Abstract : BACKGROUND: V(D)J recombinations in lymphocytes are essential for immunological diversity. They are also usefulmarkers of pathologies. In leukemia, they are used to quantify the minimal residual disease duringpatient follow-up. However, the full breadth of lymphocyte diversity is not fully understood. RESULTS: We propose new algorithms that process high-throughput sequencing (HTS) data to extract unnamedV(D)J junctions and gather them into clones for quantification. This analysis is based on a seedheuristic and is fast and scalable because in the first phase, no alignment is performed with germlinedatabase sequences. The algorithms were applied to TR HTS data from a patient with acutelymphoblastic leukemia, and also on data simulating hypermutations. Our methods identified themain clone, as well as additional clones that were not identified with standard protocols. CONCLUSIONS: The proposed algorithms provide new insight into the analysis of high-troughput sequencing data forleukemia, and also to the quantitative assessment of any immunological profile. The methodsdescribed here are implemented in a C++ open-source program called Vidjil.