## Table 2 |
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Simulation Example 2 |
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False patterns |
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Methods |
X_{500} |
X_{5000} |
X_{1000}X_{3000} |
X_{7000}X_{7002} |
(Variables) |

pLPS | 50 (50) | 50 (50) | 48 (48,50) | 50 (50,50) | 278 |

RF | NA (50) | NA (50) | NA (28,37) | NA (50,50) | (335) |

SPLR | 50 (50) | 50 (50) | 50 (50,50) | 50 (50,50) | 800 |

*n *= 1000 and *p *= 8000, with correlations among neighboring variables. Tabulated numbers show the
number of tests (out of 50) in which the pattern was detected by each algorithm. The
number outside the parentheses is the number of times the given pattern was selected;
the numbers inside the parentheses shows how many times the variables in the pattern
are detected in the model, as a main effect or in some interaction. The final column
shows the total number of times (in 50 tests) that the algorithms selected patterns
(variables for RF) that are not in the true model.

Shi * et al.*

Shi * et al.* *BMC Bioinformatics* 2012 **13**:98 doi:10.1186/1471-2105-13-98