Description Usage Arguments Value References Examples
Calculate beta diversities of your tidy_micro set. This function reformats the data into the original OTU table and then feeds that into the vegdist function
1 |
micro_set |
A tidy_micro data set |
table |
Table you'd like to use when calculating alpha diversity. Your lowest level is recommended |
method |
A dissimilarity method compatible with |
A symmetrix distance matrix
vegdist
1 2 3 4 5 6 7 8 9 10 11 12 | data(bpd_phy); data(bpd_cla); data(bpd_ord); data(bpd_fam); data(bpd_clin)
otu_tabs <- list(Phylum = bpd_phy, Class = bpd_cla,
Order = bpd_ord, Family = bpd_fam)
set <- tidy_micro(otu_tabs = otu_tabs, clinical = bpd_clin) %>%
filter(day == 7) ## Only including the first week
## Bray-Curtis beta diversity
bray <- set %>% beta_div(table = "Family")
## Morisita-Horn beta diversity
horn <- set %>% beta_div(table = "Family", method = "horn")
|
Loading required package: tidyverse
── Attaching packages ─────────────────────────────────────── tidyverse 1.3.0 ──
✔ ggplot2 3.3.2 ✔ purrr 0.3.4
✔ tibble 3.0.4 ✔ dplyr 1.0.2
✔ tidyr 1.1.2 ✔ stringr 1.4.0
✔ readr 1.4.0 ✔ forcats 0.5.0
── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
✖ dplyr::filter() masks stats::filter()
✖ dplyr::lag() masks stats::lag()
Contains 74 libraries from OTU files.
Summary of sequencing depth:
Min. 1st Qu. Median Mean 3rd Qu. Max.
8851 24938 33314 36650 43590 97408
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