fix greenlead

bookdown/13_Deviations.Rmd

@@ -48,7 +48,7 @@ set.seed(1)
 
 # ChromVAR Deviatons Enrichment with ArchR
 
-As shown in previous chapters, TF motif enrichments can help us predict which regulatory factors are most active in our cell type of interest. These enrichments, however, are not calculated on a per-cell basis and they do not take into account the insertion sequence bias of the Tn5 transposase. [chromVAR](https://greenleaflab.github.io/chromVAR/index.html), an R packaged from the Greenlead Lab, was created to account for these issues. chromVAR is designed for predicting enrichment of TF activity on a per-cell basis from sparse chromatin accessibility data. The two primary outputs of chromVAR are:
+As shown in previous chapters, TF motif enrichments can help us predict which regulatory factors are most active in our cell type of interest. These enrichments, however, are not calculated on a per-cell basis and they do not take into account the insertion sequence bias of the Tn5 transposase. [chromVAR](https://greenleaflab.github.io/chromVAR/index.html), an R packaged from the Greenleaf Lab, was created to account for these issues. chromVAR is designed for predicting enrichment of TF activity on a per-cell basis from sparse chromatin accessibility data. The two primary outputs of chromVAR are:
 
 ```{r include=FALSE, eval=FALSE,echo=FALSE}
 # JJJ I would prefer to have more clear descriptions about deviations vs z scores for chromVAR. I've always found this very nuanced and it was never clear which metric should be used in which scenarios.