Mike Love et al's DESeq2 paper from the same year is also a great article for those being introduced to RNA-seq data https://t.co/ByvdkobF9i
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@vitaliikl @mikelove What do you mean by 'normalise'? In DESeq2, we do not 'normalise' counts, but model size factors explicitly (Eqn.(1) in https://t.co/TQfmzRhZ3m ). Having alpha_i be independent of j (and s_ij) is a model assumption. One may argue with
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"Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2 | Genome Biology | Full Text" https://t.co/Z5Or7rWFUt
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@mikelove @s_anders_m @wolfgangkhuber That's why the 2014 DESeq2 paper is such a classic, easily understood by non-statisticians like me. https://t.co/pQzs7lW7ei