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fix(profile-plot): Fix summaries for profile plots for protein turnover #196

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Merged
tonywu1999 merged 1 commit into from
Apr 14, 2026
Merged

fix(profile-plot): Fix summaries for profile plots for protein turnover #196

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11 changes: 7 additions & 4 deletions R/dataProcessPlots.R
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Original file line number Diff line number Diff line change
Expand Up @@ -291,14 +291,18 @@ dataProcessPlots = function(
ifelse(is_labeled_ref, "Reference", "Endogenous"),
levels = c("Reference", "Endogenous")
)]
raw_label_map = c("H" = "Reference", "L" = "Endogenous")
} else {
label_levels = levels(factor(processed$LABEL))
if (length(label_levels) == 2) {
processed[, LABEL := factor(LABEL, labels = c("Heavy", "Light"))]
raw_label_map = c("H" = "Heavy", "L" = "Light")
} else if ("L" %in% label_levels) {
processed[, LABEL := factor(LABEL, labels = c("Endogenous"))]
raw_label_map = c("L" = "Endogenous")
} else {
processed[, LABEL := factor(LABEL, labels = c("Heavy"))]
raw_label_map = c("H" = "Heavy")
}
}

Expand Down Expand Up @@ -362,7 +366,6 @@ dataProcessPlots = function(
RUN = unique(summarized$RUN))
summarized = merge(summarized, protein_by_run, by = c("Protein", "RUN"),
all.x = TRUE, all.y = TRUE)
summary_label = if ("Light" %in% levels(processed$LABEL)) "Light" else "Endogenous"
if(!isPlotly) {
savePlot(address, "ProfilePlot_wSummarization", width, height)
}
Expand All @@ -372,21 +375,21 @@ dataProcessPlots = function(
if (all(is.na(single_protein$ABUNDANCE))) {
next()
}

pept_feat = unique(single_protein[, list(PEPTIDE, FEATURE)])
counts = pept_feat[, list(N = .N), by = "PEPTIDE"]$N
s = rep(seq_along(counts), times = counts)
ss = unlist(lapply(counts, function(x) seq(1, x)), FALSE, FALSE)
groupNametemp = data.frame(groupName,
FEATURE = unique(single_protein$FEATURE)[1],
analysis = "Run summary")

single_protein_summ = summarized[Protein == all_proteins[i], ]
quant = single_protein_summ[
Protein == all_proteins[i],
list(PROTEIN = unique(Protein), PEPTIDE = "Run summary",
TRANSITION = "Run summary", FEATURE = "Run summary",
LABEL = summary_label, RUN = RUN,
LABEL = raw_label_map[LABEL], RUN = RUN,
ABUNDANCE = LogIntensities, FRACTION = 1,
UPPERBOUND = if("Variance" %in% names(.SD)) LogIntensities + 1.96 * sqrt(Variance) else NA_real_, # 95% confidence interval
LOWERBOUND = if("Variance" %in% names(.SD)) LogIntensities - 1.96 * sqrt(Variance) else NA_real_
Expand Down
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