Make upset plot for phyloseq object.

Alternative to venn plot.

Usage

upset_pq(
  physeq,
  fact,
  taxa_fill = NULL,
  min_nb_seq = 0,
  na_remove = TRUE,
  numeric_fonction = sum,
  rarefy_after_merging = FALSE,
  rngseed = FALSE,
  verbose = TRUE,
  ...
)

Arguments

physeq

(required) a phyloseq-class object obtained using the phyloseq package.

fact

(required) Name of the factor to cluster samples by modalities. Need to be in physeq@sam_data.

taxa_fill

(default NULL) fill the ASV upset using a column in tax_table slot.

min_nb_seq

minimum number of sequences by OTUs by samples to take into count this OTUs in this sample. For example, if min_nb_seq=2,each value of 2 or less in the OTU table will not count in the venn diagram

na_remove

: if TRUE (the default), NA values in fact are removed if FALSE, NA values are set to "NA"

numeric_fonction

(default : sum) the function for numeric vector useful only for complex plot (see examples)

rarefy_after_merging

Rarefy each sample after merging by the modalities of fact parameter

rngseed

(Optional). A single integer value passed to phyloseq::rarefy_even_depth(), which is used to fix a seed for reproducibly random number generation (in this case, reproducibly random subsampling). If set to FALSE, then no fiddling with the RNG seed is performed, and it is up to the user to appropriately call set.seed beforehand to achieve reproducible results. Default is FALSE.

verbose

(logical). If TRUE, print additional information.

...

Additional arguments passed on to the ComplexUpset::upset()

Value

A ggplot2 plot

See also

ggvenn_pq()

Author

Adrien Taudière

Examples

if (requireNamespace("ComplexUpset") && packageVersion("ggplot2") < "4.0.0") {
  upset_pq(data_fungi_mini,
    fact = "Height", width_ratio = 0.2,
    taxa_fill = "Class"
  )
}
#> Loading required namespace: ComplexUpset
# \donttest{
if (requireNamespace("ComplexUpset") && packageVersion("ggplot2") < "4.0.0") {
  upset_pq(data_fungi_mini, fact = "Height", min_nb_seq = 1000)
  upset_pq(data_fungi_mini, fact = "Height", na_remove = FALSE)

  upset_pq(data_fungi_mini, fact = "Time", width_ratio = 0.2, rarefy_after_merging = TRUE)

  upset_pq(
    data_fungi_mini,
    fact = "Time",
    width_ratio = 0.2,
    annotations = list(
      "Sequences per ASV \n (log10)" = (
        ggplot(mapping = aes(y = log10(Abundance)))
        +
          geom_jitter(aes(
            color =
              Abundance
          ), na.rm = TRUE)
          +
          geom_violin(alpha = 0.5, na.rm = TRUE) +
          theme(legend.key.size = unit(0.2, "cm")) +
          theme(axis.text = element_text(size = 12))
      ),
      "ASV per phylum" = (
        ggplot(mapping = aes(fill = Phylum))
        +
          geom_bar() +
          ylab("ASV per phylum") +
          theme(legend.key.size = unit(0.2, "cm")) +
          theme(axis.text = element_text(size = 12))
      )
    )
  )

  upset_pq(
    data_fungi_mini,
    fact = "Time",
    width_ratio = 0.2,
    numeric_fonction = mean,
    annotations = list(
      "Sequences per ASV \n (log10)" = (
        ggplot(mapping = aes(y = log10(Abundance)))
        +
          geom_jitter(aes(
            color =
              Abundance
          ), na.rm = TRUE)
          +
          geom_violin(alpha = 0.5, na.rm = TRUE) +
          theme(legend.key.size = unit(0.2, "cm")) +
          theme(axis.text = element_text(size = 12))
      ),
      "ASV per phylum" = (
        ggplot(mapping = aes(fill = Phylum))
        +
          geom_bar() +
          ylab("ASV per phylum") +
          theme(legend.key.size = unit(0.2, "cm")) +
          theme(axis.text = element_text(size = 12))
      )
    )
  )

  upset_pq(
    subset_taxa(data_fungi_mini, Phylum == "Basidiomycota"),
    fact = "Time",
    width_ratio = 0.2,
    base_annotations = list(),
    annotations = list(
      "Sequences per ASV \n (log10)" = (
        ggplot(mapping = aes(y = log10(Abundance)))
        +
          geom_jitter(aes(
            color =
              Abundance
          ), na.rm = TRUE)
          +
          geom_violin(alpha = 0.5, na.rm = TRUE) +
          theme(legend.key.size = unit(0.2, "cm")) +
          theme(axis.text = element_text(size = 12))
      ),
      "ASV per phylum" = (
        ggplot(mapping = aes(fill = Class))
        +
          geom_bar() +
          ylab("ASV per Class") +
          theme(legend.key.size = unit(0.2, "cm")) +
          theme(axis.text = element_text(size = 12))
      )
    )
  )

  data_fungi2 <- data_fungi_mini
  data_fungi2@sam_data[["Time_0"]] <- data_fungi2@sam_data$Time == 0
  data_fungi2@sam_data[["Height__Time_0"]] <-
    paste0(data_fungi2@sam_data[["Height"]], "__", data_fungi2@sam_data[["Time_0"]])
  data_fungi2@sam_data[["Height__Time_0"]][grepl("NA", data_fungi2@sam_data[["Height__Time_0"]])] <-
    NA
  upset_pq(data_fungi2, fact = "Height__Time_0", width_ratio = 0.2, min_size = 2)
}
# }