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Note that, the interclass 80% sequence identity cutoff implies that a positive sample and a negative sample are allowed to be homologous, and such a relaxed interclass identity cutoff is helpful for rigorous assessment and false-positive control.
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The company cites behind-the-scenes "back-end technology" as the reason for the cutoff, implying that the system will implode at the sight of a 5,001st friend.
Here the gathering score cutoff implied an Infernal E-value cutoff of ∼30.
However, the gathering score cutoff imply an Infernal E-value cutoff of ∼1000 for the 5S rRNA family.
For non-miRNA families we therefore impose an additional Infernal E-value cutoff of 1e-3 in the cases where the E-value cutoff implied by the gathering score cutoff is above 1e-3.
We therefore chose to apply 4 additional filters as explained below, 1. using only families for which we expect a hit (i.e. only families with seeds in vertebrates), 2. Infernal E-value filtering for families with very loose E-value cutoffs implied by the gathering score, 3. a BLAST filter, 4. special filtering for the miRNA families.
This is, perhaps, at the cost of missing out some important pocket pairs at a lower PMAX cutoff, which implies that there could be some false-negative findings that may be missed out.
In some cases we find the model gathering score cutoff to imply Infernal E-value cutoffs up to around 1e6 (the extreme case is S_pombe_snR97).
The cutoff changes implied 2 untested premises: that all SCCD requires treatment and that "early detection" justifies mislabeling many nondeficient persons.
As an example a distance cutoff of 0.05 implies that a sequence within an OTU is at the most 5% distant from every other sequence within the same OTU.
For example, in a dataset of 1000 SNPs, a cutoff of 95th percentile implies that the top ranked 50 SNPs (top 5%) are examined for the presence of the two epistatic SNPs.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com