This work addresses the problem of grouping by genes long reads expressed in a wholetranscriptome sequencing data set. Long read sequencing produces several thousands base-pair long sequences, although showing high error rate in comparison to short reads. Longreads can cover full-length RNA transcripts and thus are of high interest to complete refer-ences. However, the literature is lacking tools to cluster such data de novo, in particular forOxford Nanopore Technologies reads. As a consequence, we propose a novel algorithm basedon community detection and its implementation. Since solution is meant to be reference-free(de novo), it is especially well-tailored for non model species. We demonstrate it performswell on a real mouse data set. When a reference is available, we show that it stands as analternative to mapping. In addition, we show that quick assessment of gene's expression isa straightforward use case of our solution.