In this paper, we present an algorithm to lay out a particular class of graphs coming from real case studies: the quasi-tree graph class. Protein and internet mappings projects have shown the interest of devicing dedicated tools for visualizing such graphs. Our method addresses a challenging problem which consists in computing a layout of large graphs (up to hundred of thousands of nodes) that emphasizes their tree-like property in an efficient time. In order to validate our approach, we compare our results on real data to those obtained by well known algorithms. Keywords— Graph visualization, graph drawing, graph clustering, quasi-tree graph.