diff --git a/Doc_BioassayLinReport.Rmd b/Doc_BioassayLinReport.Rmd index 6f058cf..50b3b75 100644 --- a/Doc_BioassayLinReport.Rmd +++ b/Doc_BioassayLinReport.Rmd @@ -90,198 +90,199 @@ You can also embed plots, for example: ```{r XLplot, echo=FALSE, warning=FALSE, fig.height=4, fig.width=6, fig.cap="Plot of models", fig.align='left'} -plot_f <- function(dat, sigmoid,det_sig) { - CORdat <- cor(dat[,1],dat[,ncol(dat)]) +# plot_f <- function(dat, sigmoid,det_sig) { +# CORdat <- cor(dat[,1],dat[,ncol(dat)]) +# +# all_l <- melt(data.frame(dat), id.vars="log_dose", variable.name="replname", value.name = "readout") +# isRef <- rep(c(1,0),1,each=nrow(all_l)/2) +# isSample <- rep(c(0,1),1,each=nrow(all_l)/2) +# all_l2 <- cbind(all_l, isRef, isSample) +# +# if(is.null(det_sig)) { +# if (CORdat<0) { +# startlist <- list(a=sigmoid[3], b=-sigmoid[5],cs=sigmoid[7], +# d=sigmoid[1],r=sigmoid[8]) +# } else { +# startlist <- list(a=sigmoid[3],b=sigmoid[5],cs=sigmoid[7], +# d=sigmoid[1],r=sigmoid[8]) +# } +# } else { +# startlist <- list(a=det_sig[5], b=det_sig[1],cs=det_sig[7], +# d=det_sig[3],r=det_sig[7] - det_sig[8]) +# } +# #browser() +# tryCatch({ +# mr <- gsl_nls(fn = readout ~ a+(d-a)/(1+exp(b*(log_dose-(cs-r*isSample)))), +# data=all_l2, +# start=startlist, +# control=gsl_nls_control(xtol=1e-6,ftol=1e-6, gtol=1e-6)) +# }, +# error = function(err) { +# err$message +# }) +# s_mr <- summary(mr) +# a <- s_mr$coefficients[1,1] +# b <- s_mr$coefficients[2,1] +# cs <- s_mr$coefficients[3,1] +# d <- s_mr$coefficients[4,1] +# r <- s_mr$coefficients[5,1] +# +# log_dose <- unique(all_l$log_dose) +# seq_x <- seq(min(log_dose),max(log_dose),0.1) +# SAMPLE <- a+(d-a)/(1+exp(b*(seq_x-(cs-r)))) +# REF <- a+(d-a)/(1+exp(b*(seq_x-(cs)))) +# +# if (is.null(det_sig)) { +# SAMPLEtrue <- sigmoid[4] + (sigmoid[2] -sigmoid[4])/(1+exp(sigmoid[6]*(seq_x-(sigmoid[7]-sigmoid[8])))) +# REFtrue <- sigmoid[3] + (sigmoid[1] -sigmoid[3])/(1+exp(sigmoid[5]*(seq_x-(sigmoid[7])))) +# } else { +# SAMPLEtrue <- det_sig[4] + (det_sig[6] -det_sig[4])/(1+exp(-det_sig[2]*(seq_x-(det_sig[8])))) +# REFtrue <- det_sig[3] + (det_sig[5] -det_sig[3])/(1+exp(-det_sig[1]*(seq_x-(det_sig[7])))) +# } +# +# pl_df <- cbind(seq_x, SAMPLE, REF, SAMPLEtrue, REFtrue) +# all_l2$readout[all_l2$readout < 0] <- 0.01 +# all_l2$readouttrans <- log(all_l2$readout) +# slopeEC50 <- b*(a-d)/4 +# +# Xbendl3 <- cs-(1.31696/b) +# Xbendu3 <- cs+(1.31696/b) +# XbendlT <- cs-r-(1.31696/b) +# XbenduT <- cs-r+(1.31696/b) +# bendpoints <- c(bendREF_lower = round(Xbendl3,3), bendREF_upper=round(Xbendu3,3), +# bendSAMPLE_lower = round(XbendlT,3), bendSAMPLE_upper=round(XbenduT,3)) +# +# p <- ggplot(all_l2, aes(x=log_dose, y=readout, color=factor(isRef))) + +# geom_point(shape=factor(isRef), alpha=0.8) + +# labs(title = paste("restricted 4pl; bendp:", round(Xbendl3,3),round(Xbendu3,3),round(XbendlT,3),round(XbenduT,3)), +# color="product") + +# scale_color_manual(labels=c("test","reference"), values=c("red","blue")) + +# scale_shape_manual(labels=c("test","reference")) + +# theme_bw() + +# theme(axis.text = element_text(size=14)) +# +# p2 <- p + geom_line(data=as.data.frame(pl_df), aes(x=seq_x, y=SAMPLE), color="red", +# inherit.aes = F) + +# geom_line(data=as.data.frame(pl_df), aes(x=seq_x, y=REF), color="blue", +# inherit.aes = F) + +# geom_line(data=as.data.frame(pl_df), aes(x=seq_x, y=SAMPLEtrue), color="red", linetype=2, alpha=0.4, +# inherit.aes = F) + +# geom_line(data=as.data.frame(pl_df), aes(x=seq_x, y=REFtrue), color="blue", linetype=2, alpha=0.4, +# inherit.aes = F) + +# geom_vline(xintercept=c(Xbendl3, Xbendu3), col="blue",linetype=2) + +# geom_vline(xintercept=c(XbendlT, XbenduT), col="red",linetype=2) + +# annotate("text", x=cs, y=a+(d-a)/2, label="0", size=5) + +# theme(legend.position="none") +# +# +# # transformed plots +# p_rt <- ggplot(all_l2, aes(x=log_dose, y=readouttrans, color=factor(isRef))) + +# geom_point(shape=factor(isRef), alpha=0.8) + +# labs(title = paste("restricted transformed 4pl"), color="product") + +# scale_color_manual(labels=c("test","reference"), values=c("red","blue")) + +# theme_bw() +# +# mrt <- gsl_nls(fn = readouttrans ~ a+(d-a)/(1+exp(b*(log_dose-(cs-r*isSample)))), +# data=all_l2, +# start=startlist, +# control=gsl_nls_control(xtol=1e-6,ftol=1e-6, gtol=1e-6)) +# s_mrt <- summary(mrt) +# a_trans <- s_mrt$coefficients[1,1] +# b_trans <- s_mrt$coefficients[2,1] +# cs_trans <- s_mrt$coefficients[3,1] +# d_trans <- s_mrt$coefficients[4,1] +# r_trans <- s_mrt$coefficients[5,1] +# +# XbendlTrans <- cs_trans-(1.31696/b_trans) +# XbenduTrans <- cs_trans+(1.31696/b_trans) +# XbendlTransT <- cs_trans-r_trans-(1.31696/b_trans) +# XbenduTransT <- cs_trans-r_trans+(1.31696/b_trans) +# bendpointsTRANS <- c(bendREF_lower = round(XbendlTrans,3), bendREF_upper=round(XbenduTrans,3), +# bendSAMPLE_lower = round(XbendlTransT,3), bendSAMPLE_upper=round(XbenduTransT,3)) +# +# SAMPLEtrans <- a_trans+(d_trans-a_trans)/(1+exp(b_trans*(seq_x-(cs_trans-r_trans)))) +# REFtrans <- a_trans+(d_trans-a_trans)/(1+exp(b_trans*(seq_x-(cs_trans)))) +# +# pl_df_trans <- cbind(seq_x, SAMPLEtrans, REFtrans) +# p_rt2 <- p_rt + geom_line(data=as.data.frame(pl_df_trans), aes(x=seq_x, y=SAMPLEtrans), color="red", +# inherit.aes = F) + +# geom_line(data=as.data.frame(pl_df_trans), aes(x=seq_x, y=REFtrans), color="blue", +# inherit.aes = F) + +# geom_vline(xintercept=c(XbendlTrans, XbenduTrans), col="blue",linetype=2) + +# geom_vline(xintercept=c(XbendlTransT, XbenduTransT), col="red",linetype=2) + +# theme(legend.position = "none", axis.text=element_text(size=14)) +# +# if (is.null(det_sig)) { +# unrestr <- drm(readout ~ exp(log_dose), isSample, data=all_l2, fct=LL.4(), +# pmodels=data.frame(isSample, isSample,isSample,isSample)) +# Sum_u <- summary(unrestr) +# ast <- Sum_u$coefficients[3,1] +# ate <- Sum_u$coefficients[4,1] +# bst <- Sum_u$coefficients[1,1] +# bte <- Sum_u$coefficients[2,1] +# cst <- log(Sum_u$coefficients[7,1]) +# cte <- log(Sum_u$coefficients[8,1]) +# dst <- Sum_u$coefficients[5,1] +# dte <- Sum_u$coefficients[6,1] +# } else { +# ast <- det_sig[5] +# ate <- det_sig[6] +# bst <- det_sig[1] +# bte <- det_sig[2] +# cst <- det_sig[7] +# cte <- det_sig[8] +# dst <- det_sig[3] +# dte <- det_sig[4] +# } +# REFu <- ast + (dst-ast)/(1+exp(bst*(seq_x-cst))) +# SAMPLEu <- ate + (dte-ate)/(1+exp(bte*(seq_x-cte))) +# pl_df2 <- cbind(seq_x, SAMPLEu, REFu) +# #browser() +# pu <- ggplot(all_l2, aes(x=log_dose, y=readout, color=factor(isRef))) + +# geom_point() + +# labs(title="unrestricted 4_pl-Model", color="product") + +# scale_color_manual(labels = c("test","reference"), values=c("red","blue")) + +# theme_bw() +# pu2 <- pu + geom_line(data=as.data.frame(pl_df2), aes(x=seq_x, y=SAMPLEu), +# color="red", inherit.aes = F) + +# geom_line(data=as.data.frame(pl_df2), aes(x=seq_x, y=REFu), +# color="blue", inherit.aes = F, +# show.legend = F) +# pu2_ <- pu2 + +# theme(legend.position = "none", axis.text = element_text(size=14)) +# putrans <- ggplot(all_l2, aes(x=log_dose, y=readouttrans, color=factor(isRef))) + +# geom_point() + +# labs(title="unrestricted transformed 4_pl-Model", color="product") + +# scale_color_manual(labels = c("test","reference"), values=c("red","blue")) + +# theme_bw() +# +# unrestr_trans <- drm(readouttrans ~ exp(log_dose), isSample, data=all_l2, fct=LL.4(), +# pmodels=data.frame(isSample, isSample,isSample,isSample)) +# Sum_ut <- summary(unrestr_trans) +# ast_t <- Sum_ut$coefficients[3,1] +# ate_t <- Sum_ut$coefficients[4,1] +# bst_t <- Sum_ut$coefficients[1,1] +# bte_t <- Sum_ut$coefficients[2,1] +# cst_t <- log(Sum_ut$coefficients[7,1]) +# cte_t <- log(Sum_ut$coefficients[8,1]) +# dst_t <- Sum_ut$coefficients[5,1] +# dte_t <- Sum_ut$coefficients[6,1] +# +# REFu_trans <- ast_t + (dst_t-ast_t)/(1+exp(bst_t*(seq_x-cst_t))) +# SAMPLEu_trans <- ate_t + (dte_t-ate_t)/(1+exp(bte_t*(seq_x-cte_t))) +# pl_df2u_t <- cbind(seq_x, SAMPLEu_trans, REFu_trans) +# +# pu2_t <- putrans + geom_line(data=as.data.frame(pl_df2u_t), aes(x=seq_x, y=SAMPLEu_trans), +# color="red", inherit.aes = F) + +# geom_line(data=as.data.frame(pl_df2u_t), aes(x=seq_x, y=REFu_trans), +# color="blue", inherit.aes = F, +# show.legend = F) +# pu3_t <- pu2_t +# grid.arrange(p2,p_rt2,pu2_,pu3_t, nrow=2) +# } +# +# plot_f(XLdat2, sigmoid=NULL, det_sig=coeffs) - all_l <- melt(data.frame(dat), id.vars="log_dose", variable.name="replname", value.name = "readout") - isRef <- rep(c(1,0),1,each=nrow(all_l)/2) - isSample <- rep(c(0,1),1,each=nrow(all_l)/2) - all_l2 <- cbind(all_l, isRef, isSample) - - if(is.null(det_sig)) { - if (CORdat<0) { - startlist <- list(a=sigmoid[3], b=-sigmoid[5],cs=sigmoid[7], - d=sigmoid[1],r=sigmoid[8]) - } else { - startlist <- list(a=sigmoid[3],b=sigmoid[5],cs=sigmoid[7], - d=sigmoid[1],r=sigmoid[8]) - } - } else { - startlist <- list(a=det_sig[5], b=det_sig[1],cs=det_sig[7], - d=det_sig[3],r=det_sig[7] - det_sig[8]) - } - #browser() - tryCatch({ - mr <- gsl_nls(fn = readout ~ a+(d-a)/(1+exp(b*(log_dose-(cs-r*isSample)))), - data=all_l2, - start=startlist, - control=gsl_nls_control(xtol=1e-6,ftol=1e-6, gtol=1e-6)) - }, - error = function(err) { - err$message - }) - s_mr <- summary(mr) - a <- s_mr$coefficients[1,1] - b <- s_mr$coefficients[2,1] - cs <- s_mr$coefficients[3,1] - d <- s_mr$coefficients[4,1] - r <- s_mr$coefficients[5,1] - - log_dose <- unique(all_l$log_dose) - seq_x <- seq(min(log_dose),max(log_dose),0.1) - SAMPLE <- a+(d-a)/(1+exp(b*(seq_x-(cs-r)))) - REF <- a+(d-a)/(1+exp(b*(seq_x-(cs)))) - - if (is.null(det_sig)) { - SAMPLEtrue <- sigmoid[4] + (sigmoid[2] -sigmoid[4])/(1+exp(sigmoid[6]*(seq_x-(sigmoid[7]-sigmoid[8])))) - REFtrue <- sigmoid[3] + (sigmoid[1] -sigmoid[3])/(1+exp(sigmoid[5]*(seq_x-(sigmoid[7])))) - } else { - SAMPLEtrue <- det_sig[4] + (det_sig[6] -det_sig[4])/(1+exp(-det_sig[2]*(seq_x-(det_sig[8])))) - REFtrue <- det_sig[3] + (det_sig[5] -det_sig[3])/(1+exp(-det_sig[1]*(seq_x-(det_sig[7])))) - } - - pl_df <- cbind(seq_x, SAMPLE, REF, SAMPLEtrue, REFtrue) - all_l2$readout[all_l2$readout < 0] <- 0.01 - all_l2$readouttrans <- log(all_l2$readout) - slopeEC50 <- b*(a-d)/4 - - Xbendl3 <- cs-(1.31696/b) - Xbendu3 <- cs+(1.31696/b) - XbendlT <- cs-r-(1.31696/b) - XbenduT <- cs-r+(1.31696/b) - bendpoints <- c(bendREF_lower = round(Xbendl3,3), bendREF_upper=round(Xbendu3,3), - bendSAMPLE_lower = round(XbendlT,3), bendSAMPLE_upper=round(XbenduT,3)) - - p <- ggplot(all_l2, aes(x=log_dose, y=readout, color=factor(isRef))) + - geom_point(shape=factor(isRef), alpha=0.8) + - labs(title = paste("restricted 4pl; bendp:", round(Xbendl3,3),round(Xbendu3,3),round(XbendlT,3),round(XbenduT,3)), - color="product") + - scale_color_manual(labels=c("test","reference"), values=c("red","blue")) + - scale_shape_manual(labels=c("test","reference")) + - theme_bw() + - theme(axis.text = element_text(size=14)) - - p2 <- p + geom_line(data=as.data.frame(pl_df), aes(x=seq_x, y=SAMPLE), color="red", - inherit.aes = F) + - geom_line(data=as.data.frame(pl_df), aes(x=seq_x, y=REF), color="blue", - inherit.aes = F) + - geom_line(data=as.data.frame(pl_df), aes(x=seq_x, y=SAMPLEtrue), color="red", linetype=2, alpha=0.4, - inherit.aes = F) + - geom_line(data=as.data.frame(pl_df), aes(x=seq_x, y=REFtrue), color="blue", linetype=2, alpha=0.4, - inherit.aes = F) + - geom_vline(xintercept=c(Xbendl3, Xbendu3), col="blue",linetype=2) + - geom_vline(xintercept=c(XbendlT, XbenduT), col="red",linetype=2) + - annotate("text", x=cs, y=a+(d-a)/2, label="0", size=5) + - theme(legend.position="none") - - - # transformed plots - p_rt <- ggplot(all_l2, aes(x=log_dose, y=readouttrans, color=factor(isRef))) + - geom_point(shape=factor(isRef), alpha=0.8) + - labs(title = paste("restricted transformed 4pl"), color="product") + - scale_color_manual(labels=c("test","reference"), values=c("red","blue")) + - theme_bw() - - mrt <- gsl_nls(fn = readouttrans ~ a+(d-a)/(1+exp(b*(log_dose-(cs-r*isSample)))), - data=all_l2, - start=startlist, - control=gsl_nls_control(xtol=1e-6,ftol=1e-6, gtol=1e-6)) - s_mrt <- summary(mrt) - a_trans <- s_mrt$coefficients[1,1] - b_trans <- s_mrt$coefficients[2,1] - cs_trans <- s_mrt$coefficients[3,1] - d_trans <- s_mrt$coefficients[4,1] - r_trans <- s_mrt$coefficients[5,1] - - XbendlTrans <- cs_trans-(1.31696/b_trans) - XbenduTrans <- cs_trans+(1.31696/b_trans) - XbendlTransT <- cs_trans-r_trans-(1.31696/b_trans) - XbenduTransT <- cs_trans-r_trans+(1.31696/b_trans) - bendpointsTRANS <- c(bendREF_lower = round(XbendlTrans,3), bendREF_upper=round(XbenduTrans,3), - bendSAMPLE_lower = round(XbendlTransT,3), bendSAMPLE_upper=round(XbenduTransT,3)) - - SAMPLEtrans <- a_trans+(d_trans-a_trans)/(1+exp(b_trans*(seq_x-(cs_trans-r_trans)))) - REFtrans <- a_trans+(d_trans-a_trans)/(1+exp(b_trans*(seq_x-(cs_trans)))) - - pl_df_trans <- cbind(seq_x, SAMPLEtrans, REFtrans) - p_rt2 <- p_rt + geom_line(data=as.data.frame(pl_df_trans), aes(x=seq_x, y=SAMPLEtrans), color="red", - inherit.aes = F) + - geom_line(data=as.data.frame(pl_df_trans), aes(x=seq_x, y=REFtrans), color="blue", - inherit.aes = F) + - geom_vline(xintercept=c(XbendlTrans, XbenduTrans), col="blue",linetype=2) + - geom_vline(xintercept=c(XbendlTransT, XbenduTransT), col="red",linetype=2) + - theme(legend.position = "none", axis.text=element_text(size=14)) - - if (is.null(det_sig)) { - unrestr <- drm(readout ~ exp(log_dose), isSample, data=all_l2, fct=LL.4(), - pmodels=data.frame(isSample, isSample,isSample,isSample)) - Sum_u <- summary(unrestr) - ast <- Sum_u$coefficients[3,1] - ate <- Sum_u$coefficients[4,1] - bst <- Sum_u$coefficients[1,1] - bte <- Sum_u$coefficients[2,1] - cst <- log(Sum_u$coefficients[7,1]) - cte <- log(Sum_u$coefficients[8,1]) - dst <- Sum_u$coefficients[5,1] - dte <- Sum_u$coefficients[6,1] - } else { - ast <- det_sig[5] - ate <- det_sig[6] - bst <- det_sig[1] - bte <- det_sig[2] - cst <- det_sig[7] - cte <- det_sig[8] - dst <- det_sig[3] - dte <- det_sig[4] - } - REFu <- ast + (dst-ast)/(1+exp(bst*(seq_x-cst))) - SAMPLEu <- ate + (dte-ate)/(1+exp(bte*(seq_x-cte))) - pl_df2 <- cbind(seq_x, SAMPLEu, REFu) -#browser() - pu <- ggplot(all_l2, aes(x=log_dose, y=readout, color=factor(isRef))) + - geom_point() + - labs(title="unrestricted 4_pl-Model", color="product") + - scale_color_manual(labels = c("test","reference"), values=c("red","blue")) + - theme_bw() - pu2 <- pu + geom_line(data=as.data.frame(pl_df2), aes(x=seq_x, y=SAMPLEu), - color="red", inherit.aes = F) + - geom_line(data=as.data.frame(pl_df2), aes(x=seq_x, y=REFu), - color="blue", inherit.aes = F, - show.legend = F) - pu2_ <- pu2 + - theme(legend.position = "none", axis.text = element_text(size=14)) - putrans <- ggplot(all_l2, aes(x=log_dose, y=readouttrans, color=factor(isRef))) + - geom_point() + - labs(title="unrestricted transformed 4_pl-Model", color="product") + - scale_color_manual(labels = c("test","reference"), values=c("red","blue")) + - theme_bw() - - unrestr_trans <- drm(readouttrans ~ exp(log_dose), isSample, data=all_l2, fct=LL.4(), - pmodels=data.frame(isSample, isSample,isSample,isSample)) - Sum_ut <- summary(unrestr_trans) - ast_t <- Sum_ut$coefficients[3,1] - ate_t <- Sum_ut$coefficients[4,1] - bst_t <- Sum_ut$coefficients[1,1] - bte_t <- Sum_ut$coefficients[2,1] - cst_t <- log(Sum_ut$coefficients[7,1]) - cte_t <- log(Sum_ut$coefficients[8,1]) - dst_t <- Sum_ut$coefficients[5,1] - dte_t <- Sum_ut$coefficients[6,1] - - REFu_trans <- ast_t + (dst_t-ast_t)/(1+exp(bst_t*(seq_x-cst_t))) - SAMPLEu_trans <- ate_t + (dte_t-ate_t)/(1+exp(bte_t*(seq_x-cte_t))) - pl_df2u_t <- cbind(seq_x, SAMPLEu_trans, REFu_trans) - - pu2_t <- putrans + geom_line(data=as.data.frame(pl_df2u_t), aes(x=seq_x, y=SAMPLEu_trans), - color="red", inherit.aes = F) + - geom_line(data=as.data.frame(pl_df2u_t), aes(x=seq_x, y=REFu_trans), - color="blue", inherit.aes = F, - show.legend = F) - pu3_t <- pu2_t - grid.arrange(p2,p_rt2,pu2_,pu3_t, nrow=2) -} - -plot_f(XLdat2, sigmoid=NULL, det_sig=coeffs) ``` diff --git a/Doc_BioassayReport.Rmd b/Doc_BioassayReport.Rmd index c1c9bdf..63485c3 100644 --- a/Doc_BioassayReport.Rmd +++ b/Doc_BioassayReport.Rmd @@ -42,6 +42,7 @@ knitr::opts_chunk$set(echo = TRUE) library(knitr) library(DT) +library(kableExtra) REP <- params$REP author <- params$author @@ -49,13 +50,14 @@ coeffs <- params$coeffs all_l <- REP$all_l ANOVAXLS <- REP$ANOVAXLS +XLplot4pl <- REP$XLplot4pl DiagnTable <- REP$DiagnTable UnRPLAausw <- REP$UnRPLAausw UnRPLBend <- REP$UnRPLBend PLAausw <- REP$PLAausw PLBend <- REP$PLBend -LogPLAausw <- REP$LogPLAausw -LogUnrPLAausw <- REP$LogUnrPLAausw +pottab4plXL <- REP$pottab4plXL +Lim <- REP$Lim XLdat2 <- REP$XLdat2 @@ -70,262 +72,144 @@ relpotTestPlot <- REP$relpotTestPlot # Introduction -Bioassay potency estimation uses statistical methods to quantify the strength of a biological product or drug by comparing its response to that of a reference standard. Because biological responses are inherently variable, affected by assay conditions, cell systems or organisms, and measurement noise, the 4-parametric logistic regression is used to obtain reliable potency values. The variance for confidence interval calculation is coming from the regression procedure itself and is an excellent predictor for the variability of any future potency determinations. -USP<1034> recommends calculation of standard errors of ratios of the parameters using Fieller's theorem [Finney D.J. 1978] or using the "delta" method (for a discussion about the "delta" method see [Ver Hoef 2012]). However, the presented gradient approach using the differences on the log-scale is methematically more stable und thus preferable compared to any ratio approach ([Franz, V.H. 2007]). +Bioassay potency estimation uses statistical methods to quantify the strength of a biological product or drug by comparing its response to that of a reference standard. Because biological responses are inherently variable, affected by assay conditions, cell systems or organisms, and measurement noise, the 4-parametric logistic regression is used to obtain reliable potency values. +USP<1034> recommends calculation of standard errors of ratios of the parameters using Fieller's theorem [Finney DJ 1978] or using the "delta" method (for a discussion about the "delta" method see [Ver Hoef 2012]). However, the presented gradient approach using the differences on the log-scale is mathematically more stable und thus preferable compared to a ratio approach ([Franz VH 2007]). -# Results +# Raw data All data used for the 4PL evaluation is shown in table 1: ```{r alll, echo=FALSE, warning=FALSE, results='asis'} -kable(all_l, format = "markdown", caption= "Uploaded data (test and reference) in long format", digits=3) +kable(XLdat2, format = "markdown", caption= "Uploaded data (test and reference) ", digits=3) ``` -The following 4 plots show all 4 models: restricted and unrestricted, and log transformed, respectively. -You can also embed plots, for example: +# Results -```{r XLplot, echo=FALSE, warning=FALSE, fig.height=4, fig.width=6, fig.cap="Plot of models", fig.align='left'} +## Overall result -plot_f <- function(dat, sigmoid,det_sig) { - CORdat <- cor(dat[,1],dat[,ncol(dat)]) +```{r Over_all, echo=FALSE, comment=NA, warning=NA, message=NA} - all_l <- melt(data.frame(dat), id.vars="log_dose", variable.name="replname", value.name = "readout") - isRef <- rep(c(1,0),1,each=nrow(all_l)/2) - isSample <- rep(c(0,1),1,each=nrow(all_l)/2) - all_l2 <- cbind(all_l, isRef, isSample) +potFlag <- 0 +if (pottab4plXL["test_result"][[1]][1]==1) potFlag <- 1 +AnalysisFlag <- FALSE +if (potFlag==1 | sum(testsTab$test_results)>0) AnalysisFlag <- TRUE - if(is.null(det_sig)) { - if (CORdat<0) { - startlist <- list(a=sigmoid[3], b=-sigmoid[5],cs=sigmoid[7], - d=sigmoid[1],r=sigmoid[8]) - } else { - startlist <- list(a=sigmoid[3],b=sigmoid[5],cs=sigmoid[7], - d=sigmoid[1],r=sigmoid[8]) - } - } else { - startlist <- list(a=det_sig[5], b=det_sig[1],cs=det_sig[7], - d=det_sig[3],r=det_sig[7] - det_sig[8]) - } - #browser() - tryCatch({ - mr <- gsl_nls(fn = readout ~ a+(d-a)/(1+exp(b*(log_dose-(cs-r*isSample)))), - data=all_l2, - start=startlist, - control=gsl_nls_control(xtol=1e-6,ftol=1e-6, gtol=1e-6)) - }, - error = function(err) { - err$message - }) - s_mr <- summary(mr) - a <- s_mr$coefficients[1,1] - b <- s_mr$coefficients[2,1] - cs <- s_mr$coefficients[3,1] - d <- s_mr$coefficients[4,1] - r <- s_mr$coefficients[5,1] - - log_dose <- unique(all_l$log_dose) - seq_x <- seq(min(log_dose),max(log_dose),0.1) - SAMPLE <- a+(d-a)/(1+exp(b*(seq_x-(cs-r)))) - REF <- a+(d-a)/(1+exp(b*(seq_x-(cs)))) - - if (is.null(det_sig)) { - SAMPLEtrue <- sigmoid[4] + (sigmoid[2] -sigmoid[4])/(1+exp(sigmoid[6]*(seq_x-(sigmoid[7]-sigmoid[8])))) - REFtrue <- sigmoid[3] + (sigmoid[1] -sigmoid[3])/(1+exp(sigmoid[5]*(seq_x-(sigmoid[7])))) - } else { - SAMPLEtrue <- det_sig[4] + (det_sig[6] -det_sig[4])/(1+exp(-det_sig[2]*(seq_x-(det_sig[8])))) - REFtrue <- det_sig[3] + (det_sig[5] -det_sig[3])/(1+exp(-det_sig[1]*(seq_x-(det_sig[7])))) - } - - pl_df <- cbind(seq_x, SAMPLE, REF, SAMPLEtrue, REFtrue) - all_l2$readout[all_l2$readout < 0] <- 0.01 - all_l2$readouttrans <- log(all_l2$readout) - slopeEC50 <- b*(a-d)/4 - - Xbendl3 <- cs-(1.31696/b) - Xbendu3 <- cs+(1.31696/b) - XbendlT <- cs-r-(1.31696/b) - XbenduT <- cs-r+(1.31696/b) - bendpoints <- c(bendREF_lower = round(Xbendl3,3), bendREF_upper=round(Xbendu3,3), - bendSAMPLE_lower = round(XbendlT,3), bendSAMPLE_upper=round(XbenduT,3)) - - p <- ggplot(all_l2, aes(x=log_dose, y=readout, color=factor(isRef))) + - geom_point(shape=factor(isRef), alpha=0.8) + - labs(title = paste("restricted 4pl; bendp:", round(Xbendl3,3),round(Xbendu3,3),round(XbendlT,3),round(XbenduT,3)), - color="product") + - scale_color_manual(labels=c("test","reference"), values=c("red","blue")) + - scale_shape_manual(labels=c("test","reference")) + - theme_bw() + - theme(axis.text = element_text(size=14)) - - p2 <- p + geom_line(data=as.data.frame(pl_df), aes(x=seq_x, y=SAMPLE), color="red", - inherit.aes = F) + - geom_line(data=as.data.frame(pl_df), aes(x=seq_x, y=REF), color="blue", - inherit.aes = F) + - geom_line(data=as.data.frame(pl_df), aes(x=seq_x, y=SAMPLEtrue), color="red", linetype=2, alpha=0.4, - inherit.aes = F) + - geom_line(data=as.data.frame(pl_df), aes(x=seq_x, y=REFtrue), color="blue", linetype=2, alpha=0.4, - inherit.aes = F) + - geom_vline(xintercept=c(Xbendl3, Xbendu3), col="blue",linetype=2) + - geom_vline(xintercept=c(XbendlT, XbenduT), col="red",linetype=2) + - annotate("text", x=cs, y=a+(d-a)/2, label="0", size=5) + - theme(legend.position="none") - - - # transformed plots - p_rt <- ggplot(all_l2, aes(x=log_dose, y=readouttrans, color=factor(isRef))) + - geom_point(shape=factor(isRef), alpha=0.8) + - labs(title = paste("restricted transformed 4pl"), color="product") + - scale_color_manual(labels=c("test","reference"), values=c("red","blue")) + - theme_bw() - - mrt <- gsl_nls(fn = readouttrans ~ a+(d-a)/(1+exp(b*(log_dose-(cs-r*isSample)))), - data=all_l2, - start=startlist, - control=gsl_nls_control(xtol=1e-6,ftol=1e-6, gtol=1e-6)) - s_mrt <- summary(mrt) - a_trans <- s_mrt$coefficients[1,1] - b_trans <- s_mrt$coefficients[2,1] - cs_trans <- s_mrt$coefficients[3,1] - d_trans <- s_mrt$coefficients[4,1] - r_trans <- s_mrt$coefficients[5,1] - - XbendlTrans <- cs_trans-(1.31696/b_trans) - XbenduTrans <- cs_trans+(1.31696/b_trans) - XbendlTransT <- cs_trans-r_trans-(1.31696/b_trans) - XbenduTransT <- cs_trans-r_trans+(1.31696/b_trans) - bendpointsTRANS <- c(bendREF_lower = round(XbendlTrans,3), bendREF_upper=round(XbenduTrans,3), - bendSAMPLE_lower = round(XbendlTransT,3), bendSAMPLE_upper=round(XbenduTransT,3)) - - SAMPLEtrans <- a_trans+(d_trans-a_trans)/(1+exp(b_trans*(seq_x-(cs_trans-r_trans)))) - REFtrans <- a_trans+(d_trans-a_trans)/(1+exp(b_trans*(seq_x-(cs_trans)))) - - pl_df_trans <- cbind(seq_x, SAMPLEtrans, REFtrans) - p_rt2 <- p_rt + geom_line(data=as.data.frame(pl_df_trans), aes(x=seq_x, y=SAMPLEtrans), color="red", - inherit.aes = F) + - geom_line(data=as.data.frame(pl_df_trans), aes(x=seq_x, y=REFtrans), color="blue", - inherit.aes = F) + - geom_vline(xintercept=c(XbendlTrans, XbenduTrans), col="blue",linetype=2) + - geom_vline(xintercept=c(XbendlTransT, XbenduTransT), col="red",linetype=2) + - theme(legend.position = "none", axis.text=element_text(size=14)) - - if (is.null(det_sig)) { - unrestr <- drm(readout ~ exp(log_dose), isSample, data=all_l2, fct=LL.4(), - pmodels=data.frame(isSample, isSample,isSample,isSample)) - Sum_u <- summary(unrestr) - ast <- Sum_u$coefficients[3,1] - ate <- Sum_u$coefficients[4,1] - bst <- Sum_u$coefficients[1,1] - bte <- Sum_u$coefficients[2,1] - cst <- log(Sum_u$coefficients[7,1]) - cte <- log(Sum_u$coefficients[8,1]) - dst <- Sum_u$coefficients[5,1] - dte <- Sum_u$coefficients[6,1] - } else { - ast <- det_sig[5] - ate <- det_sig[6] - bst <- det_sig[1] - bte <- det_sig[2] - cst <- det_sig[7] - cte <- det_sig[8] - dst <- det_sig[3] - dte <- det_sig[4] - } - REFu <- ast + (dst-ast)/(1+exp(bst*(seq_x-cst))) - SAMPLEu <- ate + (dte-ate)/(1+exp(bte*(seq_x-cte))) - pl_df2 <- cbind(seq_x, SAMPLEu, REFu) -#browser() - pu <- ggplot(all_l2, aes(x=log_dose, y=readout, color=factor(isRef))) + - geom_point() + - labs(title="unrestricted 4_pl-Model", color="product") + - scale_color_manual(labels = c("test","reference"), values=c("red","blue")) + - theme_bw() - pu2 <- pu + geom_line(data=as.data.frame(pl_df2), aes(x=seq_x, y=SAMPLEu), - color="red", inherit.aes = F) + - geom_line(data=as.data.frame(pl_df2), aes(x=seq_x, y=REFu), - color="blue", inherit.aes = F, - show.legend = F) - pu2_ <- pu2 + - theme(legend.position = "none", axis.text = element_text(size=14)) - putrans <- ggplot(all_l2, aes(x=log_dose, y=readouttrans, color=factor(isRef))) + - geom_point() + - labs(title="unrestricted transformed 4_pl-Model", color="product") + - scale_color_manual(labels = c("test","reference"), values=c("red","blue")) + - theme_bw() - - unrestr_trans <- drm(readouttrans ~ exp(log_dose), isSample, data=all_l2, fct=LL.4(), - pmodels=data.frame(isSample, isSample,isSample,isSample)) - Sum_ut <- summary(unrestr_trans) - ast_t <- Sum_ut$coefficients[3,1] - ate_t <- Sum_ut$coefficients[4,1] - bst_t <- Sum_ut$coefficients[1,1] - bte_t <- Sum_ut$coefficients[2,1] - cst_t <- log(Sum_ut$coefficients[7,1]) - cte_t <- log(Sum_ut$coefficients[8,1]) - dst_t <- Sum_ut$coefficients[5,1] - dte_t <- Sum_ut$coefficients[6,1] - - REFu_trans <- ast_t + (dst_t-ast_t)/(1+exp(bst_t*(seq_x-cst_t))) - SAMPLEu_trans <- ate_t + (dte_t-ate_t)/(1+exp(bte_t*(seq_x-cte_t))) - pl_df2u_t <- cbind(seq_x, SAMPLEu_trans, REFu_trans) - - pu2_t <- putrans + geom_line(data=as.data.frame(pl_df2u_t), aes(x=seq_x, y=SAMPLEu_trans), - color="red", inherit.aes = F) + - geom_line(data=as.data.frame(pl_df2u_t), aes(x=seq_x, y=REFu_trans), - color="blue", inherit.aes = F, - show.legend = F) - pu3_t <- pu2_t - grid.arrange(p2,p_rt2,pu2_,pu3_t, nrow=2) +colFmt <- function() { + + outputFormat <- knitr::opts_knit$get("rmarkdown.pandoc.to") + if(AnalysisFlag) { + text <- paste("\\textcolor{red}{Analysis failed}",sep="") + } else { + text <- paste("\\textcolor{black}{Analysis succeeded}>",sep="") + } + return(text) } -plot_f(XLdat2, sigmoid=NULL, det_sig=coeffs) + +``` + +`r colFmt()` + + +## 4pl-regression + +Relative potency (absolute and relative confidence limits) are shown in Table 2: + +```{r Pot_tab4pl, echo=FALSE, comment=NA, warning=NA, message=NA} + +#browser() +if (pottab4plXL["test_result"][[1]][1]==1) { cat(paste("FAILED: relative potency CL result of restricted model outside limits: ", Lim[[9]], "and" ,Lim[[10]] ))} +kable(pottab4plXL, format = "markdown", caption= "Relative potency with absolute and relative CLs ", digits=3, row.names = F) %>% + kable_styling(latex_options = "hold_position") ``` + +## Plot of the data and models + +The following plots show the restricted and unrestricted model, respectively. + + +```{r XLplot, echo=FALSE, warning=FALSE, fig.height=4, fig.width=6, fig.cap="Plot of models", fig.align='left', comment=F, message=F, results='asis', fig.pos='H'} + +library(cowplot) + + +plot_grid(XLplot4pl) + + +``` + + +## ANOVA table + The ANOVA of the unconstrained model is listed in table 2: ```{r anovaxls, echo=FALSE, warning=FALSE, results='asis'} -kable(ANOVAXLS, format = "markdown", caption= "ANOVA table unrestricted", digits=3) +kable(ANOVAXLS, format = "markdown", caption= "ANOVA table unrestricted", digits=3) %>% + kable_styling(latex_options = "hold_position") + + +``` + +## Analysis suitability tests + +The following table lists the chosen suitabilit test results with confidence limits, where applicable: + + +```{r SST_ergebn, echo=FALSE, cache=FALSE, warning=FALSE, message=FALSE, tidy=TRUE} + +kable(testsTab, row.names = F, format = "markdown", caption="SST results") ``` -```{r SST_ergebn, fig.align='center', fig.pos='htb!', echo=FALSE, cache=FALSE, warning=FALSE, message=FALSE, tidy=TRUE} +\footnotesize -kable(testsTab[1:7,], row.names = F, format = "markdown", caption="SST results") +```{r Fussnote, echo=F, comment=NA} + +cat("*...The estimate for F-test on regression and on non-linearity is the p-value") +cat( "F-test on regression passes if F-value > F-crit and thus p < 0.05") +cat( "F-test on non-linearity passes if F-value < F-crit and thus p > 0.05") +cat( "Test results outcome:") +cat(" 0 ... test passed (for EQ tests: CL within limits);") +cat(" 1 ... test failed (for EQ tests: CL not within limits);") + + + +``` + +\normalsize + + +```{r AST_Ergebn, echo=FALSE, cache=FALSE, warning=FALSE, message=FALSE, tidy=TRUE} + +TestsTabFlag <- FALSE +if (sum(testsTab$test_results)>0) TestsTabFlag <- TRUE +colFmt2 <- function() { + + outputFormat <- knitr::opts_knit$get("rmarkdown.pandoc.to") + if(TestsTabFlag) { + text <- paste("\\textcolor{red}{Analysis suitability tests failed}",sep="") + } else { + text <- paste("\\textcolor{black}{Analysis suitability tests succeeded}",sep="") + } + return(text) +} ``` -*...The estimate for F-test on regression and on non-linearity is the p-value - F-test on regression passes if F-value > F-crit and thus p < 0.05 - F-test on non-linearity passes if F-value < F-crit and thus p > 0.05 - Test results outcome: - - 0 ... test passed (for EQ tests: CI within limits); - - 1 ... test failed (for EQ tests CI not within limits); - - -1 ... calculations unbound/denominator too close to 0 +`r colFmt2()` - - - - - - - - - - - ## Fitting results of the 4 models with bend points @@ -377,23 +261,6 @@ kable(UnRPLBend, format = "markdown", caption= "Bend points of 4PL unrestricted" -```{r LogPLAausw, echo=FALSE, warning=FALSE, results='asis'} - -kable(LogPLAausw, format = "markdown", caption= "Restricted 4PL evaluation with log-transformed response", digits=3) - - -``` - - - -```{r LogUnRPLAausw, echo=FALSE, warning=FALSE, results='asis'} - -kable(LogUnrPLAausw, format = "markdown", caption= "Unrestricted 4PL evaluation with log-transformed response", digits=3) - - -``` - - # Appendix: Formulas ## 4PL regression diff --git a/RoxygenTestFile.Rmd b/RoxygenTestFile.Rmd index 72a1580..64284ed 100644 --- a/RoxygenTestFile.Rmd +++ b/RoxygenTestFile.Rmd @@ -49,3 +49,11 @@ expect_equal(TestTab, SolTab, check.attributes = FALSE) ``` Note that the `echo = FALSE` parameter was added to the code chunk to prevent printing of the R code that generated the plot. + + + +``` {r} +y<-1:4;mean(y) +#> [1] 2.5 +``` + diff --git a/app.R b/app.R index 6c8e123..6be8949 100644 --- a/app.R +++ b/app.R @@ -776,7 +776,7 @@ server <- function(input, output, session) { REP$PLAausw <- PLAAusw REP$PLBend <- PLAAusw2 - #### Koeffizienten-Extraktion ---- + #### Parameter extraktion ---- logcoeffs_R <- SRlog$coefficients[, 1] # logpot$coefficients names(logcoeffs_R) <- c("lower A", "Hill's slope", "upper A", "EC50 REF","EC50 DIFF") @@ -818,9 +818,13 @@ server <- function(input, output, session) { if (exists("Ind")) { Dat$dilution <- XLdat[,Ind] } else Dat$dilution <- exp(XLdat[,logI]) - # --- Plot-Ausgabe --- + + ##### Plot XL 4PL ---- output$XLplot <- renderPlot({ - plot_f(XLdat2, TransFlag=F) + XLplot4pl <- plot_f(XLdat2, TransFlag=F) + REP$XLplot4pl <- XLplot4pl + + XLplot4pl }) REP$XLdat2 <- XLdat2 @@ -1140,9 +1144,10 @@ server <- function(input, output, session) { tab <- tests_FUNC(Dat$EXCEL, Limite, PureErrFlag = PureErrFlag) tab[1,6:7] <- c("-","-") - Dat$tests_FUNC <- tab - REP$testsTab <- tab + tab2 <- tab[SelTests,] + Dat$tests_FUNC <- tab2 + REP$testsTab <- tab2 dat <- datatable(tab2,options = list( paging=TRUE, @@ -1158,26 +1163,26 @@ server <- function(input, output, session) { }) # observe #### plot CIs XL---- - observe({ - tab <- Dat$tests_FUNC - if (is.null(tab)) return(NULL) - - tab2 <- tab[-c(1,2,3,6),] - tab2[,3:7] <- apply(tab2[,3:7],2,as.numeric) - tab2[4:5,3:7] <- tab2[4:5,3:7]/100 - - p_CIs <- ggplot(tab2,aes(x=test,y=estimate, color=test,group=test)) + - geom_point() + - geom_errorbar(aes(ymin=lower_CI, ymax=upper_CI), width=0.4) + - geom_crossbar(aes(ymin=lower_limit, ymax=upper_limit), size=0.8) + - coord_flip() + - theme_bw() + - theme(legend.position = "none",text = element_text(size=20)) - - output$CIplot <- renderPlot({ p_CIs}, height=200) - - REP$CIplot <- p_CIs - }) + # observe({ + # tab <- Dat$tests_FUNC + # if (is.null(tab)) return(NULL) + # + # tab2 <- tab[-c(1,2,3,6),] + # tab2[,3:ncol(tab2)] <- apply(tab2[,3:ncol(tab2)],2,as.numeric) + # tab2[4:5,3:7] <- tab2[4:5,3:7]/100 + # + # p_CIs <- ggplot(tab2,aes(x=test,y=estimate, color=test,group=test)) + + # geom_point() + + # geom_errorbar(aes(ymin=lower_CI, ymax=upper_CI), width=0.4) + + # geom_crossbar(aes(ymin=lower_limit, ymax=upper_limit), size=0.8) + + # coord_flip() + + # theme_bw() + + # theme(legend.position = "none",text = element_text(size=20)) + # + # output$CIplot <- renderPlot({ p_CIs}, height=200) + # + # REP$CIplot <- p_CIs + # }) #### simulated data tab Meta ---- output$simdat <- DT::renderDataTable({ @@ -1643,7 +1648,7 @@ server <- function(input, output, session) { as.numeric(input$lEACratioSlope), as.numeric(input$uEACratioSlope), as.numeric(input$lEACratioua), as.numeric(input$uEACratioua), as.numeric(input$lowerPot), as.numeric(input$upperPot)) - + REP$Lim <- Lim pottab4_ <- data.frame(pottab4) pottab4_$potency <- round(as.numeric(pottab4[,2])*100,1) @@ -1667,6 +1672,8 @@ server <- function(input, output, session) { pottab4_ <- cbind(pottab4_[,-(2:4)], data.frame(tests=c(test_potCI, test_potUCI,test_potCI_t,test_potUCI_t))) colnames(pottab4_) <- c("model","potency","lower95%CI","upper95%CI","relative_lower95%CI","relative_upper95%CI","test_result") + REP$pottab4plXL <- pottab4_[1:2,] + output$pottab4plXL <- DT::renderDataTable({ dat <- datatable(pottab4_[1:2,], options=list(digits=3,