With the increasing availability of genetic data, several SNPs in a candidate gene can be combined into haplotypes to test for association with a quantitative trait. When the number of SNPs increases, the number of haplotypes can become very large and there is a need to group them together. The use of the phylogenetic relationships between haplotypes provides a natural and efficient way of grouping. Moreover, it allows us to identify disease or quantitative trait-related loci. In this article, we describe ALTree-q, a phylogeny-based approach to test for association between quantitative traits and haplotypes and to identify putative quantitative trait nucleotides (QTN). This study focuses on ALTree-q association test which is based on one-way analyses of variance (ANOVA) performed at the different levels of the tree. The statistical properties (type-one error and power rates) were estimated through simulations under different genetic models and were compared to another phylogeny-based test, TreeScan, (Templeton, 2005) and to a haplotypic omnibus test consisting in a one-way ANOVA between all haplotypes. For dominant and additive models ALTree-q is usually the most powerful test whereas TreeScan performs better under a recessive model. However, power depends strongly on the recurrence rate of the QTN, on the QTN allele frequency, and on the linkage disequilibrium between the QTN and other markers. An application of the method on Thrombin Activatable Fibronolysis Inhibitor Antigen levels in European and African samples confirms a possible association with polymorphisms of the CPB2 gene and identifies several QTNs