RT Journal Article SR Electronic T1 Significantly distinct branches of hierarchical trees: A framework for statistical analysis and applications to biological data JF bioRxiv FD Cold Spring Harbor Laboratory SP 002188 DO 10.1101/002188 A1 Guoli Sun A1 Alexander Krasnitz YR 2014 UL http://biorxiv.org/content/early/2014/01/29/002188.abstract AB We formulate a method termed Tree Branches Evaluated Statistically for Tightness (TBEST) for identifying significantly distinct tree branches in hierarchical clusters. For each branch of the tree a measure of tightness is defined as a rational function of heights, both of the branch and of its parent. A statistical procedure is then developed to determine the significance of the observed values of tightness. We test TBEST as a tool for tree-based data partitioning by applying it to four benchmark datasets, each from a different area of biology and each with a well-defined partition of the data into classes. In all cases TBEST performs on par with or better than the existing techniques.