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stuart-lab · Apr 4, 2024 · 8b98f63 · 8b98f63
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diff --git a/vignettes/integrate_atac.Rmd b/vignettes/integrate_atac.Rmd
@@ -32,6 +32,7 @@ wget https://cf.10xgenomics.com/samples/cell-arc/1.0.0/pbmc_granulocyte_sorted_1
 wget https://cf.10xgenomics.com/samples/cell-arc/1.0.0/pbmc_granulocyte_sorted_10k/pbmc_granulocyte_sorted_10k_atac_fragments.tsv.gz.tbi
 
 # scATAC
+# https://www.10xgenomics.com/datasets/10-k-peripheral-blood-mononuclear-cells-pbm-cs-from-a-healthy-donor-next-gem-v-1-1-1-1-standard-2-0-0
 wget https://cf.10xgenomics.com/samples/cell-atac/2.0.0/atac_pbmc_10k_nextgem/atac_pbmc_10k_nextgem_fragments.tsv.gz
 wget https://cf.10xgenomics.com/samples/cell-atac/2.0.0/atac_pbmc_10k_nextgem/atac_pbmc_10k_nextgem_fragments.tsv.gz.tbi
 ```

diff --git a/vignettes/motif_vignette.Rmd b/vignettes/motif_vignette.Rmd
@@ -158,7 +158,7 @@ knitr::kable(head(enriched.motifs))
 We can also plot the position weight matrices for the motifs, so we can
 visualize the different motif sequences.
 
-```{r}
+```{r warning=FALSE}
 MotifPlot(
   object = mouse_brain,
   motifs = head(rownames(enriched.motifs))