https://i-doctor.sakura.ne.jp/font/?p=41472

190929_elisa_001.Rmd

---
title: "R Notebook"
output: html_notebook
---

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```{r}
library(drc)
library(nplr)
library(tidyverse)

library("RCurl")
getURL("https://raw.githubusercontent.com/Razumall/NOPS/master/Data/ELISA.csv") %>%
  read.csv(text = ., header = TRUE) %>%
  tbl_df() -> df
```
```{r}
df %>%
  mutate_all(funs(. - as.numeric((df[8,1]+df[8,2])/2 ))) -> df2
```

```{r}
df2 %>%
  dplyr::select(X1, X2) %>%
  mutate(Concentration = c(1000*0.5^(0:6), 0)) %>%
  gather(Column, Absorbance, -Concentration) %>%
  filter(Concentration!=0) %>%
  dplyr::select(-Column) -> Standard
```

```{r}
ggplot(Standard, aes(x=Concentration, y=Absorbance))+
  geom_point()+
  scale_x_log10()
```

```{r}
library(nplr)
nplr <- nplr( x = Standard$Concentration,
        y = Standard$Absorbance )
nplr
```

```{r}
plot( nplr,
      xlab="Concenttration",
      ylab="Absorbance")
```

```{r}
df2 %>%
  dplyr::select(-c(X1, X2)) %>%
  gather(Column, Absorbance) %>%
  mutate(Sample = c(rep(1:8, 2), rep(9:16, 2), rep(17:24, 2), rep(25:32, 2), rep(33:40, 2)) ) %>%
  mutate(Sample = as.factor(Sample)) %>%
  group_by(Sample) %>%
  summarise(Mean = mean(Absorbance), SD = sd(Absorbance)) -> Measured
```

```{r}
Measured %>%
  filter(Mean > 0) -> Measured2

getEstimates(nplr, Measured2$Mean) %>%
  tbl_df() %>%
  dplyr::rename(Absorbance=y, Concentration=x) -> Estimates_nplr

# kable(Estimates_nplr %>% head(), align="c")
```


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