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vignettes/integrate_atac.Rmd

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@@ -32,6 +32,7 @@ wget https://cf.10xgenomics.com/samples/cell-arc/1.0.0/pbmc_granulocyte_sorted_1
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wget https://cf.10xgenomics.com/samples/cell-arc/1.0.0/pbmc_granulocyte_sorted_10k/pbmc_granulocyte_sorted_10k_atac_fragments.tsv.gz.tbi
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# scATAC
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# 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
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wget https://cf.10xgenomics.com/samples/cell-atac/2.0.0/atac_pbmc_10k_nextgem/atac_pbmc_10k_nextgem_fragments.tsv.gz
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wget https://cf.10xgenomics.com/samples/cell-atac/2.0.0/atac_pbmc_10k_nextgem/atac_pbmc_10k_nextgem_fragments.tsv.gz.tbi
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```

vignettes/motif_vignette.Rmd

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

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