Supermatrix and supertree are two methods for constructing a phylogenetic tree 
by using multiple data sets. However, these methods are not a panacea, as 
conflicting signals between data sets can lead to misinterpret the evolutionary 
history of taxa. In particular, the supermatrix approach is expected to be 
misleading if the species-tree signal is not dominant after the combination of 
the data sets. Moreover, most current supertree methods suffer from two 
limitations: (i) they ignore or misinterpret secondary (non-dominant) 
phylogenetic signals of the different data sets; and (ii) the logical basis of 
node robustness measures is unclear. To overcome these limitations, we propose a 
new approach, called SuperTRI, which is based on the branch support analyses of 
the independent data sets, and where the reliability of the nodes is assessed 
using three measures: the supertree Bootstrap percentage and two other values 
calculated from the separate analyses: the mean branch support (mean Bootstrap 
percentage or mean posterior probability) and the reproducibility index. The 
SuperTRI approach is tested on a data matrix including seven genes for 82 taxa 
of the family Bovidae (Mammalia, Ruminantia), and the results are compared to 
those found with the supermatrix approach. The phylogenetic analyses of the 
supermatrix and independent data sets were done using four methods of tree 
reconstruction: Bayesian inference, maximum likelihood, and unweighted and 
weighted maximum parsimony. The results indicate, firstly, that the SuperTRI 
approach shows less sensitivity to the four phylogenetic methods, secondly, that 
it is more accurate to interpret the relationships among taxa, and thirdly, that 
interesting conclusions on introgression and radiation can be drawn from the 
comparisons between SuperTRI and supermatrix analyses.