tweaks to visualisation section

bartongroup · Sep 5, 2016 · ae89206 · ae89206
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diff --git a/inst/doc/tutorial.R b/inst/doc/tutorial.R
@@ -149,22 +149,22 @@ plot_gene(mydtu, "MIX6", vals="proportions")
 # The ERROR BARS represent 2 standard deviations from the mean count across replicates.
 plot_gene(mydtu, "MIX6", vals="counts")
 
-## ------------------------------------------------------------------------
-# Proportion change VS significance.
-plot_overview(mydtu, type="volcano")
+## ----eval=FALSE----------------------------------------------------------
+#  # Proportion change VS significance.
+#  plot_overview(mydtu, type="volcano")
 
-## ------------------------------------------------------------------------
-# Distribution of maximum proportion change.
-plot_overview(mydtu, type="maxdprop")
+## ----eval=FALSE----------------------------------------------------------
+#  # Distribution of maximum proportion change.
+#  plot_overview(mydtu, type="maxdprop")
 
 ## ------------------------------------------------------------------------
 library(ggplot2)
 
 myplot <- plot_overview(mydtu, "volcano")
 myplot  # display
 
-# Change scale of y axis to linear. 
-myplot2 <- myplot + scale_y_continuous(trans = "identity")
+# Change title. 
+myplot2 <- myplot + ggtitle("My epic title")
 myplot2
 
 ## ----eval=FALSE----------------------------------------------------------

diff --git a/inst/doc/tutorial.Rmd b/inst/doc/tutorial.Rmd
@@ -591,24 +591,24 @@ Possibly the most common plot in differential expression is the volcano plot, wh
 the statistical significance. As it is difficult to define a single p-value and a single effect size at the gene level,
 the volcano can only be plotted at the transcript level.
 
-```{r}
+```{r eval=FALSE}
 # Proportion change VS significance.
 plot_overview(mydtu, type="volcano")
 ```
 
-And this is what it looks like on a larger dataset:
+This is what it looks like on a larger dataset:
 ![Dprop VS sig](./fig/volcano.jpg)
 
 The next command plots the largest change in proportion seen within each gene, against the number of genes showing 
 such change. This is a way to inspect what effect sizes are present in the data. As an additional layer of information,
 they are colour-coded by their DTU call.
 
-```{r}
+```{r eval=FALSE}
 # Distribution of maximum proportion change.
 plot_overview(mydtu, type="maxdprop")
 ```
 
-And this is what it looks like on a larger dataset:
+This is what it looks like on a larger dataset:
 ![Max Dprop](./fig/maxdprop.jpg)
 
 
@@ -624,8 +624,8 @@ library(ggplot2)
 myplot <- plot_overview(mydtu, "volcano")
 myplot  # display
 
-# Change scale of y axis to linear. 
-myplot2 <- myplot + scale_y_continuous(trans = "identity")
+# Change title. 
+myplot2 <- myplot + ggtitle("My epic title")
 myplot2
 ```
 
@@ -714,8 +714,7 @@ mydtu <- call_DTU(annot = myannot, slo = myslo, name_A = "controls",
 As measure of confidence in the DTU calls, we take the fraction of iterations that returned a positive DTU call for
 the given gene/transcript. A positive call is considered confident if the fraction of positive calls exceeds the threshold (`>= conf_thresh`). 
 A negative call is considered confident if the fraction of positive calls is below the complement of the threshold (`<= 1 - conf_thresh`).
-
-The default confidence threshold is somewhat strict, but can be over-ridden.
+The default confidence threshold can be over-ridden.
 
 ```{r eval=FALSE}
 mydtu <- call_DTU(annot = myannot, slo = myslo, name_A = "controls", 

diff --git a/inst/doc/tutorial.html b/inst/doc/tutorial.html
diff --git a/vignettes/.build.timestamp b/vignettes/.build.timestamp
diff --git a/vignettes/fig/maxdprop.jpg b/vignettes/fig/maxdprop.jpg
diff --git a/vignettes/fig/maxdprop.png b/vignettes/fig/maxdprop.png
diff --git a/vignettes/fig/volcano.jpg b/vignettes/fig/volcano.jpg
diff --git a/vignettes/fig/volcano.png b/vignettes/fig/volcano.png
diff --git a/vignettes/tutorial.R b/vignettes/tutorial.R
diff --git a/vignettes/tutorial.Rmd b/vignettes/tutorial.Rmd
@@ -591,24 +591,24 @@ Possibly the most common plot in differential expression is the volcano plot, wh
 the statistical significance. As it is difficult to define a single p-value and a single effect size at the gene level,
 the volcano can only be plotted at the transcript level.
 
-```{r}
+```{r eval=FALSE}
 # Proportion change VS significance.
 plot_overview(mydtu, type="volcano")
 ```
 
-And this is what it looks like on a larger dataset:
+This is what it looks like on a larger dataset:
 ![Dprop VS sig](./fig/volcano.jpg)
 
 The next command plots the largest change in proportion seen within each gene, against the number of genes showing 
 such change. This is a way to inspect what effect sizes are present in the data. As an additional layer of information,
 they are colour-coded by their DTU call.
 
-```{r}
+```{r eval=FALSE}
 # Distribution of maximum proportion change.
 plot_overview(mydtu, type="maxdprop")
 ```
 
-And this is what it looks like on a larger dataset:
+This is what it looks like on a larger dataset:
 ![Max Dprop](./fig/maxdprop.jpg)
 
 
@@ -624,8 +624,8 @@ library(ggplot2)
 myplot <- plot_overview(mydtu, "volcano")
 myplot  # display
 
-# Change scale of y axis to linear. 
-myplot2 <- myplot + scale_y_continuous(trans = "identity")
+# Change title. 
+myplot2 <- myplot + ggtitle("My epic title")
 myplot2
 ```
 
@@ -714,8 +714,7 @@ mydtu <- call_DTU(annot = myannot, slo = myslo, name_A = "controls",
 As measure of confidence in the DTU calls, we take the fraction of iterations that returned a positive DTU call for
 the given gene/transcript. A positive call is considered confident if the fraction of positive calls exceeds the threshold (`>= conf_thresh`). 
 A negative call is considered confident if the fraction of positive calls is below the complement of the threshold (`<= 1 - conf_thresh`).
-
-The default confidence threshold is somewhat strict, but can be over-ridden.
+The default confidence threshold can be over-ridden.
 
 ```{r eval=FALSE}
 mydtu <- call_DTU(annot = myannot, slo = myslo, name_A = "controls", 

diff --git a/vignettes/tutorial_files/figure-html/unnamed-chunk-27-2.png b/vignettes/tutorial_files/figure-html/unnamed-chunk-27-2.png