R/edge.effect.R

In BozemanDiseaseLab/BKA.PREEMPT: What the Package Does (One Line, Title Case)

#edge.effects  nerd

col <- c('col_1','col_12')
row <-  c('A', 'H')


bka.merge <- bka.merge %>%
  mutate(row.edge = ifelse(which_row %in% row, 3, 1)) %>%
  mutate(column.edge = ifelse(column %in% col, 3, 1)) %>%
  mutate(edge.sum = row.edge + column.edge) %>%
  mutate(edge.prod = row.edge*column.edge)

bka.merge %>%
  unite(well, c(which_row, column)) %>%
  ggplot(aes(x=time, y= (as.numeric(measure)))) +
  geom_point(aes(group = well, col = edge.sum)) +
  geom_line(aes(group = well, col = edge.sum)) +
  facet_grid(~sample)

bka.merge %>%
  unite(well, c(which_row, column)) %>%
  ggplot(aes(x=time, y= (as.numeric(measure)))) +
  geom_point(aes(group = well, col = edge.prod)) +
  geom_line(aes(group = well, col = edge.prod)) +
  facet_grid(~sample)

bka.merge %>%
  unite(well, c(which_row, column)) %>%
  ggplot(aes(x=time, y= (as.numeric(measure)))) +
  geom_point(aes(group = well)) +
  geom_line(aes(group = well)) +
  facet_grid(~sample)


data %>%
  unite(well, c(which_row, column)) %>%
  filter(sample != 'Blank') %>%
  ggplot() + theme_bw() +
  geom_line(aes(x=time, y= as.numeric(measure), group = well)) +
  scale_y_continuous(0,3)+ facet_wrap(~sample)  + 
  scale_color_gradient(low="red", high="blue")

data %>%
  unite(well, c(which_row, column)) %>%
  filter(sample != 'Blank') %>%
  ggplot() + theme_bw() +
  geom_line(aes(x=time, y= log(as.numeric(measure)), group = well)) +
  scale_y_continuous(0,3)+ facet_wrap(~sample)  + 
  scale_color_gradient(low="red", high="blue")






# old bka dat that had edge effect problem ? different template
data2 <- read_excel("data/Exp_014_E.coli_BKA_2.5.19.xlsx")
data2$which_bat <-  rep(1:2, each=4, length.out=nrow(data2))
data2$edge.specific <- c(1,2,3,4,4,3,2,1)
colnames(data2)[(3:14)] <-  (c(c(1:6),c(6.001,5.001,4.001,3.001,2.001,1.001)))
data2$which_row <- LETTERS[1:8]

data2.tidy <- data2  %>%
  gather(variable, measurement, 3:14) %>%
  mutate(product =  edge.specific *as.numeric (variable) ) %>%
  select(-c(deg)) %>%
  group_by(Tme, which_row)  %>%
  mutate(tme2 =  rep (c(1:12), each = 9)) # change back to 8 if doesnt work

wells <- readxl::read_excel( 'data/soft_max_template.xlsx', col_names = FALSE, sheet = 2)
colnames(wells) <- c("col_1", "col_2", "col_3","col_4","col_5","col_6","col_7","col_8","col_9","col_10","col_11","col_12")
wells$which_row <- NA
wells$which_row[1:8] <- LETTERS[1:8]

wells.tidy <- wells[1:8,] %>%
  group_by(which_row)  %>%
  gather(key=column, value = sample, 1:12)

data.tidy.join <- full_join(data2.tidy, wells.tidy)

data.tidy.join %>%
  ggplot() + theme_bw() +
  geom_point(aes(y= measurement, x= tme2, group = sample, col = (product) )) +
  scale_color_gradient(low="red", high="blue")