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subChar_multiGroup

Source: R/subChar_multiGroup.R
subChar_multiGroup.Rd

This function conducts subgroup lipid characteristic analysis for multi-group data. Lipid species are categorized and summarized into a new lipid abundance table according to two selected lipid characteristics, followed by differential expression analysis. The two chosen characteristics should be either both continuous data or one continuous and one categorical data.

Usage

subChar_multiGroup(
  processed_se,
  char,
  subChar,
  ref_group,
  post_hoc = c("One-way ANOVA", "Kruskal–Wallis test"),
  post_hoc_sig = c("pval", "padj"),
  post_hoc_p_cutoff = 0.05,
  transform = c("none", "log10", "square", "cube")
)

Arguments

processed_se

A SummarizedExperiment object constructed by as_summarized_experiment and processed by data_process.

char

Character. A lipid characteristic selected from the common list returned by list_lipid_char. Allowed lipid characteristics include 'Total.C', 'Total.DB', 'Total.OH', 'FA.C', 'FA.DB', and 'FA.OH'. Selected characteristics must be one of 'Total.C', 'Total.DB', 'Total.OH', 'FA.C', 'FA.DB', or 'FA.OH'.

subChar

Character. A lipid characteristic selected from the common list returned by list_lipid_char. Must be differ from 'char'.

ref_group

Character. Group name of the reference group. It must be one of the group names in the group information table's group column.

post_hoc

Character. The method to statistic calculation. Allowed method include "One-way ANOVA" and "Kruskal–Wallis test". Default is 'One-way ANOVA'.

post_hoc_sig

Character. The p-value to be used for the statistically significant. Must be one of "pval" or "padj". Default is 'pval'.

post_hoc_p_cutoff

Numeric. Significant level. Default is 0.05.

transform

Character. Method for data transformation. Allowed methods include "none", "log10", "square", "cube". Select 'none' to skip data transformation. Default is 'log10'.

Value

Return a SummarizedExperiment object containing analysis results.

Examples

data("se_multiGroup")
processed_se <- data_process(
    se=se_multiGroup, exclude_missing=TRUE, exclude_missing_pct=70,
    replace_na_method='min', replace_na_method_ref=0.5,
    normalization='Percentage', transform='log10')
subChar_se <- subChar_multiGroup(
    processed_se, char='Total.C', subChar='class', ref_group='ctrl',
    post_hoc='One-way ANOVA', post_hoc_sig='pval', post_hoc_p_cutoff=0.05,
    transform='log10')
#> There are 4 ratio characteristics that can be converted in your dataset.