Allow pmartR to accept e_meta with duplicate edata_cname and emeta_cname pairings

[rarichardson92]

This fix will allow pmartR to handle output from e_meta files aggregated over multiple samples that may have had different libraries for protein matching.

Need to update documentation to reflect fix also.

Additionally, if this is done so as to: 1) remove the requirement from preflight and 2) pull only unique pairing in edata_cname and emeta_cname at the point of use (bpquant and protein_quant), I think this chunk from the protein_quant example code should run without error:

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 provided:
results = protein_quant(pepData = mypepData, method = 'rollup',
                          combine_fn = 'mean', isoformRes = isoformRes)

In summary - we want object construction to allow edata_cname + emeta_cname duplicates in e_meta, and make protein_quant/bpquant only use unique pairings when doing rollup.

[evanglass]

Experimental support for it in the protein_quant function only (no isoformRes) is now available in protein_quant-combine_dups branch.

Example code:

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

# Split up ProteinList into multiple rows (they should be joined back together by protein_quant)
mypepData$e_meta <- mypepData$e_meta %>%
    dplyr::mutate(ProteinList = strsplit(ProteinList, ";")) %>%
    tidyr::unnest(ProteinList) %>%
    data.frame(check.names = FALSE)	
attr(mypepData, "cnames")$emeta_cname <- "ProteinList"

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')

results <- protein_quant(pepData = mypepData, method = 'rollup', combine_fn = 'median', parallel = FALSE, emeta_cols = "RazorProtein")