Table 2.

Multiple Linear Regression of Transformed Divergence Values on Three Aspects of Sequence Content and Recombination Rates

Dependent Variable	Independent Variablesa	Adjusted R2 b	Test Statistic(F)c	df	P
Shotgun human-chimp divergence values
	3 Mb	.083	8.07	1, 475	.005
	100 kb	.072	24.71	1, 475	9×10-7
	Local	.060	26.76	1, 475	3×10-7
BAC human-chimp divergence values
	3 Mb	.159	4.59	1, 98	.035
	100 kb	.181	8.57	1, 98	.004
	Local	.130	7.58	1, 98	.007
SeattleSNP human-chimp divergence values
	3 Mb	.071	1.63	1, 71	.205
	100 kb	.072	4.86	1, 71	.031
	Local	.078	6.37	1, 71	.014
Human-baboon divergence values
	3 Mb	.203	3.38	1, 110	.069
	100 kb	.136	7.72	1, 110	.006
	Local	.395	18.35	1, 110	4×10-5

^a“3 Mb,” “100 kb,” and “local” refer to the CpG, GC, and polyAT content at each scale (see “Materials and Methods” section).

^bThe adjusted R² is the proportionate reduction of the variance in transformed divergence values achieved by the introduction of recombination rates and sequence motifs in a given regression model. Note that R² values are not comparable across data sets. In particular, they depend on the variance of the error terms, which will differ across data sets, because of varying precision of divergence estimates (see “Materials and Methods” section). They also depend on the range of the independent variables.

^cBy use of a partial F test, we examine whether adding the recombination rate to the regression model explains a larger proportion of the variance in divergence values than do the three aspects of sequence content alone.