add ref to pseudocounts (#574)

Signed-off-by: Daena Rys <[email protected]>

inst/assets/bibliography.bib

@@ -2210,4 +2210,15 @@ @Manual{microbiomap
     year = {2024},
     note = {R package version 0.99.13, commit bbb29aa746a3023ac331f62b8a47fbfc30441f8e},
     url = {https://github.com/seandavi/MicroBioMap},
-  }
+  }
+
+@article{Costea2014,
+  title = {A fair comparison},
+  journal = {Nature Methods},
+  volume = {11},
+  pages = {359},
+  year = {2014},
+  doi = {https://doi.org/10.1038/nmeth.2897},
+  url = {https://www.nature.com/articles/nmeth.2897},
+  author = {Costea, Paul I. and Zeller, Georg and Sunagawa, Shinichi and Bork, Peer}
+}

inst/pages/transformation.qmd

@@ -100,14 +100,19 @@ A complete list of available transformations and parameters, is
 available in the function
 [help](https://microbiome.github.io/mia/reference/transformAssay.html).
 
-## Pseudocount
+::: {.callout-important}
 
-::: {.callout-warning}
-## TODO
+Pseudocount is a small non-negative value added to the normalized data to avoid 
+taking the logarithm of zero. It's value can have a significant impact on the results when applying 
+a logarithm transformation to normalized data, as the logarithm transformation 
+is a nonlinear operation that can fundamentally change the data distribution [@Costea2014].
 
-Pseudocount can affect the results. Add here citation to the article. Also
-explain the idea of pseudocount. ancombc2 takes into account the affect by
-performing sensitivity test on multiple pseudocount values.
+
+Pseudocount should be chosen consistently across all normalization methods being 
+compared, for example, by setting it to a value smaller than the minimum abundance 
+value before transformation. Some tools, like ancombc2, take into account the effect 
+of the pseudocount by performing sensitivity tests using multiple pseudocount 
+values. See [@sec-differential-abundance].
 
 :::