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fn_name #59

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Oct 10, 2024
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fn_name #59

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6 changes: 3 additions & 3 deletions episodes/eda_qc.Rmd
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Expand Up @@ -620,12 +620,12 @@ In this case, we only have a few doublets at the periphery of some clusters. It

#### Exercise 1: Normalization

Here we used the deconvolution method implemented in `scran` based on a previous clustering step. Use the `calculateSumFactors` to compute the size factors without considering a preliminary clustering. Compare the resulting size factors via a scatter plot. How do the results change? What are the risks of not including clustering information?
Here we used the deconvolution method implemented in `scran` based on a previous clustering step. Use the `pooledSizeFactors` to compute the size factors without considering a preliminary clustering. Compare the resulting size factors via a scatter plot. How do the results change? What are the risks of not including clustering information?

::: solution

```{r}
deconv.sf2 <- calculateSumFactors(sce) # dropped `cluster = clust` here
deconv.sf2 <- pooledSizeFactors(sce) # dropped `cluster = clust` here

summary(deconv.sf2)

Expand Down Expand Up @@ -703,7 +703,7 @@ clust <- quickCluster(sce)

table(clust)

deconv.sf <- calculateSumFactors(sce, cluster = clust)
deconv.sf <- pooledSizeFactors(sce, cluster = clust)

sizeFactors(sce) <- deconv.sf

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