L,
8L, 30L, 40L, 25L, 10L, 5L, 30L, 10L, 5L, 10L, 35L, 2L, 10L,
10L, 10L, 90L, 45L, 60L, 7L, 1L, 15L), Fire = c(0L, 1L, 0L, 1L,
0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L,
1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 1L, 0L, 0L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 0L, 1L, 0L, 1L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L,
0L, 1L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 1L, 0L, 0L, 0L, 1L, 1L,
0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L,
1L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 1L,
0L, 0L, 1L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 1L, 1L, 0L, 1L, 1L, 0L, 1L, 1L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 1L,
0L, 0L, 1L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 1L, 0L, 0L,
1L, 1L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 1L, 1L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L,
1L, 0L, 0L, 1L, 0L, 1L, 0L, 1L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L,
1L, 0L, 1L, 0L, 0L, 0L, 1L, 1L, 0L, 0L, 0L, 0L, 1L, 1L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 0L, 1L, 1L, 1L, 1L, 1L,
1L, 0L, 0L, 0L, 1L, 1L, 0L, 0L, 1L, 0L, 0L, 0L, 1L, 1L, 1L, 0L,
1L, 1L, 1L, 0L, 0L, 0L, 0L, 1L, 1L, 0L, 0L, 1L, 0L, 0L, 0L, 0L,
1L, 1L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L,
1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 1L, 0L, 0L, 0L,
1L, 1L, 0L, 0L, 0L, 1L, 0L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 1L,
0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 0L, 0L,
0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L)), .Names = c("Cov.herb",
"Fire"), class = "data.frame", row.names = c(2L, 3L, 4L, 6L,
7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L,
20L, 21L, 22L, 23L, 24L, 25L, 26L, 27L, 29L, 30L, 31L, 32L, 33L,
34L, 35L, 36L, 37L, 38L, 39L, 40L, 41L, 43L, 44L, 45L, 46L, 47L,
48L, 49L, 50L, 51L, 54L, 55L, 56L, 57L, 58L, 59L, 60L, 61L, 62L,
63L, 64L, 65L, 66L, 67L, 68L, 69L, 70L, 71L, 72L, 74L, 75L, 76L,
77L, 78L, 79L, 80L, 81L, 82L, 83L, 84L, 85L, 87L, 88L, 89L, 90L,
91L, 92L, 93L, 94L, 95L, 96L, 97L, 98L, 99L, 100L, 101L, 102L,
103L, 104L, 105L, 106L, 107L, 108L, 109L, 110L, 111L, 112L, 113L,
114L, 115L, 116L, 117L, 118L, 119L, 120L, 121L, 122L, 123L, 124L,
125L, 126L, 153L, 154L, 155L, 161L, 162L, 163L, 164L, 165L, 166L,
167L, 169L, 170L, 171L, 173L, 174L, 175L, 176L, 177L, 178L, 179L,
180L, 181L, 182L, 183L, 184L, 185L, 186L, 187L, 188L, 189L, 190L,
191L, 192L, 193L, 194L, 195L, 196L, 197L, 198L, 199L, 200L, 201L,
202L, 203L, 204L, 205L, 206L, 207L, 209L, 211L, 213L, 214L, 215L,
216L, 217L, 218L, 219L, 220L, 221L, 222L, 223L, 224L, 225L, 226L,
227L, 228L, 229L, 230L, 231L, 232L, 233L, 234L, 235L, 236L, 237L,
238L, 239L, 240L, 241L, 242L, 243L, 244L, 245L, 246L, 247L, 248L,
249L, 250L, 251L, 252L, 253L, 254L, 255L, 256L, 257L, 258L, 259L,
260L, 261L, 262L, 263L, 269L, 270L, 274L, 275L, 276L, 277L, 279L,
280L, 281L, 282L, 283L, 284L, 285L, 286L, 287L, 288L, 289L, 290L,
291L, 292L, 293L, 294L, 295L, 296L, 297L, 298L, 299L, 300L, 301L,
302L, 303L, 304L, 305L, 306L, 307L, 308L, 309L, 310L, 311L, 312L,
313L, 314L, 315L, 316L, 317L, 318L, 319L, 320L, 321L, 322L, 323L,
324L, 325L, 326L, 327L, 328L, 329L, 330L, 331L, 332L, 333L, 334L,
335L, 336L, 337L, 338L, 339L, 340L, 341L, 342L, 343L, 344L, 345L,
346L, 347L, 349L, 350L, 351L, 352L, 353L, 354L, 355L, 356L, 357L,
358L, 359L, 360L, 361L, 362L, 363L, 364L, 365L, 366L, 367L, 368L,
369L, 370L, 371L, 372L, 373L, 374L, 375L, 376L, 377L, 378L, 380L,
381L, 382L, 383L, 384L, 385L, 386L, 387L, 388L, 389L, 390L, 391L,
392L, 393L, 394L, 395L, 396L, 397L, 398L, 399L, 400L, 401L, 402L,
403L, 404L, 405L, 406L, 407L, 408L, 409L, 410L, 411L, 412L, 413L,
414L, 415L, 416L, 417L, 418L, 419L, 420L, 421L, 422L, 423L, 424L,
425L, 426L, 427L, 428L, 429L, 430L, 431L, 432L, 433L, 434L, 435L,
436L, 437L, 438L, 439L, 440L, 441L, 443L, 444L, 445L, 446L, 447L,
448L, 449L, 450L, 451L, 453L, 454L, 455L, 457L, 458L, 459L, 460L,
461L, 463L, 464L, 465L, 466L, 467L, 468L, 469L, 470L, 471L, 472L,
473L, 474L, 475L, 476L, 477L, 478L, 479L, 480L, 481L, 482L, 483L,
484L, 485L, 486L, 487L, 488L, 489L, 490L, 491L, 492L, 493L, 494L,
495L, 496L, 497L, 498L, 499L, 500L, 501L, 502L, 503L, 504L, 505L,
506L, 507L, 508L, 509L, 510L, 511L, 512L, 513L, 514L, 515L, 516L,
517L, 518L, 519L, 520L, 521L, 522L, 523L, 524L, 525L, 526L, 527L,
528L, 529L, 530L, 531L, 532L, 533L, 534L, 535L, 536L, 537L, 538L,
539L, 540L, 541L, 542L, 543L, 544L, 545L, 546L, 547L, 548L, 549L,
551L, 552L, 553L, 554L, 555L, 556L, 557L, 558L, 559L, 560L, 561L,
562L, 563L, 564L, 565L, 566L, 567L, 568L, 569L, 570L, 571L, 572L,
573L, 574L, 575L, 576L, 577L, 578L, 579L, 580L, 581L, 582L, 583L,
584L, 585L, 587L, 588L, 589L, 590L, 591L, 592L, 593L, 594L, 595L,
596L, 597L, 598L, 599L, 600L, 601L, 602L, 603L, 604L, 605L, 606L,
607L, 608L, 609L, 610L, 611L, 612L, 613L, 614L, 615L, 616L, 617L,
618L, 619L, 620L, 621L, 622L, 623L, 624L, 625L, 626L, 628L, 629L,
631L, 632L, 633L, 634L, 635L, 636L, 637L, 638L, 639L, 640L, 641L,
642L, 643L, 644L, 645L, 646L, 648L, 649L, 650L, 651L, 652L, 653L,
654L, 655L, 656L, 657L, 658L, 659L, 660L, 661L, 662L, 663L, 664L,
665L, 666L, 667L, 668L, 669L, 670L, 671L, 672L, 673L, 674L, 675L,
676L, 677L, 678L, 679L, 680L, 682L, 683L, 684L, 685L, 686L, 687L,
689L, 690L, 691L, 692L, 693L, 694L, 697L, 698L, 699L, 700L, 701L,
702L, 704L, 705L, 706L, 707L))

So, my point was that doing it this way would give you more flexibility with your plotting. For example,
# Fit model
fit <- glm (Cov.herb ~ Fire, family=gaussian, data=data)
# Get model data for plotting
vis.out <- visreg(fit, scale = "response", plot = FALSE)
# Load library
library(ggplot2)
# Create plot
p <- ggplot(data = data)
p <- p + geom_boxplot(aes(x = as.factor(Fire), y = Cov.herb, fill = as.factor(Fire)), alpha = 0.3, outlier.alpha = 1)
p <- p + xlab("Fire") + ylab("Herb cover [%]")
p <- p + geom_ribbon(data = vis.out$fit, aes(x = Fire + 1, ymin = visregLwr, ymax = visregUpr), fill = "lightgrey")
p <- p + geom_line(data = vis.out$fit, aes(x = Fire + 1, y = visregFit), colour = "salmon", size = 1.25)
p <- p + scale_x_discrete(labels = c("No", "Yes"))
p <- p + theme(legend.position = "none")
print(p)
gives,
Is that the sort of thing you're looking for? (You could also add all the data points using geom_point to plot on top of the boxes. I think that usually looks pretty cool.)

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