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inst/pages/exercises.qmd

@@ -1033,7 +1033,7 @@ that by default only the first two dimensions are shown.
 4. Check which information is stored in the ColData of the TreeSE. What would
 be worth visualizing in our coordination plot?
 5. Make the same plot again, but this time colour the observations by
-Enterotype. You can do that by setting `colour.by` to the appropriate colname
+Enterotype. You can do that by setting `colour_by` to the appropriate colname
 in the colData of the TreeSE.
 6. **Extra**: Plot all three dimensions of PCA with `scater::plotReducedDim`
 and the optional argument `ncomponents`. Colour observations by Enterotype.
@@ -1054,7 +1054,7 @@ assay in terms of Bray-Curtis dissimilarity. You can use `scater::runMDS`
 with the compulsory argument `FUN = vegan::vegdist`.
 4. Plot the first two dimensions of PCA with `plotReducedDim`, to which you
 should give the appropriate reducedDim name as the second argument. Colour
-the observations by Enterotype with `colour.by`.
+the observations by Enterotype with `colour_by`.
 5. **Extra**: Perform MDS again with `scater::runMDS`, but this time use Jaccard
 dissimilarity. The distance metric to use can be defined with the optional
 argument `method`, choosing from the methods in `?vegan::vegdist`. If you