allow calibration curves for single replicate experiments

Author: KarinSchork

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: CalibraCurve
 Title: Calibration curves for targeted proteomics, lipidomics and metabolomics data
-Version: 1.1.1
+Version: 1.1.2
 Authors@R: c(
     person("Karin", "Schork", , "karin.schork@rub.de", role = c("aut", "cre"),
            comment = c(ORCID = "0000-0003-3756-4347")),

NEWS.md

@@ -2,5 +2,14 @@
 
 
 # 0.99.0
-
 Initial submission to BioConductor.
+
+
+# 1.1.1
+Bugfixes
+
+# 1.1.2
+Allow calculation of calibration curves with only one replicate per concentration level. 
+
+
+

R/02_preliminary_linear_range.R

@@ -97,7 +97,11 @@ calculate_PLR <- function(dataCleaned, cvThres = 20,
 #' @importFrom stats sd
 #'
 .calcCV <- function(x) {
-    SD <- stats::sd(x$Measurement)
+    if (nrow(x) == 1) { #only one raplicate
+        SD <- 0
+    } else {
+        SD <- stats::sd(x$Measurement)
+    }
     Mean <- mean(x$Measurement)
     CV <- SD / Mean * 100
     names(CV) <- NULL

R/03_final_linear_range.R

@@ -155,6 +155,7 @@ calculate_FLR <- function(dataPrelim, weightingMethod = "1/x^2",
     calculatedConc <- (x - coeff[1]) / coeff[2]
     perBias <- 100 * abs(calculatedConc - expConc) / expConc
     names(perBias) <- NULL
+
     return(perBias)
 }
 
@@ -174,6 +175,7 @@ calculate_FLR <- function(dataPrelim, weightingMethod = "1/x^2",
     concentrations <- as.numeric(names(x))
     perBiasValues <- mapply(FUN = .calcPerBias, x = x, expConc = concentrations,
                             MoreArgs = list(LMfit = LMfit))
+    if(!is.matrix(perBiasValues)) perBiasValues <-  t(as.matrix(perBiasValues))
     return(perBiasValues)
 }
 
@@ -191,6 +193,7 @@ calculate_FLR <- function(dataPrelim, weightingMethod = "1/x^2",
 #' @importFrom stats sd median
 #'
 .calcPerBiasAvgSDCV <- function(x, method = "mean") {
+
     if (method == "mean") {
         avgPerBias <- colMeans(x)
     }