diff --git a/inst/book/cell-annotation.Rmd b/inst/book/cell-annotation.Rmd
index 2ff1933..a9c9b5d 100644
--- a/inst/book/cell-annotation.Rmd
+++ b/inst/book/cell-annotation.Rmd
@@ -36,7 +36,7 @@ In this section, we will demonstrate the use of the `r Biocpkg("SingleR")` metho
 This method assigns labels to cells based on the reference samples with the highest Spearman rank correlations, using only the marker genes between pairs of labels to focus on the relevant differences between cell types.
 It also performs a fine-tuning step for each cell where the correlations are recomputed with just the marker genes for the top-scoring labels.
 This aims to resolve any ambiguity between those labels by removing noise from irrelevant markers for other labels.
-Further details can be found in the [_SingleR_ book](https://ltla.github.io/SingleRBook) from which most of the examples here are derived.
+Further details can be found in the [_SingleR_ book](https://bioconductor.org/books/release/SingleRBook/) from which most of the examples here are derived.
 
 ### Using existing references