merge

fgcz · Oct 26, 2020 · cab177e · cab177e
2 parents df39e11 + 3a3e49c
commit cab177e
Showing 1 changed file with 10 additions and 6 deletions.
diff --git a/vignettes/JPR_TechnicalNote.Rmd b/vignettes/JPR_TechnicalNote.Rmd
@@ -3,13 +3,14 @@ title: rawR - Technical Note, Journal of Proteome Research, Second Biennial Spec
   Issue on Software Tools and Resources in February 2021
 author: "Tobias Kockmann^1‡^ & Christian Panse^1,2‡^"
 date: "`r Sys.Date()`"
-bibliography: rawR.bib
 output:
   pdf_document:
-    keep_tex:  true
+    keep_tex: true
   html_document:
     df_print: paged
     citation_package: natbib
+  word_document: default
+bibliography: rawR.bib
 vignette: |
   %\usepackage[utf8]{inputenc}
   %\VignetteEncoding{UTF-8}
@@ -131,13 +132,12 @@ C <- readChromatogram(rawfile, mass = iRT, tol = 10, type = "xic", filter = "ms"
 plot(C)
 ```
 
-For regression, we now extract the RTs at the maximum of intensity traces stored in the chromatogram object and fit a linear model of the form $$rt = a \cdot score+b$$.
+For regression, we now extract the RTs at the maximum of the intensity traces stored in the chromatogram object and fit a linear model of the form $$rt = a + b\cdot score$$. The fitted model can than be inspected using the well known procedures. Code chunk `iRTscoreFitPlot` shows a visual inspection by scatter plotting observed RTs as a function of iRT score together with the regression line. The corresponding $$R^2$$ indicates that the RTs behave highly linear! This is expected since, the iRT peptides were separated on a 20 min linear gradient from 5% to 35% using C18 RP material. 
 
 ```{r iRTscoreFit, error=TRUE}
 score <- c(-24.92, 19.79, 70.52, 87.23, 0, 28.71, 12.39, 33.38, 42.26, 54.62, 100)
 rt <- sapply(C, function(x) x$times[which.max(x$intensities)[1]])
 fit <- lm(rt ~ score)
-summary(fit)
 ```
 
 
@@ -148,8 +148,12 @@ plot(rt ~ score,
      xlab = "iRT score",
      pch=16,frame.plot = FALSE)
 abline(fit, col = 'grey')
-legend("topleft", legend = "regression line", bty = "n", cex = 0.75)
-#text(score, rt,  substr(names(iRT),1,3),pos=3)
+abline(v = 0, col = "grey", lty = 2)
+legend("topleft", legend = paste("Regression line: ", "rt =",
+                                 format(coef(fit)[1], digits = 4), " + ",
+                                 format(coef(fit)[2], digits = 2), "score",
+                                 "\nR2: ", format(summary(fit)$r.squared, digits = 2)),
+       bty = "n", cex = 0.75)
 text(score, rt,  iRT,pos=1,cex=0.5)
 ```