Current implementations of the log-rank test (R survdiff, SAS LIFETEST, etc.) are based on an asymptotic approximation for the distribution of the log-rank statistic that is not appropriate when the two populations to be compared are unbalanced, as it is the case when testing the association of a mutation with survival in genomic studies. This asymptotic approximation results in p-values that can be very different from the exact p-values, up to 7 orders of magnitude, and a large number of false discoveries are reported because of this difference.
ExaLT (Exact Log-rank Test) is a method to compute a conservative approximation of the exact p-value. In particular, the method computes the p-value for the exact permutational p-value, that is more appropriate for testing the association of mutations with survival.
- C++ Compiler / R package
:: MORE INFORMATION
Accurate computation of survival statistics in genome-wide studies.
Vandin F, Papoutsaki A, Raphael BJ, Upfal E.
PLoS Comput Biol. 2015 May 7;11(5):e1004071. doi: 10.1371/journal.pcbi.1004071.
F. Vandin, A. Papoutsaki, B.J. Raphael, E.Upfal (2013)
Genome-Wide Survival Analysis of Somatic Mutations in Cancer.
17th Annual International Conference on Research in Computational Molecular Biology (RECOMB 2013).