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subChar_twoGroup

Source: R/subChar_twoGroup.R
subChar_twoGroup.Rd

This function conducts subgroup lipid characteristic analysis for two-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_twoGroup(
  processed_se,
  char,
  subChar,
  ref_group,
  test = c("t-test", "Wilcoxon test"),
  significant = c("pval", "padj"),
  p_cutoff = 0.05,
  FC_cutoff = 1,
  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'.

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.

test

A character string indicating which method to be used for comparing means. Allowed method include "t-test" and "Wilcoxon test". Default is 't-test'.

significant

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

p_cutoff

Numeric. Significant level. Default is 0.05.

FC_cutoff

Numeric. Significance of the fold-change. Default is 1.

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("de_data_twoGroup")
processed_se <- data_process(
    de_data_twoGroup, exclude_missing=TRUE, exclude_missing_pct=70,
    replace_na_method='min', replace_na_method_ref=0.5,
    normalization='Percentage', transform='log10')
subChar_se <- subChar_twoGroup(processed_se, char="Total.C", subChar="class",
    ref_group="ctrl", test='t-test', significant="pval", p_cutoff=0.05,
    FC_cutoff=1, transform='log10')
#> There are 4 ratio characteristics that can be converted in your dataset.