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fixed issues in the bs-seq for pdf compilation
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altuna akalin authored and altuna akalin committed Oct 9, 2020

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Showing 2 changed files with 3 additions and 2 deletions.
2 changes: 1 addition & 1 deletion 10-bs-seq-analysis.Rmd
Original file line number Diff line number Diff line change
@@ -339,7 +339,7 @@ res=methSeg(mbw,minSeg=10,G=1:4,
```

In this case, we know that BIC does not improve much after 4 segment classes. Now, we will not have a look at the characteristics of the segment classes. We are going to plot the mean methylation value and the length of the segment as a scatter plot; the result of this plot is shown in Figure \@ref(fig:segplot).
```{r segplot, fig.cap="Scatter plot of segment mean, methylation values versus segment length. Each dot is a segment identified by the _methSeg()_ function."}
```{r segplot, fig.cap="Scatter plot of segment mean, methylation values versus segment length. Each dot is a segment identified by the methSeg() function."}
# plot
plot(res$seg.mean,
log10(width(res)),pch=20,
3 changes: 2 additions & 1 deletion 11-multiomics-analysis.Rmd
Original file line number Diff line number Diff line change
@@ -775,4 +775,5 @@ ggplot2::ggplot(cov_factor, ggplot2::aes(x=cimp, y=factor2, group=cimp)) + ggplo
4. Microsatellite instability (MSI) is associated with hyper-mutated tumors. As seen in Figure \@ref(fig:momutationsHeatmap), one of the subtypes has tumors with significantly more mutations than the other. Which subtype is that? Which NMF factor is associated with that subtype? And which NMF factor is associated with MSI? [Difficulty: **Advanced**]


[^mfamca]: When dealing with categorical variables, MFA uses MCA (Multiple Correspondence Analysis). This is less relevant to biological data analysis and will not be discussed here.
[^mfamca]: When dealing with categorical variables, MFA uses MCA (Multiple Correspondence Analysis). This is less relevant to biological data analysis and will not be discussed here.

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