mp_balance_clade-methods: Calculating the balance score of internal nodes (clade)...

mp_balance_cladeR Documentation

Calculating the balance score of internal nodes (clade) according to the geometric.mean/mean/median abundance of their binary children tips.

Description

Calculating the balance score of internal nodes (clade) according to the geometric.mean/mean/median abundance of their binary children tips.

Usage

mp_balance_clade(
  .data,
  .abundance = NULL,
  force = FALSE,
  relative = TRUE,
  balance_fun = c("geometric.mean", "mean", "median"),
  pseudonum = 0.001,
  action = "get",
  ...
)

## S4 method for signature 'MPSE'
mp_balance_clade(
  .data,
  .abundance = NULL,
  force = FALSE,
  relative = TRUE,
  balance_fun = c("geometric.mean", "mean", "median"),
  pseudonum = 0.001,
  action = "get",
  ...
)

## S4 method for signature 'tbl_mpse'
mp_balance_clade(
  .data,
  .abundance = NULL,
  force = FALSE,
  relative = TRUE,
  balance_fun = c("geometric.mean", "mean", "median"),
  pseudonum = 0.001,
  action = "get",
  ...
)

## S4 method for signature 'grouped_df_mpse'
mp_balance_clade(
  .data,
  .abundance = NULL,
  force = FALSE,
  relative = TRUE,
  balance_fun = c("geometric.mean", "mean", "median"),
  pseudonum = 0.001,
  action = "get",
  ...
)

Arguments

.data

MPSE object which must contain otutree slot, required

.abundance

the column names of abundance.

force

logical whether calculate the (relative) abundance forcibly when the abundance is not be rarefied, default is FALSE.

relative

logical whether calculate the relative abundance.

balance_fun

function the method to calculate the (relative) abundance of internal nodes according to their children tips, default is 'geometric.mean', other options are 'mean' and 'median'.

pseudonum

numeric add a pseudo numeric to avoid the error of division in calculation, default is 0.001 .

action

character, "add" joins the new information to the otutree slot if it exists (default). In addition, "only" return a non-redundant tibble with the just new information. "get" return a new 'MPSE' object, and the 'OTU' column is the internal nodes and 'Abundance' column is the balance scores.

...

additional parameters, meaningless now.

Value

a object according to 'action' argument.

References

Morton JT, Sanders J, Quinn RA, McDonald D, Gonzalez A, Vázquez-Baeza Y, Navas-Molina JA, Song SJ, Metcalf JL, Hyde ER, Lladser M, Dorrestein PC, Knight R. 2017. Balance trees reveal microbial niche differentiation. mSystems 2:e00162-16. https://doi.org/10.1128/mSystems.00162-16.

Justin D Silverman, Alex D Washburne, Sayan Mukherjee, Lawrence A David. A phylogenetic transform enhances analysis of compositional microbiota data. eLife 2017;6:e21887. https://doi.org/10.7554/eLife.21887.001.

Examples

## Not run: 
  suppressPackageStartupMessages(library(curatedMetagenomicData))
  xx <- curatedMetagenomicData('ZellerG_2014.relative_abundance', dryrun=F)
  xx[[1]] %>% as.mpse -> mpse
  mpse.balance.clade <- mpse %>%
    mp_balance_clade(
      .abundance = Abundance,
      force = TRUE,
      relative = FALSE,
      action = 'get',
      pseudonum = .01
    )
  mpse.balance.clade 

  # Performing the Euclidean distance or PCA.

  mpse.balance.clade %>%
    mp_cal_dist(.abundance = Abundance, distmethod = 'euclidean') %>%
    mp_plot_dist(.distmethod = 'euclidean', .group = disease, group.test = T)

  mpse.balance.clade %>%
    mp_adonis(.abundance = Abundance, .formula=~disease, distmethod = 'euclidean', permutation = 9999)

  mpse.balance.clade %>%
    mp_cal_pca(.abundance = Abundance) %>% 
    mp_plot_ord(.group = disease)

  # Detecting the signal balance nodes.
  mpse.balance.clade %>% mp_diff_analysis(
      .abundance = Abundance,
      force = TRUE,
      relative = FALSE,
      .group = disease,
      fc.method = 'compare_mean'
  )

## End(Not run)

YuLab-SMU/MicrobiotaProcess documentation built on Nov. 8, 2024, 4:37 p.m.