Merge pull request #1 from DOH-HNH0303/rough_plot

adding rough script plot

bin/plot.R

@@ -0,0 +1,61 @@
+library(tidyverse)
+library(broom)
+
+# load dataframe
+df <- read_csv("summary.csv") %>%
+  mutate(y = 100*n/length)
+
+mash <- read_csv("mash.csv") %>%
+  rename(sample=1,
+        ani = 2,
+        rep=3,
+        dist=4)%>%
+  mutate(x=100*(1-dist)) %>%
+  select(sample, ani, rep, x)
+
+df <- left_join(df, mash, by = c("sample","ani","rep")) %>%
+  unique()
+
+p <- ggplot(df, aes(x=100*ani, y=x))+
+  geom_point()+
+  labs(x="Actual ANI", y = "Estimated ANI (Mash)")+
+  theme_bw()
+ggsave(plot = p, filename = "ani_act-vs-est.jpg", dpi = 300, width = 5, height = 4)
+
+p <- df %>%
+  mutate(diff = 100*ani-x) %>%
+  ggplot(aes(x=ani, y=diff))+
+  geom_point()+
+  labs(x="Actual ANI", y = "Difference (Actual ANI - Estimated ANI)")+
+  theme_bw()
+ggsave(plot = p, filename = "ani_diff.jpg", dpi = 300, width = 5, height = 4)
+
+
+
+# https://douglas-watson.github.io/post/2018-09_exponential_curve_fitting/      
+fit <- nls(y ~ SSasymp(x, yf, y0, log_alpha), data = df)
+summary(fit)
+
+df.fitted <- augment(fit, newdata = data.frame(x=seq(from=80, to=100, by = 0.0001)))
+
+df.fitted %>%
+  filter(x == 80 | x == 85 | x == 90 | x == 95) %>%
+  rename(ANI=1,
+         Predicted_Amb=2)
+
+threshold <- df.fitted %>%
+  filter( abs(`.fitted`) == min(abs(`.fitted`))) %>%
+  filter( x == max(x)) %>%
+  .$x
+
+cat(paste0("Threshold @ 0: ",threshold, sep = "\n"))
+
+p <- ggplot(data = augment(fit), aes(x=x, y=y))+
+  geom_point()+
+  geom_line(data = df.fitted, aes(x=x, y=.fitted))+
+  geom_vline(xintercept = threshold, linetype="dashed", color = "red")+
+  theme_bw()+
+  labs(x="Sample-Reference % ANI", y = "% Ambiguous Bases (N) in Consensus")
+ggsave(plot = p, filename = "nls.jpg", dpi = 300, width = 5, height = 4)
+
+