Sometimes, a researcher is interested in finding genes that are not, or only very weakly, affected by the treatment or experimental condition. This amounts to a setting similar to the one just discussed, but the roles of the null and alternative hypotheses are swapped. We are here asking for evidence of the effect being weak, not for evidence of the effect being zero, because the latter question is rarely tractable. The meaning of weak needs to be quantified for the biological question at hand by choosing a suitable threshold θ for the LFC. For such analyses, DESeq2 offers a test of the composite null hypothesis |βir|≥θ, which will report genes as significant for which there is evidence that their LFC is weaker than θ. Figure 4B shows the outcome of such a test. For genes with very low read count, even an estimate of zero LFC is not significant, as the large uncertainty of the estimate does not allow us to exclude that the gene may in truth be more than weakly affected by the experimental condition. Note the lack
