Applies BP-Quant to a pepData object

bpquant(statRes, pepData, pi_not = 0.9, max_proteoforms = 5, parallel = TRUE)

Arguments

statRes

an object of the class 'statRes'

pepData

an omicsData object of the class 'pepData' that includes the e_meta component

pi_not

numeric value between 0 and 1 indicating the background probability/frequency of a zero signature

max_proteoforms

a numeric value corresponding to the maximum threshold for the number of possible proteoforms

parallel

a logical indicator of whether the calculation will be parallelized

Value

a list of data frames, one for each unique protein. The data frames have three columns, a protein identifier, a peptide identifier, and a "ProteoformID". The class of this list is 'isoformRes'.

Details

The result of this function can be used as one the isoformRes input argument to protein_quant. The bpquant function itself operates as follows: The statRes object contains the signatures data frame, the pepData object is used for its e_meta data frame. Next the signatures data frame and e_meta are merged by their edata_cname (e.g. peptide identifier) columns, this new data frame called protein_sig_data will be input to bpquant_mod in a “foreach” statement. “Foreach” will subset protein_sig_data for each unique protein and apply bpquant_mod to each subset and store the results.

Examples

# \donttest{
library(pmartRdata)

mypepData <- group_designation(
  omicsData = pep_object,
  main_effects = c("Phenotype")
)
mypepData = edata_transform(omicsData = mypepData, data_scale = "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 = 'combined',
  pval_adjust_a_multcomp = 'bon',
  pval_adjust_g_multcomp = 'bon'
)

result = bpquant(statRes = imd_anova_res, pepData = mypepData)
# }