Correlations between hemagglutination inhibition (HI) and viral neutralization (VN) titers and plasmablast and plasma B cells among trivalent inactivated influenza vaccine (TIV) vaccinees.
This reports reproduces Figure 2 of Cao RG et al(2014) published as part of the original study.
First, we initialize the connection to SDY144 using CreateConnection.
We grab the datasets of interests with the getDataset method.
flow <- con$getDataset("fcs_analyzed_result")
hai <- con$getDataset("hai")
vn <- con$getDataset("neut_ab_titer")Then, we select the cell populations and time points of intereset.
pb <- flow[population_name_reported %in% c("Plasma cells,Freq. of,B lym CD27+",
"Plasmablast,Freq. of,Q3: CD19+, CD20-")]
pb <- pb[, population_cell_number := as.numeric(population_cell_number)]
pb <- pb[study_time_collected == 7 & study_time_collected_unit == "Days"] # 13 subjects
pb <- pb[, list(participant_id, population_cell_number, population_name_reported)]We compute the HI and VN titer as the fold-increase between baseline and day 30.
# HAI
hai <- hai[, response := value_preferred / value_preferred[study_time_collected == 0],
by = "virus,cohort,participant_id"][study_time_collected == 30]
hai <- hai[, list(participant_id, virus, response)]
dat_hai <- merge(hai, pb, by = "participant_id", allow.cartesian = TRUE)
# VN
vn <- vn[, response:= value_preferred/value_preferred[study_time_collected == 0],
by = "virus,cohort,participant_id"][study_time_collected == 30]
vn <- vn[, list(participant_id, virus, response)]
dat_vn <- merge(vn, pb, by = "participant_id", allow.cartesian = TRUE)ggplot2Correlation between the absolute number of plasmablasts and plasma B cells 7 days after vaccination with and fold-increase of HI titers from baseline to day 30 after vaccination.
ggplot(dat_hai, aes(x = population_cell_number, y = response)) +
geom_point() +
geom_smooth(method = "lm") +
facet_grid(virus ~ population_name_reported, scale = "free") +
xlab("Number of cells") +
ylab("HI fold-increase Day 30 vs. baseline") +
theme_IS()Correlation between the absolute number of plasmablasts and plasma B cells 7 days after vaccination with and fold-increase of VN titers from baseline to day 30 after vaccination.
ggplot(dat_vn, aes(x = population_cell_number, y = response)) +
geom_point() +
geom_smooth(method = "lm") +
facet_grid(virus ~ population_name_reported, scale = "free") +
xlab("Number of cells") +
ylab("VN fold-increase Day 30 vs. baseline") +
theme_IS()