protein_quant: Protein Quantification

In pmartR: Panomics Marketplace - Quality Control and Statistical Analysis for Panomics Data

Protein Quantification

Description

This function takes in a pepData object, method (quantification method, mean, median or rrollup), and the optional argument isoformRes (defaults to NULL). An object of the class 'proData' is returned.

Usage

protein_quant(
  pepData,
  method,
  isoformRes = NULL,
  qrollup_thresh = NULL,
  single_pep = FALSE,
  single_observation = FALSE,
  combine_fn = "median",
  parallel = TRUE,
  emeta_cols = NULL,
  emeta_cols_sep = ";"
)

Arguments

pepData	an omicsData object of the class 'pepData'
method	character string specifying one of four protein quantification methods, 'rollup', 'rrollup', 'qrollup' and 'zrollup'
isoformRes	list of data frames, the result of applying the 'bpquant' function to original pepData object. Defaults to NULL.
qrollup_thresh	numeric value; is the peptide abundance cutoff value. Is an argument to qrollup function.
single_pep	logical indicating whether or not to remove proteins that have just a single peptide mapping to them, defaults to FALSE.
single_observation	logical indicating whether or not to remove peptides that have just a single observation, defaults to FALSE.
combine_fn	character string specifying either be 'mean', 'median', or 'sum'. Using 'sum' is only supported when method is 'rollup'.
parallel	logical indicating whether or not to use "doParallel" loop in applying rollup functions. Defaults to TRUE. Is an argument of rrollup, qrollup and zrollup functions.
emeta_cols	character vector indicating additional columns of e_meta that should be kept after rolling up to the protein level. The default, NULL, only keeps the column containing the mapping variable along with the new columns created (peps_per_pro and n_peps_used).
emeta_cols_sep	character specifying the string that will separate the elements for emeta_cols when they are collapsed into a single row when aggregating rows belonging to the same protein. Defaults to ";"

Details

If isoformRes is provided then, a temporary pepData object is formed using the isoformRes information as the e_meta component and the original pepData object will be used for e_data and f_data components. The emeta_cname for the temporary pepData object will be the 'protein_isoform' column of isoformRes. Then one of the three 'method' functions can be applied to the temporary pepData object to return a proData object. If isofromRes is left NULL, then depending on the input for 'method', the correct 'method' function is applied directly to the input pepData object and a proData object is returned.

Value

omicsData object of the class 'proData'

References

Webb-Robertson, B.-J. M., Matzke, M. M., Datta, S., Payne, S. H., Kang, J., Bramer, L. M., ... Waters, K. M. (2014). Bayesian Proteoform Modeling Improves Protein Quantification of Global Proteomic Measurements. Molecular & Cellular Proteomics.: MCP, 13(12), 3639-3646.

Examples

library(pmartRdata)

mypepData <- group_designation(omicsData = pep_object, main_effects = c("Phenotype"))
mypepData = edata_transform(omicsData = mypepData, "log2")

imdanova_Filt <- imdanova_filter(omicsData = mypepData)
mypepData <- applyFilt(filter_object = imdanova_Filt, omicsData = mypepData, min_nonmiss_anova = 2)

imd_anova_res <- imd_anova(omicsData = mypepData, test_method = 'comb',
                           pval_adjust_a_multcomp = 'bon', pval_adjust_g_multcomp = 'bon')

isoformRes = bpquant(statRes = imd_anova_res, pepData = mypepData)

# case where isoformRes is NULL:
results <- protein_quant(pepData = mypepData, method = 'rollup',
                         combine_fn = 'median', isoformRes = NULL)

# case where isoformRes is provided:
# results2 = protein_quant(pepData = mypepData, method = 'rollup',
#                           combine_fn = 'mean', isoformRes = isoformRes)

pmartR documentation built on June 10, 2025, 9:10 a.m.