Assessment of the predictive accuracy of five in silico prediction tools, alone or in combination, and two metaservers to classify long QT syndrome gene mutations

Table 2 Conditions for SNV data output from two, three, four and all in silico missense prediction tools in order to be considered tolerated and damaging

Number of in silico prediction tools	SNV considered as Tolerated	SNV considered as Damaging
Two tools	Unanimous neutral/tolerated/benign	Unanimous damaging/disease/deleterious/non-neutral
Two tools		One output is damaging/disease/deleterious/non-neutral
Three tools	Unanimous neutral/tolerated/benign	Unanimous damaging/disease/deleterious/non-neutral
Three tools	Two outputs are neutral/tolerated/benign	Two outputs are damaging/disease/deleterious/non-neutral
Four tools	Unanimous neutral/tolerated/benign	Unanimous damaging/disease/deleterious/non-neutral
Four tools	Three outputs are neutral/tolerate/benign	Two or more outputs are damaging/disease/deleterious/non-neutral
All tools	Unanimous neutral/tolerated/benign	Unanimous damaging/disease/deleterious/non-neutral
All tools	Three outputs are neutral/tolerated/benign	Three or more outputs are damaging/disease/deleterious/non-neutral

ISSN: 1471-2350