我想手动更改堆叠条形图的顺序,以使我的标签可读,这些标签的观察结果很少,以至于它们彼此重叠。我的目标是将顺序设置为“未分类”、“真菌”、“绿色植物”,以将几乎没有观察到的条形彼此分开。
我在这里尝试了建议的解决方案,但它不起作用。也许我错过了什么?
levels(as.factor(totaltibble$kingdom))
[1] "Fungi" "unclassified" "Viridiplantae"
phytibble <- psmelt(physeq_comp)
totaltibble <-phytibble %>%
group_by(Sample, superkingdom, kingdom)%>%
summarize(sum(Abundance))
ggplot(totaltibble, aes(superkingdom, `sum(Abundance)`, fill=factor(kingdom, levels=c("unclassified", "Fungi", "Viridiplantae"))))+
geom_col(aes(fill=kingdom))+
scale_y_continuous("Anzahl der Reads", labels = comma_format(big.mark = ".", decimal.mark = ","))+
scale_fill_manual("Reich", labels = c("Fungi", "unklassifiziert", "Viridiplantae"), values = wes_palette("Darjeeling1") )+
scale_x_discrete("Domäne", labels = c("Backteria", "Eukaryota", "unklassifiziert", "Viren"))+
ggtitle("Absolute Häufigkeit nach Reich und Domäne")+
facet_grid(~Sample, labeller=(Sample=sample_labeller))+
geom_text(aes(label=`sum(Abundance)`), vjust=1.6)+
theme_bw()
我创建情节的对象:
structure(list(Sample = c("MB5_2020_nano", "MB5_2020_nano", "MB6_2020_nano",
"MB6_2020_nano", "MB5_2020_ill", "MB5_2020_ill", "MB6_2020_ill",
"MB6_2020_ill", "MB5_2020_nano", "MB6_2020_nano", "MB5_2020_ill",
"MB5_2020_nano", "MB5_2020_nano", "MB6_2020_ill", "MB6_2020_nano",
"MB6_2020_nano", "MB6_2020_ill", "MB5_2020_nano", "MB6_2020_nano",
"MB5_2020_ill", "MB6_2020_ill", "MB5_2020_ill", "MB5_2020_ill",
"MB6_2020_ill"), superkingdom = c("Eukaryota", "unclassified",
"Eukaryota", "unclassified", "unclassified", "Eukaryota", "Eukaryota",
"unclassified", "Bacteria", "Bacteria", "Eukaryota", "Eukaryota",
"Eukaryota", "Eukaryota", "Eukaryota", "Eukaryota", "Bacteria",
"Viruses", "Viruses", "Bacteria", "Eukaryota", "Eukaryota", "Viruses",
"Viruses"), totalreads = c(740180, 740180, 220406, 220406, 122691,
122691, 41791, 41791, 740180, 220406, 122691, 740180, 740180,
41791, 220406, 220406, 41791, 740180, 220406, 122691, 41791,
122691, 122691, 41791), kingdom = c("Fungi", "unclassified",
"Fungi", "unclassified", "unclassified", "Fungi", "Fungi", "unclassified",
"unclassified", "unclassified", "unclassified", "unclassified",
"Viridiplantae", "unclassified", "unclassified", "Viridiplantae",
"unclassified", "unclassified", "unclassified", "unclassified",
"Viridiplantae", "Viridiplantae", "unclassified", "unclassified"
), abundance = c(440891, 295055, 126035, 93059, 61774, 60325,
28618, 12905, 3548, 1021, 591, 437, 224, 220, 191, 93, 47, 25,
7, 1, 1, 0, 0, 0), percent = c(59.5653759896241, 39.8626009889486,
57.1831075379073, 42.2216273604167, 50.3492513713312, 49.1682356489066,
68.4788590844919, 30.8798545141298, 0.479342862546948, 0.463236028057312,
0.481697924053109, 0.0590396930476371, 0.0302629090221298, 0.526429135459788,
0.0866582579421613, 0.0421948585791675, 0.112464406211864, 0.00337755681050555,
0.0031759570973567, 0.000815055709057714, 0.0023928597066354,
0, 0, 0)), row.names = c(NA, -24L), groups = structure(list(Sample = c("MB5_2020_ill",
"MB5_2020_ill", "MB5_2020_ill", "MB5_2020_ill", "MB5_2020_nano",
"MB5_2020_nano", "MB5_2020_nano", "MB5_2020_nano", "MB6_2020_ill",
"MB6_2020_ill", "MB6_2020_ill", "MB6_2020_ill", "MB6_2020_nano",
"MB6_2020_nano", "MB6_2020_nano", "MB6_2020_nano"), superkingdom = c("Bacteria",
"Eukaryota", "unclassified", "Viruses", "Bacteria", "Eukaryota",
"unclassified", "Viruses", "Bacteria", "Eukaryota", "unclassified",
"Viruses", "Bacteria", "Eukaryota", "unclassified", "Viruses"
), totalreads = c(122691, 122691, 122691, 122691, 740180, 740180,
740180, 740180, 41791, 41791, 41791, 41791, 220406, 220406, 220406,
220406), .rows = structure(list(20L, c(6L, 11L, 22L), 5L, 23L,
9L, c(1L, 12L, 13L), 2L, 18L, 17L, c(7L, 14L, 21L), 8L, 24L,
10L, c(3L, 15L, 16L), 4L, 19L), ptype = integer(0), class = c("vctrs_list_of",
"vctrs_vctr", "list"))), row.names = c(NA, -16L), class = c("tbl_df",
"tbl", "data.frame"), .drop = TRUE), class = c("grouped_df",
"tbl_df", "tbl", "data.frame"))