formatted Global.R
This commit is contained in:
Simon Innerbichler
+395
-205
@@ -14,16 +14,16 @@
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#' potency estimates and respective CIs of restricted and unrestricted models, and the predictions thereof.
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#' @export
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#' @examples
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#' dat <- data.frame(REF1=c(1547, 1620, 1644, 2504, 3426, 3512, 3401, 3787), REF2=c(1492, 1536, 1384, 2286, 3046, 3479, 3516, 3497),
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#' dat <- data.frame(
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#' REF1 = c(1547, 1620, 1644, 2504, 3426, 3512, 3401, 3787), REF2 = c(1492, 1536, 1384, 2286, 3046, 3479, 3516, 3497),
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#' REF3 = c(1468, 1827, 1558, 2252, 3002, 3349, 2945, 3665),
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#' TEST1 = c(1405, 1523, 1502, 1474, 2383, 3221, 3589, 3445), TEST2 = c(1420, 1516, 1544, 1512, 2226, 3219, 3327, 3591),
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#' TEST3=c(1399, 1376, 1588, 1475, 2148, 3083, 2942, 3466), log_dose=c(5.01,3.401,2.708,2.015,1.32176,0.62861,-0.0645385,-1.6739764))
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#' TEST3 = c(1399, 1376, 1588, 1475, 2148, 3083, 2942, 3466), log_dose = c(5.01, 3.401, 2.708, 2.015, 1.32176, 0.62861, -0.0645385, -1.6739764)
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#' )
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#' TransF <- FALSE
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#' Dat <- list()
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#' te <- Fitting_FUNC(dat, TransF)
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#' print(te)
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Fitting_FUNC <- function(ro_new, TransFlag = F) {
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CORro <- cor(ro_new[, 1], ro_new[, ncol(ro_new)])
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# browser()
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@@ -36,64 +36,99 @@ Fitting_FUNC <- function(ro_new, TransFlag=F) {
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if (!TransFlag) {
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startlist <- list(a = min(ro_new[, 2]), b = SLOPE, d = max(ro_new[, 2]), cs = mean(all_l$log_dose), r = 0)
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mr <- tryCatch({gsl_nls(fn = readout ~ a+(d-a)/(1+exp(b*((cs-r*isSample)-log_dose))),
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mr <- tryCatch(
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{
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gsl_nls(
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fn = readout ~ a + (d - a) / (1 + exp(b * ((cs - r * isSample) - log_dose))),
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data = all_l2,
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start = startlist, # race=T,
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control=gsl_nls_control(xtol=1e-6,ftol=1e-6, gtol=1e-6))
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control = gsl_nls_control(xtol = 1e-6, ftol = 1e-6, gtol = 1e-6)
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)
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},
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warning = function(e) {
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mr <<- "In nlsModel singular gradient matrix"
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})
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}
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)
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# Stop if singular gradient matrix
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if (is.character(mr)) return(mr)
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if (is.character(mr)) {
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return(mr)
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}
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s_mr <- tryCatch({
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s_mr <- tryCatch(
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{
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s_mr <- summary(mr)
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},
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error = function(err) {
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s_mr <- NULL
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})
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}
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)
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} else {
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startlist <- list(a = log(min(ro_new[, 2])), b = SLOPE, d = log(max(ro_new[, 2])), cs = mean(all_l$log_dose), r = 0)
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mrT <- gsl_nls(fn = log(readout) ~ a+(d-a)/(1+exp(b*((cs-r*isSample)-log_dose))),
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mrT <- gsl_nls(
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fn = log(readout) ~ a + (d - a) / (1 + exp(b * ((cs - r * isSample) - log_dose))),
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data = all_l2,
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start = startlist,
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control=gsl_nls_control(xtol=1e-6,ftol=1e-6, gtol=1e-6))
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control = gsl_nls_control(xtol = 1e-6, ftol = 1e-6, gtol = 1e-6)
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)
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s_mr <- summary(mrT)
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}
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if (!TransFlag) {
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startlistmu <- list(as=min(ro_new[,2]), bs=SLOPE, ds=max(ro_new[,2]), cs=mean(all_l$log_dose),
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at=min(ro_new[,2]), bt=SLOPE, dt=max(ro_new[,2]), r=0)
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tryCatch({
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mu <- gsl_nls(fn = readout ~ as*isRef + at*isSample + (ds*isRef + dt*isSample - as*isRef - at*isSample)/
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startlistmu <- list(
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as = min(ro_new[, 2]), bs = SLOPE, ds = max(ro_new[, 2]), cs = mean(all_l$log_dose),
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at = min(ro_new[, 2]), bt = SLOPE, dt = max(ro_new[, 2]), r = 0
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)
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tryCatch(
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{
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mu <- gsl_nls(
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fn = readout ~ as * isRef + at * isSample + (ds * isRef + dt * isSample - as * isRef - at * isSample) /
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(1 + isRef * exp(bs * (cs - log_dose)) + isSample * exp(bt * (cs - r * isSample - log_dose))),
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data = all_l,
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start = startlistmu,
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control=gsl_nls_control(xtol=1e-6,ftol=1e-6, gtol=1e-6))
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control = gsl_nls_control(xtol = 1e-6, ftol = 1e-6, gtol = 1e-6)
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)
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},
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error = function(msg) {
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return(0) })
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return(0)
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}
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)
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Sum_u <- tryCatch({ summary(mu) },
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Sum_u <- tryCatch(
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{
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summary(mu)
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},
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error = function(msg) {
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return(0) })
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return(0)
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}
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)
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} else {
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startlistmu <- list(as=log(min(ro_new[,2])), bs=SLOPE, ds=log(max(ro_new[,2])), cs=mean(all_l$log_dose),
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at=log(min(ro_new[,2])), bt=SLOPE, dt=log(max(ro_new[,2])), r=0)
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tryCatch({
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muT <- gsl_nls(fn = log(readout) ~ as*isRef + at*isSample + (ds*isRef + dt*isSample - as*isRef - at*isSample)/
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startlistmu <- list(
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as = log(min(ro_new[, 2])), bs = SLOPE, ds = log(max(ro_new[, 2])), cs = mean(all_l$log_dose),
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at = log(min(ro_new[, 2])), bt = SLOPE, dt = log(max(ro_new[, 2])), r = 0
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)
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tryCatch(
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{
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muT <- gsl_nls(
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fn = log(readout) ~ as * isRef + at * isSample + (ds * isRef + dt * isSample - as * isRef - at * isSample) /
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(1 + isRef * exp(bs * (cs - log_dose)) + isSample * exp(bt * (cs - r * isSample - log_dose))),
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data = all_l,
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start = startlistmu,
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control=gsl_nls_control(xtol=1e-6,ftol=1e-6, gtol=1e-6))
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control = gsl_nls_control(xtol = 1e-6, ftol = 1e-6, gtol = 1e-6)
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)
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},
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error = function(msg) {
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return(0) })
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return(0)
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}
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)
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Sum_u <- tryCatch({ summary(muT) },
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Sum_u <- tryCatch(
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{
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summary(muT)
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},
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error = function(msg) {
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return(0) })
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return(0)
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}
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)
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}
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if (!TransFlag) {
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pot_est <- exp(confintd(mr, "r", method = "asymptotic"))
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@@ -119,25 +154,40 @@ Fitting_FUNC <- function(ro_new, TransFlag=F) {
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#' @returns A grid object with 2 linearity plots, restricted and unrestricted model.
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#' @export
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#' @examples
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#' data.frame(R_dil1 = c(10.0651024695491, 10.9844983291817, 10.7635586089293, 10.4597656321327, 10.3898668457823, 10.8171761349909,
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#' 10.319758021908, 10.1304854046653),
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#' R_dil2 = c(10.9649145494504, 10.0202868589385, 10.8424145955735, 10.9311360356894, 10.3284659026404,
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#' 10.6890147558796, 10.3014450252305, 10.9594838595181),
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#' R_dil3 = c(10.4630510824383, 10.4566715089363, 10.2350765290036, 10.3300581874798, 10.9648088137065,
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#' 10.286893755805, 10.4856643841389, 10.5275521552307),
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#' T_dil1 = c(12.732175566336, 12.7756403995095, 12.1672539684741, 12.7060603907892, 12.8000685682832,
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#' 12.8800092157515, 12.7160581291873, 12.6996878912416),
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#' T_dil2 = c(12.3923194313831, 12.0943488144175, 12.7955302154828, 12.4825917078735, 12.6856540203788,
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#' 12.7348548498556, 12.9222470610476, 12.1186618671252),
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#' T_dil3 = c(12.7899182255274, 12.9722600411128, 12.7078445380891, 12.4913523531941, 12.1718281909609,
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#' 12.5313873615133, 12.952802332772, 12.5960321394342),
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#' log_dose = c(0, -1.09861228866811, -2.19722457733622, -3.29583686600433, -4.39444915467244,
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#' -5.49306144334055, -6.59167373200866, -7.69028602067677))
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#' data.frame(
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#' R_dil1 = c(
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#' 10.0651024695491, 10.9844983291817, 10.7635586089293, 10.4597656321327, 10.3898668457823, 10.8171761349909,
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#' 10.319758021908, 10.1304854046653
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#' ),
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#' R_dil2 = c(
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#' 10.9649145494504, 10.0202868589385, 10.8424145955735, 10.9311360356894, 10.3284659026404,
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#' 10.6890147558796, 10.3014450252305, 10.9594838595181
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#' ),
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#' R_dil3 = c(
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#' 10.4630510824383, 10.4566715089363, 10.2350765290036, 10.3300581874798, 10.9648088137065,
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#' 10.286893755805, 10.4856643841389, 10.5275521552307
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#' ),
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#' T_dil1 = c(
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#' 12.732175566336, 12.7756403995095, 12.1672539684741, 12.7060603907892, 12.8000685682832,
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#' 12.8800092157515, 12.7160581291873, 12.6996878912416
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#' ),
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#' T_dil2 = c(
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#' 12.3923194313831, 12.0943488144175, 12.7955302154828, 12.4825917078735, 12.6856540203788,
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#' 12.7348548498556, 12.9222470610476, 12.1186618671252
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#' ),
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#' T_dil3 = c(
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#' 12.7899182255274, 12.9722600411128, 12.7078445380891, 12.4913523531941, 12.1718281909609,
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#' 12.5313873615133, 12.952802332772, 12.5960321394342
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#' ),
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#' log_dose = c(
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#' 0, -1.09861228866811, -2.19722457733622, -3.29583686600433, -4.39444915467244,
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#' -5.49306144334055, -6.59167373200866, -7.69028602067677
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#' )
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#' )
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#'
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#'
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#' p <- plotSingularity(dat)
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#' print(p)
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#'
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plotSingularity <- function(dat) { # sigmoid,det_sig,
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CORdat <- cor(dat[, 1], dat[, ncol(dat)])
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# browser()
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@@ -158,8 +208,10 @@ plotSingularity <- function(dat) { #sigmoid,det_sig,
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# browser()
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pSing <- ggplot(all_l2, aes(x = log_dose, y = readout, color = factor(isRef))) +
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geom_point(shape = factor(isRef), size = 3, alpha = 0.8) +
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labs(title = paste("No 4pl fit possible"),
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color="product") +
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labs(
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title = paste("No 4pl fit possible"),
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color = "product"
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) +
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scale_color_manual(labels = c("test", "reference"), values = c("#C2173F", "#4545BA")) +
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scale_shape_manual(labels = c("test", "reference")) +
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scale_x_continuous(breaks = scales::pretty_breaks(n = 10)) +
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@@ -171,8 +223,6 @@ plotSingularity <- function(dat) { #sigmoid,det_sig,
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}
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#' Plot sigmoidal curve
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#'
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#' Returns the final plots of the 4pl function as sigmoidal lines, and the single readouts as scatter, with REF in blue and TEST in red.
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@@ -185,18 +235,18 @@ plotSingularity <- function(dat) { #sigmoid,det_sig,
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#' @returns A grid object either of the original scale or the natural log of the readouts.
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#' @export
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#' @examples
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#' dat <- data.frame(REF1=c(1547, 1620, 1644, 2504, 3426, 3512, 3401, 3787), REF2=c(1492, 1536, 1384, 2286, 3046, 3479, 3516, 3497),
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#' dat <- data.frame(
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#' REF1 = c(1547, 1620, 1644, 2504, 3426, 3512, 3401, 3787), REF2 = c(1492, 1536, 1384, 2286, 3046, 3479, 3516, 3497),
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#' REF3 = c(1468, 1827, 1558, 2252, 3002, 3349, 2945, 3665),
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#' TEST1 = c(1405, 1523, 1502, 1474, 2383, 3221, 3589, 3445), TEST2 = c(1420, 1516, 1544, 1512, 2226, 3219, 3327, 3591),
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#' TEST3=c(1399, 1376, 1588, 1475, 2148, 3083, 2942, 3466), log_dose=c(5.01,3.401,2.708,2.015,1.32176,0.62861,-0.0645385,-1.6739764))
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#' TEST3 = c(1399, 1376, 1588, 1475, 2148, 3083, 2942, 3466), log_dose = c(5.01, 3.401, 2.708, 2.015, 1.32176, 0.62861, -0.0645385, -1.6739764)
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#' )
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#' sigmoid <- c(0.7163324, 0.5636804, 10.6156340, 9.9784160, -0.7504673, -0.7108692, -3.5788141, -0.6662962)
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#' det_sig <- FALSE
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#' TransF <- FALSE
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#' Dat <- list()
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#' p <- plot_f(dat, sigmoid, det_sig, TransF)
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#' print(p)
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plot_f <- function(dat, TransFlag = F) { # sigmoid,det_sig,
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CORdat <- cor(dat[, 1], dat[, ncol(dat)])
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# browser()
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@@ -249,17 +299,21 @@ plot_f <- function(dat, TransFlag=F) { #sigmoid,det_sig,
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XasympuS <- cs + (3 / b)
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XasymplT <- cs - r - (3 / b)
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XasympuT <- cs - r + (3 / b)
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bendpoints <- c(bendREF_lower = round(Xbendl3,3), bendREF_upper=round(Xbendu3,3),
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bendpoints <- c(
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bendREF_lower = round(Xbendl3, 3), bendREF_upper = round(Xbendu3, 3),
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bendSAMPLE_lower = round(XbendlT, 3), bendSAMPLE_upper = round(XbenduT, 3),
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asympREF_lower = round(XasymplS, 3), asympREF_upper = round(XasympuS, 3),
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asympSAMPLE_lower = round(XasymplT,3), asympSAMPLE_upper=round(XasympuT,3))
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asympSAMPLE_lower = round(XasymplT, 3), asympSAMPLE_upper = round(XasympuT, 3)
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)
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Dat$bendpoints <- bendpoints
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Dat$cfordils <- cs
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# browser()
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p <- ggplot(all_l2, aes(x = log_dose, y = readout, color = factor(isRef))) +
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geom_point(shape = factor(isRef), size = 3, alpha = 0.8) +
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labs(title = paste("restricted 4pl model"),
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color="product") +
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labs(
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title = paste("restricted 4pl model"),
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color = "product"
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) +
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scale_color_manual(labels = c("test", "reference"), values = c("#C2173F", "#4545BA")) +
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scale_shape_manual(labels = c("test", "reference")) +
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scale_x_continuous(breaks = scales::pretty_breaks(n = 10)) +
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@@ -267,14 +321,22 @@ plot_f <- function(dat, TransFlag=F) { #sigmoid,det_sig,
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# theme_bw() +
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theme(axis.text = element_text(size = 14))
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p2 <- p + geom_line(data=as.data.frame(pl_df), aes(x=seq_x, y=SAMPLE), color="#C2173F",
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inherit.aes = F) +
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geom_line(data=as.data.frame(pl_df), aes(x=seq_x, y=REF), color="#4545BA",
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inherit.aes = F) +
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geom_line(data=as.data.frame(pl_df), aes(x=seq_x, y=SAMPLEtrue), color="#C2173F", linetype=2, alpha=0.4,
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inherit.aes = F) +
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geom_line(data=as.data.frame(pl_df), aes(x=seq_x, y=REFtrue), color="#4545BA", linetype=2, alpha=0.4,
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inherit.aes = F) +
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p2 <- p + geom_line(
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data = as.data.frame(pl_df), aes(x = seq_x, y = SAMPLE), color = "#C2173F",
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inherit.aes = F
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) +
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geom_line(
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data = as.data.frame(pl_df), aes(x = seq_x, y = REF), color = "#4545BA",
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inherit.aes = F
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) +
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geom_line(
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data = as.data.frame(pl_df), aes(x = seq_x, y = SAMPLEtrue), color = "#C2173F", linetype = 2, alpha = 0.4,
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inherit.aes = F
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) +
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geom_line(
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data = as.data.frame(pl_df), aes(x = seq_x, y = REFtrue), color = "#4545BA", linetype = 2, alpha = 0.4,
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inherit.aes = F
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) +
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geom_vline(xintercept = c(Xbendl3, Xbendu3), col = "#4545BA", linetype = 2) +
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geom_vline(xintercept = c(XbendlT, XbenduT), col = "#C2173F", linetype = 2) +
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geom_vline(xintercept = c(XasymplS, XasympuS), col = "#4545BABB", linetype = 3) +
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@@ -303,17 +365,23 @@ plot_f <- function(dat, TransFlag=F) { #sigmoid,det_sig,
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XbenduTrans <- cs_trans + (1.5434 / b_trans)
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XbendlTransT <- cs_trans - r_trans - (1.5434 / b_trans)
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XbenduTransT <- cs_trans - r_trans + (1.5434 / b_trans)
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bendpointsTRANS <- c(bendREF_lower = round(XbendlTrans,3), bendREF_upper=round(XbenduTrans,3),
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bendSAMPLE_lower = round(XbendlTransT,3), bendSAMPLE_upper=round(XbenduTransT,3))
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bendpointsTRANS <- c(
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bendREF_lower = round(XbendlTrans, 3), bendREF_upper = round(XbenduTrans, 3),
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bendSAMPLE_lower = round(XbendlTransT, 3), bendSAMPLE_upper = round(XbenduTransT, 3)
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)
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Dat$bendpointsTRANS <- bendpointsTRANS
|
||||
SAMPLEtrans <- a_trans + (d_trans - a_trans) / (1 + exp(b_trans * ((cs_trans - r_trans) - seq_x)))
|
||||
REFtrans <- a_trans + (d_trans - a_trans) / (1 + exp(b_trans * ((cs_trans) - seq_x)))
|
||||
|
||||
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="#C2173F",
|
||||
inherit.aes = F) +
|
||||
geom_line(data=as.data.frame(pl_df_trans), aes(x=seq_x, y=REFtrans), color="#4545BA",
|
||||
inherit.aes = F) +
|
||||
p_rt2 <- p_rt + geom_line(
|
||||
data = as.data.frame(pl_df_trans), aes(x = seq_x, y = SAMPLEtrans), color = "#C2173F",
|
||||
inherit.aes = F
|
||||
) +
|
||||
geom_line(
|
||||
data = as.data.frame(pl_df_trans), aes(x = seq_x, y = REFtrans), color = "#4545BA",
|
||||
inherit.aes = F
|
||||
) +
|
||||
geom_vline(xintercept = c(XbendlTrans, XbenduTrans), col = "#4545BA", linetype = 2) +
|
||||
geom_vline(xintercept = c(XbendlTransT, XbenduTransT), col = "#C2173F", linetype = 2) +
|
||||
theme(legend.position = "none", axis.text = element_text(size = 14))
|
||||
@@ -349,11 +417,15 @@ plot_f <- function(dat, TransFlag=F) { #sigmoid,det_sig,
|
||||
labs(title = "unrestricted 4pl model", color = "product") +
|
||||
scale_color_manual(labels = c("test", "reference"), values = c("#C2173F88", "#4545BA88")) +
|
||||
theme_bw()
|
||||
pu2 <- pu + geom_line(data=as.data.frame(pl_df2), aes(x=seq_x, y=SAMPLEu),
|
||||
color="#C2173F", inherit.aes = F) +
|
||||
geom_line(data=as.data.frame(pl_df2), aes(x=seq_x, y=REFu),
|
||||
pu2 <- pu + geom_line(
|
||||
data = as.data.frame(pl_df2), aes(x = seq_x, y = SAMPLEu),
|
||||
color = "#C2173F", inherit.aes = F
|
||||
) +
|
||||
geom_line(
|
||||
data = as.data.frame(pl_df2), aes(x = seq_x, y = REFu),
|
||||
color = "#4545BA", inherit.aes = F,
|
||||
show.legend = F)
|
||||
show.legend = F
|
||||
)
|
||||
pu2_ <- pu2 +
|
||||
theme(legend.position = "none", axis.text = element_text(size = 14))
|
||||
|
||||
@@ -378,11 +450,15 @@ plot_f <- function(dat, TransFlag=F) { #sigmoid,det_sig,
|
||||
SAMPLEu_trans <- ate_t + (dte_t - ate_t) / (1 + exp(bte_t * (cte_t - seq_x)))
|
||||
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="#C2173F", inherit.aes = F) +
|
||||
geom_line(data=as.data.frame(pl_df2u_t), aes(x=seq_x, y=REFu_trans),
|
||||
pu2_t <- putrans + geom_line(
|
||||
data = as.data.frame(pl_df2u_t), aes(x = seq_x, y = SAMPLEu_trans),
|
||||
color = "#C2173F", inherit.aes = F
|
||||
) +
|
||||
geom_line(
|
||||
data = as.data.frame(pl_df2u_t), aes(x = seq_x, y = REFu_trans),
|
||||
color = "#4545BA", inherit.aes = F,
|
||||
show.legend = F)
|
||||
show.legend = F
|
||||
)
|
||||
pu3_t <- pu2_t
|
||||
if (TransFlag) grid.arrange(p_rt2, pu3_t, nrow = 1) else grid.arrange(p2, pu2_, nrow = 1)
|
||||
}
|
||||
@@ -401,13 +477,23 @@ plot_f <- function(dat, TransFlag=F) { #sigmoid,det_sig,
|
||||
#' @returns A data-frame with readouts and natural log of concentrations.
|
||||
#' @export
|
||||
#' @examples
|
||||
#' as=3; bs=1; cs=-4; ds=10; at=3; bt=1; dt=10;r=0.0001;ct=cs-r;sd_fac=0.1; gt=1; gs=1;
|
||||
#' lnConc=c(1,0,-1,-2,-3,-4,-5,-6)
|
||||
#' as <- 3
|
||||
#' bs <- 1
|
||||
#' cs <- -4
|
||||
#' ds <- 10
|
||||
#' at <- 3
|
||||
#' bt <- 1
|
||||
#' dt <- 10
|
||||
#' r <- 0.0001
|
||||
#' ct <- cs - r
|
||||
#' sd_fac <- 0.1
|
||||
#' gt <- 1
|
||||
#' gs <- 1
|
||||
#' lnConc <- c(1, 0, -1, -2, -3, -4, -5, -6)
|
||||
#' heteroNoise <- FALSE
|
||||
#' noDilS <- 3
|
||||
#' noD <- 8
|
||||
#' Calc_DilRes(as, bs, cs, ds, at, bt, dt, r, ct, sd_fac, gt, gs, log_conc = lnConc, heteroNoise, noDilS, noD)
|
||||
|
||||
Calc_DilRes <- function(as = 3, bs = 1, cs = -4, ds = 10, at = 3, bt = 1, dt = 10, r = 0.0001, ct = cs - r,
|
||||
sd_fac = 0.1, gt = 1, gs = 1, log_conc,
|
||||
heteroNoise = FALSE, noDilSeries, noDils) {
|
||||
@@ -447,20 +533,24 @@ Calc_DilRes <- function(as=3, bs=1, cs=-4, ds=10, at=3, bt=1, dt=10,r=0.0001,ct
|
||||
#' @returns A data-frame with potency estimate, absolute CIs, test result, relative CIs.
|
||||
#' @export
|
||||
#' @examples
|
||||
#' CIRC <- data.frame(log_dose = c(-2.5,-2.5,-2.5, -3.2,-3.2,-3.2,-3.9,-3.9,-3.9,
|
||||
#' -3.2,-3.2,-3.2,-3.9,-3.9,-3.9,-4.7,-4.7,-4.7),
|
||||
#' replname= c("R_dil1","R_dil1","R_dil1", "R_dil2","R_dil2","R_dil2", "R_dil3","R_dil3","R_dil3",
|
||||
#' "T_dil1","T_dil1","T_dil1", "T_dil2","T_dil2","T_dil2", "T_dil3","T_dil3","T_dil3"),
|
||||
#' CIRC <- data.frame(
|
||||
#' log_dose = c(
|
||||
#' -2.5, -2.5, -2.5, -3.2, -3.2, -3.2, -3.9, -3.9, -3.9,
|
||||
#' -3.2, -3.2, -3.2, -3.9, -3.9, -3.9, -4.7, -4.7, -4.7
|
||||
#' ),
|
||||
#' replname = c(
|
||||
#' "R_dil1", "R_dil1", "R_dil1", "R_dil2", "R_dil2", "R_dil2", "R_dil3", "R_dil3", "R_dil3",
|
||||
#' "T_dil1", "T_dil1", "T_dil1", "T_dil2", "T_dil2", "T_dil2", "T_dil3", "T_dil3", "T_dil3"
|
||||
#' ),
|
||||
#' readout = c(72.1, 75.8, 76.04, 59.8, 61, 62.7, 43.6, 45, 41.5, 53.5, 62.2, 65.9, 48.3, 43.8, 43.14, 28.17, 29.2, 31.2),
|
||||
#' isRef = c(rep(1, 9), rep(0, 9)),
|
||||
#' isSample = c(rep(0,9), rep(1,9)))
|
||||
#' isSample = c(rep(0, 9), rep(1, 9))
|
||||
#' )
|
||||
#' Lim <- c(rep(0, 8), 70, 130) # only Lim 9 and 10 relevant
|
||||
#' PureErrF <- TRUE
|
||||
#'
|
||||
#'
|
||||
#' LinPotTab(circles = CIRC, Lim, PureErrF)
|
||||
|
||||
|
||||
LinPotTab <- function(circles, Lim, PureErrFlag) {
|
||||
circ_ABl <- circles
|
||||
circ_Al <- circ_ABl[circ_ABl$isSample == 1, ]
|
||||
@@ -468,11 +558,14 @@ LinPotTab <- function(circles, Lim, PureErrFlag) {
|
||||
# restr CSSI model
|
||||
modAB <- lm(readout ~ log_dose + isSample, circ_ABl)
|
||||
coeffs <- modAB$coefficients
|
||||
SU_modAB <- tryCatch({
|
||||
SU_modAB <- tryCatch(
|
||||
{
|
||||
SU_modAB <- summary(modAB)
|
||||
}, error = function(msg) {
|
||||
},
|
||||
error = function(msg) {
|
||||
return(NA)
|
||||
})
|
||||
}
|
||||
)
|
||||
# Intercept diff/slope modAB
|
||||
linPot <- exp(modAB$coefficients[3] / modAB$coefficients[2])
|
||||
|
||||
@@ -504,8 +597,10 @@ LinPotTab <- function(circles, Lim, PureErrFlag) {
|
||||
relLinpotCI <- ExpLinPot / linPot * 100
|
||||
if (relLinpotCI[2] > Lim[[9]] & relLinpotCI[3] < Lim[[10]]) test_potCI <- 0 else test_potCI <- 1
|
||||
|
||||
pottab <- cbind(round(linPot*100,3), round(ExpLinPot[2]*100,3), round(ExpLinPot[3]*100,3),
|
||||
round(test_potCI,3), round(relLinpotCI[2],3),round(relLinpotCI[3],3))
|
||||
pottab <- cbind(
|
||||
round(linPot * 100, 3), round(ExpLinPot[2] * 100, 3), round(ExpLinPot[3] * 100, 3),
|
||||
round(test_potCI, 3), round(relLinpotCI[2], 3), round(relLinpotCI[3], 3)
|
||||
)
|
||||
colnames(pottab) <- c("Potency", "lower 95%CI", "upper 95%CI", "test_result", "lowerRel95%CI", "upperRel95%CI")
|
||||
return(pottab)
|
||||
}
|
||||
@@ -524,23 +619,25 @@ LinPotTab <- function(circles, Lim, PureErrFlag) {
|
||||
#' 4) summary of restricted linear model.
|
||||
#' @export
|
||||
#' @examples
|
||||
#' dat <- data.frame(R_dil1 =c(10221, 18258, 31993, 49336, 68332, 83527, 95584, 102229),
|
||||
#' dat <- data.frame(
|
||||
#' R_dil1 = c(10221, 18258, 31993, 49336, 68332, 83527, 95584, 102229),
|
||||
#' R_dil2 = c(10136, 19078, 31925, 49003, 68034, 83776, 95495, 101608),
|
||||
#' T_dil1 = c(10830, 19891, 33915, 52131, 70617, 85784, 95937, 102791),
|
||||
#' T_dil2 = c(11169, 20153, 34007, 52179, 69962, 85543, 96439, 102655),
|
||||
#' log_dose=c( -1.2029, -1.89712, -2.590267, -3.2834, -3.97656, -4.66917, -5.362323, -6.05334))
|
||||
#' CIRC <- data.frame(log_dose=c( -2.590267, -2.590267, -3.2834 , -3.2834, -3.97656, -3.97656, -2.590267, -2.590267,-3.2834, -3.2834, -3.97656, -3.97656),
|
||||
#' log_dose = c(-1.2029, -1.89712, -2.590267, -3.2834, -3.97656, -4.66917, -5.362323, -6.05334)
|
||||
#' )
|
||||
#' CIRC <- data.frame(
|
||||
#' log_dose = c(-2.590267, -2.590267, -3.2834, -3.2834, -3.97656, -3.97656, -2.590267, -2.590267, -3.2834, -3.2834, -3.97656, -3.97656),
|
||||
#' replname = c("R_dil1", "R_dil2", "R_dil1", "R_dil2", "R_dil1", "R_dil2", "T_dil1", "T_dil2", "T_dil1", "T_dil2", "T_dil1", "T_dil2"),
|
||||
#' readout = c(31993, 31925, 49336, 49003, 68332, 68034, 33915, 34007, 52131, 52179, 70617, 69962),
|
||||
#' isRef = c(rep(1, 6), rep(0, 6)),
|
||||
#' isSample = c(rep(0,6), rep(1,6)))
|
||||
#' isSample = c(rep(0, 6), rep(1, 6))
|
||||
#' )
|
||||
#' Lim <- c(rep(0, 8), 70, 130) # only Lim 9 and 10 relevant
|
||||
#' PureErrF <- TRUE
|
||||
#'
|
||||
#'
|
||||
#' ANOVAlintests(ro_new, circles, Lim, PureErrF)
|
||||
|
||||
|
||||
ANOVAlintests <- function(ro_new, circles, Lim, PureErrFlag) {
|
||||
all_l <- melt(data.frame(ro_new), id.vars = "log_dose", variable.name = "replname", value.name = "readout")
|
||||
isRef <- rep(c(1, 0), 1, each = nrow(all_l) / 2)
|
||||
@@ -594,11 +691,14 @@ ANOVAlintests <- function(ro_new, circles, Lim, PureErrFlag) {
|
||||
if (PureErrFlag) {
|
||||
FitAnova <- anova(lm(readout ~ factor(log_dose) * isSample, circ_ABl))
|
||||
meanPureErr <- FitAnova[4, 3]
|
||||
SU_modAB <- tryCatch({
|
||||
SU_modAB <- tryCatch(
|
||||
{
|
||||
SU_modAB <- summary(modAB)
|
||||
}, error = function(msg) {
|
||||
},
|
||||
error = function(msg) {
|
||||
return(NA)
|
||||
})
|
||||
}
|
||||
)
|
||||
if (length(SU_modAB) > 1) s_modABcoeffs <- summary(modAB)$coefficients
|
||||
|
||||
DFsPure <- FitAnova[4, 1]
|
||||
@@ -626,7 +726,6 @@ ANOVAlintests <- function(ro_new, circles, Lim, PureErrFlag) {
|
||||
|
||||
SSRes <- SSE
|
||||
dfRes <- dfPureE
|
||||
|
||||
} else {
|
||||
SSRes <- RSS
|
||||
dfRes <- dfRMSE
|
||||
@@ -671,7 +770,9 @@ ANOVAlintests <- function(ro_new, circles, Lim, PureErrFlag) {
|
||||
if (is.na(F_nonlin)) F_nonlin <- 0
|
||||
if (F_nonlin > 0) {
|
||||
p_F_nonlin <- round(pf(F_nonlin, 2, dfPureE, lower.tail = F), 5)
|
||||
} else { p_F_nonlin <- "SSnonlin neg or 0"; }
|
||||
} else {
|
||||
p_F_nonlin <- "SSnonlin neg or 0"
|
||||
}
|
||||
|
||||
# significances
|
||||
F_regr <- (SSreg / 1) / (SSRes / dfRes)
|
||||
@@ -683,28 +784,44 @@ ANOVAlintests <- function(ro_new, circles, Lim, PureErrFlag) {
|
||||
p_F_nonp <- round(pf(F_nonpar, 1, dfRes, lower.tail = F), 3)
|
||||
p_F_LoF <- p_F_nonlin
|
||||
|
||||
res_tab_lin <- data.frame(test = c("F-test on sign. of regression", "F_test on non-lin",
|
||||
res_tab_lin <- data.frame(
|
||||
test = c(
|
||||
"F-test on sign. of regression", "F_test on non-lin",
|
||||
"F-test on R^2 A", "F_test on R^2 B",
|
||||
"F-test on slope A", "F-test on slope B",
|
||||
"F-test on non-parallelism","F-test on preparation"),
|
||||
test_results = c(ifelse(p_F_regr<0.05,0,1),ifelse(p_F_nonlin<0.05,1,0),
|
||||
"F-test on non-parallelism", "F-test on preparation"
|
||||
),
|
||||
test_results = c(
|
||||
ifelse(p_F_regr < 0.05, 0, 1), ifelse(p_F_nonlin < 0.05, 1, 0),
|
||||
ifelse(pFR2_A < 0.05, 1, 0), ifelse(pFR2_B < 0.05, 1, 0),
|
||||
ifelse(p_F_slope_A < 0.05, 0, 1), ifelse(p_F_slope_B < 0.05, 0, 1),
|
||||
ifelse(p_F_nonp<0.05,1,0),ifelse(p_F_prep<0.05,0,1)),
|
||||
estimate = c(p_F_regr, p_F_nonlin,pFR2_A,pFR2_B,p_F_slope_A,
|
||||
p_F_slope_B,p_F_nonp,p_F_prep),
|
||||
Source = c("Treatment","Preparation","Regression","Non-parallelism",
|
||||
"Resid Error","Non-linearity","Pure error", "Total"),
|
||||
ifelse(p_F_nonp < 0.05, 1, 0), ifelse(p_F_prep < 0.05, 0, 1)
|
||||
),
|
||||
estimate = c(
|
||||
p_F_regr, p_F_nonlin, pFR2_A, pFR2_B, p_F_slope_A,
|
||||
p_F_slope_B, p_F_nonp, p_F_prep
|
||||
),
|
||||
Source = c(
|
||||
"Treatment", "Preparation", "Regression", "Non-parallelism",
|
||||
"Resid Error", "Non-linearity", "Pure error", "Total"
|
||||
),
|
||||
df = c(dfTreat, 1, 1, 1, dfRMSE, 2, dfPureE, lenCirc - 1),
|
||||
SumSquares = c(round(SStreat,5),round(SSprep,5),round(SSreg,5),
|
||||
SumSquares = c(
|
||||
round(SStreat, 5), round(SSprep, 5), round(SSreg, 5),
|
||||
round(SSnonpar, 5), round(RSS, 5), round(SSnonlin, 5),
|
||||
round(SSE,5),round(SStot,5)),
|
||||
MS = c(round(SStreat/dfTreat,5),round(SSprep,5),round(SSreg,5),
|
||||
round(SSE, 5), round(SStot, 5)
|
||||
),
|
||||
MS = c(
|
||||
round(SStreat / dfTreat, 5), round(SSprep, 5), round(SSreg, 5),
|
||||
round(SSnonpar, 5), round(RSS / dfRMSE, 5), round(SSnonlin / 2, 5),
|
||||
round(SSE/dfPureE,5),round(SStot/dfTotal,5)),
|
||||
"F-value" = c(round(F_treat,5), round(F_prep,5),round(F_regr,5),
|
||||
round(F_nonpar,5),"",round(F_nonlin,5),"",""),
|
||||
"p-value" = c(p_F_treat, p_F_prep, p_F_regr, p_F_nonp, "", p_F_LoF, "",""))
|
||||
round(SSE / dfPureE, 5), round(SStot / dfTotal, 5)
|
||||
),
|
||||
"F-value" = c(
|
||||
round(F_treat, 5), round(F_prep, 5), round(F_regr, 5),
|
||||
round(F_nonpar, 5), "", round(F_nonlin, 5), "", ""
|
||||
),
|
||||
"p-value" = c(p_F_treat, p_F_prep, p_F_regr, p_F_nonp, "", p_F_LoF, "", "")
|
||||
)
|
||||
RET <- list(res_tab_lin, su_modU2, SlopeDiffCI, su_mod2)
|
||||
return(RET)
|
||||
}
|
||||
@@ -730,20 +847,21 @@ ANOVAlintests <- function(ro_new, circles, Lim, PureErrFlag) {
|
||||
#' sigmoid <- c(10.0, 10.0, 110.0, 110.0, 1.0, 1.0, -3.5, 0.0)
|
||||
#' indS <- 3
|
||||
#' indT <- 3
|
||||
#' pl_df <- data.frame(lnC=c(-1.203973,-1.897120 ,-2.590267,-3.283414,-3.976562,-4.669176,-5.362323,-6.053340),
|
||||
#' pl_df <- data.frame(
|
||||
#' lnC = c(-1.203973, -1.897120, -2.590267, -3.283414, -3.976562, -4.669176, -5.362323, -6.053340),
|
||||
#' plotS = c(113.772511, 97.668371, 81.564231, 65.460091, 49.355952, 33.264200, 17.160060, 1.105405),
|
||||
#' plotT = c(114.213375,97.588663,80.963951,64.339239,47.714527,31.102604,14.477892,-2.095735))
|
||||
#' plotT = c(114.213375, 97.588663, 80.963951, 64.339239, 47.714527, 31.102604, 14.477892, -2.095735)
|
||||
#' )
|
||||
#'
|
||||
#'
|
||||
#' PlotLinPLA_FUNC(circle, sigmoid, all_l2, pl_df, indS, indT)
|
||||
|
||||
|
||||
PlotLinPLA_FUNC <- function(circle, sigmoid, all_l2, pl_df, indS, indT) {
|
||||
# browser()
|
||||
mLin <- gsl_nls(readout ~ (intS + r) * isSample + intS * isRef + k * log_dose,
|
||||
data = circle,
|
||||
start = list(intS = 0, k = 1, r = 0),
|
||||
control = gsl_nls_control(xtol=1e-10,ftol=1e-10,gtol=1e-10))
|
||||
control = gsl_nls_control(xtol = 1e-10, ftol = 1e-10, gtol = 1e-10)
|
||||
)
|
||||
# alternativ: modAB <- lm(readout ~ log_dose+isSample, circle)
|
||||
sum_mLin <- summary(mLin)
|
||||
|
||||
@@ -760,8 +878,6 @@ PlotLinPLA_FUNC <-function(circle, sigmoid, all_l2, pl_df, indS, indT) {
|
||||
}
|
||||
|
||||
|
||||
|
||||
|
||||
p <- ggplot(all_l2, aes(x = log_dose, y = readout, color = factor(isRef))) +
|
||||
geom_point(size = 2) +
|
||||
# labs(title=paste("linear regression model", indS,indT), color="product") +
|
||||
@@ -770,18 +886,36 @@ PlotLinPLA_FUNC <-function(circle, sigmoid, all_l2, pl_df, indS, indT) {
|
||||
scale_x_continuous(breaks = scales::pretty_breaks(n = 10)) +
|
||||
scale_y_continuous(breaks = scales::pretty_breaks(n = 10)) +
|
||||
theme_bw()
|
||||
p2 <- p + geom_line(data=pl_df,aes(x=lnC,y=plotS),color="#4545BA",
|
||||
inherit.aes = F) +
|
||||
geom_line(data=pl_df,aes(x=lnC,y=plotT),color="#C2173F",
|
||||
inherit.aes = F) +
|
||||
{if (!is.null(truePL_df)) geom_line(data=data.frame(truePL_df),aes(x=seq_x,y=SAMPLEtrue),color="#C2173F", linetype=2,alpha=0.4,
|
||||
inherit.aes = F) } +
|
||||
{if (!is.null(truePL_df)) geom_line(data=data.frame(truePL_df),aes(x=seq_x,y=REFtrue),color="#4545BA", linetype=2,alpha=0.4,
|
||||
inherit.aes = F)} +
|
||||
p2 <- p + geom_line(
|
||||
data = pl_df, aes(x = lnC, y = plotS), color = "#4545BA",
|
||||
inherit.aes = F
|
||||
) +
|
||||
geom_line(
|
||||
data = pl_df, aes(x = lnC, y = plotT), color = "#C2173F",
|
||||
inherit.aes = F
|
||||
) +
|
||||
{
|
||||
if (!is.null(truePL_df)) {
|
||||
geom_line(
|
||||
data = data.frame(truePL_df), aes(x = seq_x, y = SAMPLEtrue), color = "#C2173F", linetype = 2, alpha = 0.4,
|
||||
inherit.aes = F
|
||||
)
|
||||
}
|
||||
} +
|
||||
{
|
||||
if (!is.null(truePL_df)) {
|
||||
geom_line(
|
||||
data = data.frame(truePL_df), aes(x = seq_x, y = REFtrue), color = "#4545BA", linetype = 2, alpha = 0.4,
|
||||
inherit.aes = F
|
||||
)
|
||||
}
|
||||
} +
|
||||
labs(title = paste("unrestricted PLA model"), subtitle = paste("Regression starts for reference sample:", indS, "for test sample:", indT)) +
|
||||
theme(legend.position = "none", axis.text = element_text(size = 14))
|
||||
p3 <- p2 + geom_point(circle, mapping=aes(x=log_dose, y=readout, shape=factor(isRef),
|
||||
size=5,alpha=0.2), col=c("black"), inherit.aes = FALSE) +
|
||||
p3 <- p2 + geom_point(circle, mapping = aes(
|
||||
x = log_dose, y = readout, shape = factor(isRef),
|
||||
size = 5, alpha = 0.2
|
||||
), col = c("black"), inherit.aes = FALSE) +
|
||||
scale_shape_manual(labels = c("test", "reference"), values = c(21, 21))
|
||||
# fit intercept for test and ref and common slope
|
||||
|
||||
@@ -790,25 +924,44 @@ PlotLinPLA_FUNC <-function(circle, sigmoid, all_l2, pl_df, indS, indT) {
|
||||
pl_restT <- sum_mLin$coefficients[1, 1] + sum_mLin$coefficients[3, 1] + sum_mLin$coefficients[2, 1] * log_dose
|
||||
pl_rest <- data.frame(lnC = log_dose, plotS = pl_restS, plotT = pl_restT)
|
||||
|
||||
pr2 <- p + geom_line(data=pl_rest,aes(x=lnC,y=plotS),color="#4545BA",
|
||||
inherit.aes = F) +
|
||||
geom_line(data=pl_rest,aes(x=lnC,y=plotT),color="#C2173F",
|
||||
inherit.aes = F) +
|
||||
{if (!is.null(truePL_df)) geom_line(data=data.frame(truePL_df),aes(x=seq_x,y=SAMPLEtrue),color="#C2173F", linetype=2,alpha=0.4,
|
||||
inherit.aes = F) } +
|
||||
{if (!is.null(truePL_df)) geom_line(data=data.frame(truePL_df),aes(x=seq_x,y=REFtrue),color="#4545BA", linetype=2,alpha=0.4,
|
||||
inherit.aes = F) } +
|
||||
labs(title = paste("restricted linear regression model"),
|
||||
subtitle = paste("Regression on highlighted points")) +
|
||||
pr2 <- p + geom_line(
|
||||
data = pl_rest, aes(x = lnC, y = plotS), color = "#4545BA",
|
||||
inherit.aes = F
|
||||
) +
|
||||
geom_line(
|
||||
data = pl_rest, aes(x = lnC, y = plotT), color = "#C2173F",
|
||||
inherit.aes = F
|
||||
) +
|
||||
{
|
||||
if (!is.null(truePL_df)) {
|
||||
geom_line(
|
||||
data = data.frame(truePL_df), aes(x = seq_x, y = SAMPLEtrue), color = "#C2173F", linetype = 2, alpha = 0.4,
|
||||
inherit.aes = F
|
||||
)
|
||||
}
|
||||
} +
|
||||
{
|
||||
if (!is.null(truePL_df)) {
|
||||
geom_line(
|
||||
data = data.frame(truePL_df), aes(x = seq_x, y = REFtrue), color = "#4545BA", linetype = 2, alpha = 0.4,
|
||||
inherit.aes = F
|
||||
)
|
||||
}
|
||||
} +
|
||||
labs(
|
||||
title = paste("restricted linear regression model"),
|
||||
subtitle = paste("Regression on highlighted points")
|
||||
) +
|
||||
theme(legend.position = "none", axis.text = element_text(size = 14))
|
||||
pr3 <- pr2 + geom_point(circle, mapping=aes(x=log_dose, y=readout, shape=factor(isRef),
|
||||
size=5, alpha=0.2), col=c("black"), inherit.aes = FALSE) +
|
||||
pr3 <- pr2 + geom_point(circle, mapping = aes(
|
||||
x = log_dose, y = readout, shape = factor(isRef),
|
||||
size = 5, alpha = 0.2
|
||||
), col = c("black"), inherit.aes = FALSE) +
|
||||
scale_shape_manual(labels = c("test", "reference"), values = c(21, 21))
|
||||
return(grid.arrange(p3, pr3, nrow = 1))
|
||||
}
|
||||
|
||||
|
||||
|
||||
#' Calculates the potency of 4PL PLA of all models model
|
||||
#'
|
||||
#' The gradient method is used for calculating the potency for a restricted model, an unrestricteed model,
|
||||
@@ -822,17 +975,17 @@ PlotLinPLA_FUNC <-function(circle, sigmoid, all_l2, pl_df, indS, indT) {
|
||||
#' 4) summary of restricted linear model.
|
||||
#' @export
|
||||
#' @examples
|
||||
#' ro_new <- data.frame(R_dil1 =c(10221, 18258, 31993, 49336, 68332, 83527, 95584, 102229),
|
||||
#' ro_new <- data.frame(
|
||||
#' R_dil1 = c(10221, 18258, 31993, 49336, 68332, 83527, 95584, 102229),
|
||||
#' R_dil2 = c(10136, 19078, 31925, 49003, 68034, 83776, 95495, 101608),
|
||||
#' T_dil1 = c(10830, 19891, 33915, 52131, 70617, 85784, 95937, 102791),
|
||||
#' T_dil2 = c(11169, 20153, 34007, 52179, 69962, 85543, 96439, 102655),
|
||||
#' log_dose=c( -1.2029, -1.89712, -2.590267, -3.2834, -3.97656, -4.66917, -5.362323, -6.05334))
|
||||
#' log_dose = c(-1.2029, -1.89712, -2.590267, -3.2834, -3.97656, -4.66917, -5.362323, -6.05334)
|
||||
#' )
|
||||
#' PureErrF <- TRUE
|
||||
#'
|
||||
#'
|
||||
#' pot4plFUNC(ro_new, PureErrF)
|
||||
|
||||
|
||||
pot4plFUNC <- function(ro_new, PureErrFlag) {
|
||||
all_l <- melt(data.frame(ro_new), id.vars = "log_dose", variable.name = "replname", value.name = "readout")
|
||||
isRef <- rep(c(1, 0), 1, each = nrow(all_l) / 2)
|
||||
@@ -869,8 +1022,10 @@ pot4plFUNC <- function(ro_new, PureErrFlag) {
|
||||
# V_V <- VCOV/SU_mr$sigma^2
|
||||
V_V <- SU_mr$cov.unscaled
|
||||
SEsPure <- sqrt(diag(V_V) * meanPureErr)
|
||||
pot_est <- c(exp(SU_mrCoeff['r',1]),exp(SU_mrCoeff['r',1]-qt(0.975,DFsPure)*SEsPure['r']),
|
||||
exp(SU_mrCoeff['r',1]+qt(0.975,DFsPure)*SEsPure['r']))
|
||||
pot_est <- c(
|
||||
exp(SU_mrCoeff["r", 1]), exp(SU_mrCoeff["r", 1] - qt(0.975, DFsPure) * SEsPure["r"]),
|
||||
exp(SU_mrCoeff["r", 1] + qt(0.975, DFsPure) * SEsPure["r"])
|
||||
)
|
||||
# unrestricted
|
||||
SU_mu <- FITs[[2]]
|
||||
s_muCoeff <- SU_mu$coefficients
|
||||
@@ -878,8 +1033,10 @@ pot4plFUNC <- function(ro_new, PureErrFlag) {
|
||||
# VCOVu <- vcov(mu)
|
||||
V_Vu <- SU_mu$cov.unscaled
|
||||
SEsPureU <- sqrt(diag(V_Vu) * meanPureErr)
|
||||
potU_est <- c(exp(s_muCoeff['r',1]),exp(s_muCoeff['r',1]-qt(0.975,DFsPure)*SEsPureU['r']),
|
||||
+ exp(s_muCoeff['r',1]+qt(0.975,DFsPure)*SEsPureU['r']))
|
||||
potU_est <- c(
|
||||
exp(s_muCoeff["r", 1]), exp(s_muCoeff["r", 1] - qt(0.975, DFsPure) * SEsPureU["r"]),
|
||||
+exp(s_muCoeff["r", 1] + qt(0.975, DFsPure) * SEsPureU["r"])
|
||||
)
|
||||
} # PureErrFlag
|
||||
|
||||
FITstrans <- Fitting_FUNC(ro_new, TransFlag = TRUE)
|
||||
@@ -918,13 +1075,14 @@ pot4plFUNC <- function(ro_new, PureErrFlag) {
|
||||
#' @returns A data-frame with the lower and upper CI in anti-log form.
|
||||
#' @export
|
||||
#' @examples
|
||||
#' xs=2; xt=3.2; se_xt=0.34;se_xs=0.23; DFs=32-16
|
||||
#' xs <- 2
|
||||
#' xt <- 3.2
|
||||
#' se_xt <- 0.34
|
||||
#' se_xs <- 0.23
|
||||
#' DFs <- 32 - 16
|
||||
#'
|
||||
#'
|
||||
#' ParamCI_F(xt, xs, se_xt, se_xs, CoVar, DFs, Conf = 0.975)
|
||||
|
||||
|
||||
|
||||
ParamCI_F <- function(xt, xs, se_xt, se_xs, CoVar, DFs, Conf = 0.975) {
|
||||
log_xs <- log(abs(xs))
|
||||
log_xt <- log(abs(xt))
|
||||
@@ -951,18 +1109,17 @@ ParamCI_F <- function(xt,xs,se_xt, se_xs, CoVar,DFs, Conf=0.975) {
|
||||
#' @export
|
||||
#' @examples
|
||||
#'
|
||||
#' dat <- data.frame(REF1=c(1547, 1620, 1644, 2504, 3426, 3512, 3401, 3787), REF2=c(1492, 1536, 1384, 2286, 3046, 3479, 3516, 3497),
|
||||
#' dat <- data.frame(
|
||||
#' REF1 = c(1547, 1620, 1644, 2504, 3426, 3512, 3401, 3787), REF2 = c(1492, 1536, 1384, 2286, 3046, 3479, 3516, 3497),
|
||||
#' REF3 = c(1468, 1827, 1558, 2252, 3002, 3349, 2945, 3665),
|
||||
#' TEST1 = c(1405, 1523, 1502, 1474, 2383, 3221, 3589, 3445), TEST2 = c(1420, 1516, 1544, 1512, 2226, 3219, 3327, 3591),
|
||||
#' TEST3=c(1399, 1376, 1588, 1475, 2148, 3083, 2942, 3466), log_dose=c(5.01,3.401,2.708,2.015,1.32176,0.62861,-0.0645385,-1.6739764))
|
||||
#' TEST3 = c(1399, 1376, 1588, 1475, 2148, 3083, 2942, 3466), log_dose = c(5.01, 3.401, 2.708, 2.015, 1.32176, 0.62861, -0.0645385, -1.6739764)
|
||||
#' )
|
||||
#' Lim <- c(-1, 1, 0.005, 2, 0.5, 2, 0.5, 2, 75, 133, 75, 133)
|
||||
#' PureErrF <- FALSE
|
||||
#'
|
||||
#' tests_FUNC(ro_new, Lim, PureErrF)
|
||||
|
||||
|
||||
tests_FUNC <- function(ro_new, Lim, PureErrFlag) {
|
||||
|
||||
all_l <- melt(data.frame(ro_new), 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)
|
||||
@@ -972,7 +1129,9 @@ tests_FUNC <- function(ro_new, Lim, PureErrFlag) {
|
||||
all_l$readout[all_l$readout < 0] <- 0.01
|
||||
# browser()
|
||||
FITs <- Fitting_FUNC(ro_new = ro_new, TransFlag = FALSE)
|
||||
if (is.character(FITs)) return(FITs) # if singularity
|
||||
if (is.character(FITs)) {
|
||||
return(FITs)
|
||||
} # if singularity
|
||||
|
||||
POTr_CI <- FITs[[3]][2:3]
|
||||
potAll2 <- FITs[[3]]
|
||||
@@ -991,7 +1150,6 @@ tests_FUNC <- function(ro_new, Lim, PureErrFlag) {
|
||||
DFsPure <- FitAnova[4, 1]
|
||||
|
||||
|
||||
|
||||
testPOTr <- logical()
|
||||
if (POTr_CI[1] * 100 > Lim[[9]] & POTr_CI[2] * 100 < Lim[[10]]) testPOTr <- 0 else testPOTr <- 1
|
||||
|
||||
@@ -1024,7 +1182,13 @@ tests_FUNC <- function(ro_new, Lim, PureErrFlag) {
|
||||
PureMSE <- SSE / SSE_df
|
||||
RMSE_pure <- sqrt(PureMSE)
|
||||
## non-lin = LoF
|
||||
if (PureErrFlag) { ERR <- PureMSE; ERR_df <- SSE_df } else { ERR <- MSEunr; ERR_df <- RSS_df }
|
||||
if (PureErrFlag) {
|
||||
ERR <- PureMSE
|
||||
ERR_df <- SSE_df
|
||||
} else {
|
||||
ERR <- MSEunr
|
||||
ERR_df <- RSS_df
|
||||
}
|
||||
SSnonlin <- sum((predict(lm(readout ~ factor(Conc) * isSample, all_l)) - predPotU)^2)
|
||||
LoF_df <- FitAnova[1, 1] + FitAnova[2, 1]
|
||||
F_regr <- (SSregr / AnovaDFs[3]) / ERR
|
||||
@@ -1032,7 +1196,9 @@ tests_FUNC <- function(ro_new, Lim, PureErrFlag) {
|
||||
if (ncol(ro_new) < 4) F_nonlin <- 0 else F_nonlin <- (SSnonlin / AnovaDFs[6]) / ERR
|
||||
if (F_nonlin > 0) {
|
||||
p_F_nonlin <- round(pf(F_nonlin, AnovaDFs[6], ERR_df, lower.tail = F), 5)
|
||||
} else { p_F_nonlin <- "SSnonlin neg or single dilutions" }
|
||||
} else {
|
||||
p_F_nonlin <- "SSnonlin neg or single dilutions"
|
||||
}
|
||||
|
||||
test_a <- test_b <- test_d <- test_ad <- logical()
|
||||
|
||||
@@ -1122,10 +1288,16 @@ tests_FUNC <- function(ro_new, Lim, PureErrFlag) {
|
||||
|
||||
Dat$up_lowAs <- abs(ds - as)
|
||||
|
||||
lowerCIlowerA <- lAsCI2[1]; lowerCIupperA <- uAsCI2[1]; upperCIlowerA <- lAsCI2[2]; upperCIupperA <- uAsCI2[2]
|
||||
test_lowA <- test_d; test_uppA <- test_a
|
||||
lowerCIlowerA <- lAsCI2[1]
|
||||
lowerCIupperA <- uAsCI2[1]
|
||||
upperCIlowerA <- lAsCI2[2]
|
||||
upperCIupperA <- uAsCI2[2]
|
||||
test_lowA <- test_d
|
||||
test_uppA <- test_a
|
||||
# browser()
|
||||
res_tab <- data.frame(test= c("F-test on sign. of regression*",
|
||||
res_tab <- data.frame(
|
||||
test = c(
|
||||
"F-test on sign. of regression*",
|
||||
"EQ test on lower asymptotes difference",
|
||||
"EQ test ratio of lower asymptotes",
|
||||
"EQ test ratio of Hill slopes",
|
||||
@@ -1133,19 +1305,28 @@ tests_FUNC <- function(ro_new, Lim, PureErrFlag) {
|
||||
"F-test on non-linearity*",
|
||||
"EQ test ratio of asymptote difference",
|
||||
"geom. rel. CI restr. model",
|
||||
"geom. rel. CI unrestr. model"),
|
||||
test_results = c(ifelse(p_F_regr<0.05,0,1), test_la_diff, test_lowA, test_b, test_uppA,
|
||||
"geom. rel. CI unrestr. model"
|
||||
),
|
||||
test_results = c(
|
||||
ifelse(p_F_regr < 0.05, 0, 1), test_la_diff, test_lowA, test_b, test_uppA,
|
||||
ifelse(p_F_nonlin > 1, 1, ifelse(p_F_nonlin < 0.05, 1, 0)), test_ad,
|
||||
testPOTr, test_c),
|
||||
estimate = c(round(p_F_regr, 3), round(lAs_diff, 5),
|
||||
testPOTr, test_c
|
||||
),
|
||||
estimate = c(
|
||||
round(p_F_regr, 3), round(lAs_diff, 5),
|
||||
estLowA, round(bs / bt, 5), estUppA, p_F_nonlin,
|
||||
round(dt_at/ds_as, 5), round(potAll2[1]*100,2),round(potAllU2[1]*100,2)),
|
||||
round(dt_at / ds_as, 5), round(potAll2[1] * 100, 2), round(potAllU2[1] * 100, 2)
|
||||
),
|
||||
lower_limit = c("-", Lim[[1]], Lim[[3]], Lim[[5]], Lim[[7]], "-", Lim[[11]], Lim[[9]], Lim[[9]]),
|
||||
upper_limit = c("-", Lim[[2]], Lim[[4]], Lim[[6]], Lim[[8]], "-", Lim[[12]], Lim[[10]], Lim[[10]]),
|
||||
lower_CI = c(RMSE_r, round(lCI_laDiff,3), round(lAsCI2[1],5), round(slopeCI2[1],5),
|
||||
round(uAsCI2[1],5), "-", round(AsDiffCI2[1],5), round(potAll2[2],2), round(potAllU2[2],2)),
|
||||
upper_CI = c(RMSE_pure, round(uCI_laDiff,3), round(lAsCI2[2],5), round(slopeCI2[2],5),
|
||||
round(uAsCI2[2],5), "-", round(AsDiffCI2[2],5), round(potAll2[3],2), round(potAllU2[3],2))
|
||||
lower_CI = c(
|
||||
RMSE_r, round(lCI_laDiff, 3), round(lAsCI2[1], 5), round(slopeCI2[1], 5),
|
||||
round(uAsCI2[1], 5), "-", round(AsDiffCI2[1], 5), round(potAll2[2], 2), round(potAllU2[2], 2)
|
||||
),
|
||||
upper_CI = c(
|
||||
RMSE_pure, round(uCI_laDiff, 3), round(lAsCI2[2], 5), round(slopeCI2[2], 5),
|
||||
round(uAsCI2[2], 5), "-", round(AsDiffCI2[2], 5), round(potAll2[3], 2), round(potAllU2[3], 2)
|
||||
)
|
||||
)
|
||||
return(res_tab)
|
||||
}
|
||||
@@ -1160,15 +1341,15 @@ tests_FUNC <- function(ro_new, Lim, PureErrFlag) {
|
||||
#' @export
|
||||
#' @examples
|
||||
#'
|
||||
#' ro_new <- data.frame(REF1=c(1547, 1620, 1644, 2504, 3426, 3512, 3401, 3787), REF2=c(1492, 1536, 1384, 2286, 3046, 3479, 3516, 3497),
|
||||
#' ro_new <- data.frame(
|
||||
#' REF1 = c(1547, 1620, 1644, 2504, 3426, 3512, 3401, 3787), REF2 = c(1492, 1536, 1384, 2286, 3046, 3479, 3516, 3497),
|
||||
#' REF3 = c(1468, 1827, 1558, 2252, 3002, 3349, 2945, 3665),
|
||||
#' TEST1 = c(1405, 1523, 1502, 1474, 2383, 3221, 3589, 3445), TEST2 = c(1420, 1516, 1544, 1512, 2226, 3219, 3327, 3591),
|
||||
#' TEST3=c(1399, 1376, 1588, 1475, 2148, 3083, 2942, 3466), log_dose=c(5.01,3.401,2.708,2.015,1.32176,0.62861,-0.0645385,-1.6739764))
|
||||
#' TEST3 = c(1399, 1376, 1588, 1475, 2148, 3083, 2942, 3466), log_dose = c(5.01, 3.401, 2.708, 2.015, 1.32176, 0.62861, -0.0645385, -1.6739764)
|
||||
#' )
|
||||
#'
|
||||
#'
|
||||
#' ANOVA4plUnresfunc(ro_new)
|
||||
|
||||
|
||||
ANOVA4plUnresfunc <- function(ro_new) {
|
||||
all_l <- melt(data.frame(ro_new), id.vars = "log_dose", variable.name = "replname", value.name = "readout")
|
||||
all_len <- nrow(all_l)
|
||||
@@ -1216,17 +1397,26 @@ ANOVA4plUnresfunc <- function(ro_new) {
|
||||
p_SSnonp <- round(pf((SSnonparallel / AnovaDFs[4]) / MSE, AnovaDFs[3], RSS_df, lower.tail = F), 3)
|
||||
p_SSLoF <- round(pf((SSnonlin / LoF_df) / (SSE / SSE_df), LoF_df, SSE_df, lower.tail = F), 5)
|
||||
|
||||
ANOVAtab <- data.frame(Source = c("Treatment","Preparation","Regression",
|
||||
ANOVAtab <- data.frame(
|
||||
Source = c(
|
||||
"Treatment", "Preparation", "Regression",
|
||||
"Non-Parallelism", "Residual Error", "Non-linearity",
|
||||
"Pure Error","Total"),
|
||||
"Pure Error", "Total"
|
||||
),
|
||||
DF = AnovaDFs,
|
||||
SumSquares = c(SStreat, SSprep,SSregr, SSnonparallel,
|
||||
RSS, SSnonlin,SSE, SStot),
|
||||
MeanSquares = c(round(SStreat/AnovaDFs[1],3), SSprep, round(SStreat/AnovaDFs[3],3),round(SSnonparallel/AnovaDFs[4],3),
|
||||
round(MSE,5), round(SSnonlin/LoF_df,5), round(SSE/SSE_df,5),""),
|
||||
"F-value" = c(round((SStreat/AnovaDFs[1])/MSE,5), round((SSprep/AnovaDFs[2])/MSE,5),
|
||||
SumSquares = c(
|
||||
SStreat, SSprep, SSregr, SSnonparallel,
|
||||
RSS, SSnonlin, SSE, SStot
|
||||
),
|
||||
MeanSquares = c(
|
||||
round(SStreat / AnovaDFs[1], 3), SSprep, round(SStreat / AnovaDFs[3], 3), round(SSnonparallel / AnovaDFs[4], 3),
|
||||
round(MSE, 5), round(SSnonlin / LoF_df, 5), round(SSE / SSE_df, 5), ""
|
||||
),
|
||||
"F-value" = c(
|
||||
round((SStreat / AnovaDFs[1]) / MSE, 5), round((SSprep / AnovaDFs[2]) / MSE, 5),
|
||||
round((SSregr / AnovaDFs[3]) / MSE, 5), round((SSnonparallel / AnovaDFs[4]) / MSE, 5),
|
||||
"",round((SSnonlin/LoF_df)/(SSE/SSE_df),5),"",""),
|
||||
"", round((SSnonlin / LoF_df) / (SSE / SSE_df), 5), "", ""
|
||||
),
|
||||
"p_value" = c(round(p_SStreat, 3), p_SSprep, round(p_SSregr, 3), p_SSnonp, "", p_SSLoF, "", "")
|
||||
)
|
||||
|
||||
@@ -1243,16 +1433,15 @@ ANOVA4plUnresfunc <- function(ro_new) {
|
||||
#' @export
|
||||
#' @examples
|
||||
#'
|
||||
#' ro_new <- data.frame(REF1=c(1547, 1620, 1644, 2504, 3426, 3512, 3401, 3787), REF2=c(1492, 1536, 1384, 2286, 3046, 3479, 3516, 3497),
|
||||
#' ro_new <- data.frame(
|
||||
#' REF1 = c(1547, 1620, 1644, 2504, 3426, 3512, 3401, 3787), REF2 = c(1492, 1536, 1384, 2286, 3046, 3479, 3516, 3497),
|
||||
#' REF3 = c(1468, 1827, 1558, 2252, 3002, 3349, 2945, 3665),
|
||||
#' TEST1 = c(1405, 1523, 1502, 1474, 2383, 3221, 3589, 3445), TEST2 = c(1420, 1516, 1544, 1512, 2226, 3219, 3327, 3591),
|
||||
#' TEST3=c(1399, 1376, 1588, 1475, 2148, 3083, 2942, 3466), log_dose=c(5.01,3.401,2.708,2.015,1.32176,0.62861,-0.0645385,-1.6739764))
|
||||
#' TEST3 = c(1399, 1376, 1588, 1475, 2148, 3083, 2942, 3466), log_dose = c(5.01, 3.401, 2.708, 2.015, 1.32176, 0.62861, -0.0645385, -1.6739764)
|
||||
#' )
|
||||
#'
|
||||
#'
|
||||
#' perConcTab(ro_new, noDilSeries = 3)
|
||||
|
||||
|
||||
|
||||
perConcTab <- function(ro_new, noDilSeries) {
|
||||
Reftab <- ro_new[, c(1:noDilSeries)]
|
||||
Testtab <- ro_new[, c((noDilSeries + 1):(2 * noDilSeries))]
|
||||
@@ -1273,7 +1462,6 @@ perConcTab <- function(ro_new, noDilSeries) {
|
||||
tTesttab2 <- rbind(tTesttab, avs_test, sds_test, cv_test)
|
||||
concTab <- rbind(tReftab2, tTesttab2)
|
||||
return(concTab)
|
||||
|
||||
}
|
||||
|
||||
#' Calculates dilution series.
|
||||
@@ -1289,17 +1477,19 @@ perConcTab <- function(ro_new, noDilSeries) {
|
||||
#' @export
|
||||
#' @examples
|
||||
#'
|
||||
#' x <- 1; Div <- 3;N <- 0; res <- c(); noDil <- 7
|
||||
#' x <- 1
|
||||
#' Div <- 3
|
||||
#' N <- 0
|
||||
#' res <- c()
|
||||
#' noDil <- 7
|
||||
#'
|
||||
#' divFUN(x, Div, N, res, noDil)
|
||||
|
||||
|
||||
|
||||
divFUN <- function(x, Div, N, res, noDil) {
|
||||
N <- N + 1
|
||||
y <- x / Div
|
||||
res <- c(res, y)
|
||||
if (N==noDil) { return(res) }
|
||||
if (N == noDil) {
|
||||
return(res)
|
||||
}
|
||||
divFUN(y, Div, N, res, noDil)
|
||||
}
|
||||
|
||||
|
||||
Reference in New Issue
Block a user