```{r heatmap-plot, out.width='80%', fig.align='center', fig.height= 4, fig.width=4, fig.dpi = 300, fig.cap="Spatial variability across the plates", out.extra='frontpage'} # import the dataset data_6P <- read_csv("data/tidydata/data_6P_cal_3nd.csv") # select the colmuns needed data_selected <- data_6P %>% filter(Sample != "C+" & Sample != "C-") %>% # remove the control samples select(Plate, Row, Col, Time, HE) %>% rename(Column = Col) %>% filter(Time == 0 | Time == 120 | Time == 240 | Time == 360 | Time == 1440 |Time == 1800) %>% mutate_each(funs(replace(., .<0, 0))) # replace the negtive values by 0 # plot at time 1800min ### filter the time points data_t0 <- data_selected %>% filter(Time == 360) %>% filter(!(Column == 7 & Row == "F" & Plate == 6)) %>% # remove an "outlier" filter(!(Column == 1 & Row == "F" & Plate == 1)) %>% # remove an "outlier" filter(!(Column == 9 & Row == "H" & Plate == 6)) # remove an "outlier" ### plotting data_t0 %>% ggplot(aes(x = Column, y = Row, fill = HE)) + scale_fill_continuous(name = "Hydrolysis extent", type = "viridis") + scale_x_continuous(breaks = c(1, 3, 5, 7, 9, 11)) + theme(axis.ticks = element_blank(), axis.text = element_text(color = "black"), panel.grid = element_blank(), panel.background = element_blank(), legend.position = "bottom", legend.key.size = unit(0.15, "cm"), legend.key.width = unit(0.8, "cm"), legend.title.align = 0.5, legend.text = element_text(size = 7), legend.title = element_text(size = 9), axis.text.x = element_text(color="black", size=7), axis.text.y = element_text(color="black", size=7)) + geom_tile(color = "white", size = 0.1) + facet_wrap(~Plate) + theme(strip.background = element_blank()) ```
The heatmap is to explore the spatial variability across the plates at different time points, and also to find potential outliers. For example the figure above shows the hydrolysis extent of the first six plates at 360 minutes. The white blocks are the empty samples, missing values and very few outliers. As we can see here, the color are randomly distributed, no patterns can be found, which is good. The plate 3 and 6 tend to have higher intensity than the others, whether it's due to the variation of the experimental conditions (temperature, enzymatic activity...) or the difference between samples need to be checked later on.

```{r standard-plot, out.width='80%', fig.align='center', fig.height= 4, fig.width=4, fig.dpi = 300, fig.cap="Experimental results of the starch degradability"} # import the dataset and add a new colume # this new column will help us do the plot hydro <- read_csv("data/tidydata/data_6P_cal_3nd.csv")%>% mutate(status = case_when( ## creat a new column to classify three different conditions Sample == "C+" ~ "Positive control", ## if the sample name is C+, give it pos_control Sample == "C-" ~ "Negative control", ## if the sample name is C-, give it neg_control TRUE ~ "Sample" ## if it's not the cases above, give it other )) # creat a new column to distingrish each sample hydro <- hydro %>% mutate(Well = paste(Plate, Row, Col, sep = "_")) # remove the outlier at 20min in plate 1 ## find the outlier first find_max <- hydro %>% filter(Time == 20) %>% arrange(desc(HE)) ## remove it hydro_no_outlier <- hydro %>% filter(!(Time == 20 & Well == "1_C_11")) # plotting the hydrolysis extent overtime ggplot(data = hydro_no_outlier, aes(x = Time, y = HE, group = Well, color = status)) + geom_point(size = 1, shape = 1) + ## use hollow circles by "shape = 1" geom_line(size = 0.05) + # make the line thinner scale_color_manual(values = c("#e41a1c", "#4daf4a", "#377eb8")) + scale_y_continuous(limits = c(0,100), expand = c(0, 0)) + ## set the range of the y axis with no more expand scale_x_continuous(breaks = c(500, 1500), limits = c(0, 1900), expand = c(0, 0)) + ylab("Hydrolysis extent (%)") + ## change the label for the y axis xlab("Time (min)") + ## change the name of the x axis theme(legend.title = element_blank(), panel.grid = element_blank(), axis.line = element_line(colour = "black", size = 0.5), panel.background = element_blank(), axis.ticks=element_line(colour="black", size=.5)) + labs(x = "Time (min)", y = "Hydrolysis extent (%)") + theme(axis.text.x = element_text(color="black", size=7), axis.text.y = element_text(color="black", size=7)) + theme(legend.key = element_blank(), legend.position = "bottom") + theme(plot.margin = unit(c(5.5,12,5.5,5.5), "pt")) + ## set the margin facet_wrap(~ Plate) + theme(strip.background = element_blank()) ```

```{r fitted-HE-plot, out.width='80%', fig.align='center', fig.height= 4, fig.width = 4, fig.dpi = 300, fig.cap="Fitted results of the starch degradability"} # read in the fitted hydrolysis extent dataset fitted_HE <- read_csv("analysis/fitted_HE.csv") %>% select(h, k, Xinf, fitted_HE) # combine this dataset with the previous dataset total_data <- bind_cols(hydro, fitted_HE) %>% filter(!(Time == 20 & Well == "1_C_11")) # remember to remove this outlier # creat another data frame with expanded rows selected <- total_data %>% select(status, Well, h, k, Xinf) %>% unique() # remove the repeated rows # repeat each row 1801 times expanded <- selected[rep(seq_len(nrow(selected)), each = 1801), ] Time <- c(0:1800) x <- expanded %>% mutate(Time = rep(Time, times = 283)) %>% mutate(fitted_HE = Xinf*(1-exp(-k*Time**(1-h)))) # plotting ggplot() + geom_point(data = total_data, aes(x = Time, y = HE, group = Well, color = status), size = 1, shape = 1) + ## use hollow circles by "shape = 1" geom_line(data = x, aes(x = Time, y = fitted_HE, group = Well, color = status), size = 0.05) + # make the line thinner #if we want to add transparancy to the Samples (try the lines below) #geom_line(data = x, #aes(x = Time, # y = fitted_HE, #group = Well, #color = status, # alpha = status == "Sample"), #size = 0.05) + scale_alpha_manual(values = c(1, 0.1)) + # c(FALSE, TRUE) scale_color_manual(values = c("#e41a1c", "#4daf4a", "#377eb8")) + scale_y_continuous(limits = c(0,100), expand = c(0, 0)) + ## set the range of the y axis with no more expand scale_x_continuous(breaks = c(500, 1500), limits = c(0, 1900), expand = c(0, 0)) + ylab("Hydrolysis extent (%)") + ## change the label for the y axis xlab("Time (min)") + ## change the name of the x axis theme(legend.title = element_blank(), panel.grid = element_blank(), axis.line = element_line(colour = "black", size = 0.5), panel.background = element_blank(), axis.ticks=element_line(colour="black", size=.5)) + labs(x = "Time (min)", y = "Hydrolysis extent (%)") + theme(axis.text.x = element_text(color="black", size=7), axis.text.y = element_text(color="black", size=7)) + theme(legend.key = element_blank(), legend.position = "bottom") + theme(plot.margin = unit(c(5.5,12,5.5,5.5), "pt")) + ## set the margin facet_wrap(~ Plate) + theme(strip.background = element_blank()) ```