Table 1

Wild-type motif classifier performance Download Figure 4-1, TIF file.

Comparison	Motifs (number)	Cv error (%)	Cv error Std	Mc error (%)	Mc EP	RM error (%)	RM error Std
`Wild type`
`Day/night`	`15`	`0.20`	`0.63`	`50.0`	`2.25`	`9.25`	`2.50`
`Day 5/day 6`	`93`	`20.2`	`9.60`	`50.0`	`3.18`	`45.8`	`4.09`
`Night 5/night 6`	`85`	`19.8`	`8.09`	`50.0`	`3.18`	`48.3`	`6.00`
`Day hours`
•`09-10`	`102`	`6.39`	`1.23`	`7.14`	`0.44`	`7.67`	`0.26`
•`10-11`	`1`	`7.37`	`0.31`	`7.14`	`0.44`	`7.18`	`0.10`
•`11-12`	`5`	`7.20`	`0.23`	`7.14`	`0.44`	`7.15`	`0.03`
•`12-13`	`9`	`7.06`	`0.34`	`7.14`	`0.44`	`7.19`	`0.08`
•`13-14`	`1`	`7.14`	`0.12`	`7.14`	`0.44`	`7.14`	`0`
•`14-15`	`1`	`7.14`	`0.12`	`7.14`	`0.44`	`7.14`	`0`
•`15-16`	`1`	`7.11`	`0.14`	`7.14`	`0.44`	`7.14`	`0`
•`16-17`	`1`	`7.09`	`0.15`	`7.14`	`0.44`	`7.14`	`0`
•`17-18`	`1`	`7.14`	`0.12`	`7.14`	`0.44`	`7.14`	`0`
•`18-19`	`1`	`7.14`	`0.12`	`7.14`	`0.44`	`7.14`	`0`
•`19-20`	`1`	`7.14`	`0.12`	`7.14`	`0.44`	`7.14`	`0`
•`20-21`	`3`	`7.11`	`0.27`	`7.14`	`0.44`	`7.15`	`0.01`
•`21-22`	`1`	`7.14`	`0.12`	`7.14`	`0.44`	`7.14`	`0`
•`22-23`	`1`	`7.14`	`0.12`	`7.14`	`0.44`	`7.15`	`0.03`
`Night hours`
•`23-24`	`23`	`0.69`	`0.47`	`10.0`	`0.60`	`6.57`	`1.23`
•`24–01`	`177`	`9.84`	`1.83`	`10.0`	`0.60`	`11.6`	`0.78`
•`01–02`	`5`	`9.92`	`0.51`	`10.0`	`0.60`	`10.0`	`0.05`
•`02-03`	`88`	`9.72`	`1.18`	`10.0`	`0.60`	`10.4`	`0.31`
•`03-04`	`1`	`10.0`	`0.17`	`10.0`	`0.60`	`10.0`	`0.04`
•`04-05`	`22`	`9.92`	`0.47`	`10.0`	`0.60`	`10.1`	`0.07`
•`05-06`	`1`	`10.0`	`0.17`	`10.0`	`0.60`	`10.0`	`0`
•`06-07`	`1`	`10.0`	`0.17`	`10.0`	`0.60`	`10.0`	`0.02`
•`07-08`	`3`	`9.84`	`0.34`	`10.0`	`0.60`	`10.0`	`0.01`
•`08-09`	`1`	`10.0`	`0.17`	`10.0`	`0.60`	`10.0`	`0.01`
`Morning/evening`	`229`	`33.2`	`2.32`	`50.0`	`0.85`	`44.7`	`0.96`
`Early/late night`	`26`	`36.4`	`2.18`	`50.0`	`1.00`	`43.4`	`1.55`

A table showing the performance of each wild-type motif classifier. Each classifier sought to separate the data shown in the comparison column, e.g., day/night. For the hourly comparisons, each hour was compared with data from all other hours grouped together. For each comparison, 250 motifs were chosen by mRMR, then a smaller number were retained (see motifs column) based on classification error curves (Extended Data Fig. 4-1A). Cv, 10-fold cross validated; Std, SD across the 10 folds; Mc, majority class classifier; EP, SE of proportion; RM, classifiers built from random motif subsets.