Table 5.

Log(ods) and relative Pvalues associated to different single species (SSs) in logistic models

		Univariate			Bivariate			Multivariate
Predictor	Samples	Log(odds)	AUC	Pvalue	Log(odds)	AUC	Pvalue	Log(odds)	Pvalue
ggallus	17	–2.6	0.67	2.2e–217	–1.9	0.72	5.9e–106	–1.3	1.1e–51
ggorilla	12	–2.9	0.65	3.7e–162	–0.99	0.78	4e–19	–0.0092	0.95
hsapiens	59	–4.3	0.7	1.4e–300	–1.9	0.74	7.3e–54	–1.7	2.6e–31
mdomestica	20	–3.1	0.68	1.5e–225	–1.8	0.73	1.2e–77	–1	3.3e–23
mmulatta	14	–2.7	0.65	1e–175	–1.1	0.8	2.1e–25	0.38	0.002
mmusculus	49	–4	0.69	6.4e–275	–2.1	0.78	1.9e–74	–1.4	1.2e–24
oanatinus	19	–2.9	0.68	2.5e–229	–1.9	0.78	3.9e–92	–1.4	1.3e–46
pabelii	10	–2.8	0.64	3.7e–142	–1.2	0.81	1.7e–27	–0.53	2.2e–05
ptroglodytes	28	–3.1	0.67	1.5e–204	–1.2	0.77	1.6e–27	–0.36	0.01
xtropicalis	13	–2.7	0.65	5.5e–176	–1.8	0.78	4.4e–79	–1.5	5.3e–56

Bivariate models include two predictors: the indicated species plus AS. Note that AS and SSs derive from different expression datasets, GTEx and Necsulea respectively. The bivariate model that include hsapiens (from Necsulea) and AS shows that the contribute of hsapiens to the prediction is significant even if derive from the same specie of AS. The multivariate model consider all SSs but not AS, the AUC in this case is 0.77, the same AUC that we obtain with AS alone