@@ -238,7 +238,7 @@ either to a `poplin` object or a `matrix`.

 The `poplin_naplot()` helps to visually inspect missingness of the data.

-```{r naplot, fig.width = 8, fig.height = 8}

+```{r naplot, fig.width = 7, fig.height = 7}

 poplin_naplot(x = faahko_poplin, xin = "raw")

 ```

@@ -247,7 +247,7 @@ poplin_naplot(x = faahko_poplin, xin = "raw")

 The `poplin_corplot()` visualizes correlations between samples (or features) to

 quickly check the grouping structure in the data.

-```{r corplot, fig.width = 8, fig.height = 8}

+```{r corplot, fig.width = 7, fig.height = 7}

 poplin_corplot(x = faahko_poplin, xin = "knn_cyclic")

 ```

@@ -273,7 +273,7 @@ poplin_boxplot(faahko_poplin, xin = "knn_cyclic", group = group)

 The `poplin_scoreplot()` function visualizes the data onto a lower-dimensional

 space using the `poplin_reduce()` output.

-```{r poplin_scoreplot}

+```{r poplin_scoreplot, fig.width = 7, fig.height = 5}

 group <- colData(faahko_poplin)$sample_group

 ## PCA output

@@ -286,6 +286,21 @@ poplin_scoreplot(faahko_poplin, xin = "plsda", ellipse = TRUE,

 ```

+## poplin_biplot

+

+The `poplin_biplot()` function Visualize an overlay of a score plot and a

+loading plot using the `poplin_reduce()` output.

+

+```{r poplin_biplot, fig.width = 7, fig.height = 5}

+group <- colData(faahko_poplin)$sample_group

+

+poplin_biplot(faahko_poplin, xin = "pca", group = group, 

+              ellipse = TRUE, arrow_col = "orange", 

+              arrow_label_subset = c("FT039", "FT042", "FT046", "FT098"),

+              arrow_label_col = "gray20")

+

+```

+

 # Session info {-}

 ```{r session info}