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@@ -1080,12 +1080,16 @@ literal "false"
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\end_inset
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.
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- While methylation array data are not derived from counts and the mean-variance
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- trend in M-values has a different shape than that of RNA-seq count data,
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- the voom method is sufficiently general to model any smooth mean-variance
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- trend, so is applicable to M-values from methylation array data.
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- However, some implementation details of the method must be adapted to allow
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- voom to accept M-values rather than read counts as input.
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+ While methylation array data are not derived from counts and have a very
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+ different mean-variance relationship from that of typical RNA-seq data,
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+ the voom method makes no specific assumptions on the shape of the mean-variance
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+ relationship - it only assumes that the relationship is smooth enough to
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+ model using a lowess curve.
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+ Hence, the method is sufficiently general to model the mean-variance relationsh
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+ip in methylation array data.
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+ However, the standard implementation of voom assumes that the input is
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+ given in raw read counts, and minor adjustments are required to run it
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+ on methylation M-values.
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\end_layout
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\begin_layout Standard
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