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investigate_data <- tibble(rtime = rtime(xcms_p_POS_g_r_g, adjusted = FALSE, bySample = TRUE),
adjustedRtime = rtime(xcms_p_POS_g_r_g, adjusted = TRUE, bySample = TRUE),
file = basename(fileNames(xcms_p_POS_g_r_g))
unnest(c(rtime, adjustedRtime)) %>%
mutate(diff = adjustedRtime - rtime)
filter(abs(adjustedRtime-250)<1) %>% # <-- focus on a small RT range where the outlier is clear
arrange(diff) %>% # <-- use desc if looking for a positive difference
arrange(diff) # <-- use desc if looking for a positive difference
missing = 200
extra = 100
xset1in the console it should tell you if there are any groups.
xset2 <- retcor(xset1, family= "s", plottype= "m", missing=1, extra=1,as when you do