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Next-generation sequencing (NGS) technologies have raised a challenging de novo genome assembly problem that is further amplified in recently emerged single-cell sequencing projects. While various NGS assemblers can use information from several libraries of read-pairs, most of them were originally developed for a single library and do not fully benefit from multiple libraries. Moreover, most assemblers assume uniform read coverage, condition that does not hold for single-cell projects where utilization of read-pairs is even more challenging. We have developed an exSPAnder algorithm that accurately resolves repeats in the case of both single and multiple libraries of read-pairs in both standard and single-cell assembly projects. Availability and implementation: http://bioinf.spbau.ru/en/spades Contact: ap@bioinf.spbau.ru

One of the key advances in genome assembly that has led to a significant improvement in contig lengths has been improved algorithms for utilization of paired reads (mate-pairs). While in most assemblers, mate-pair information is used in a post-processing step, the recently proposed Paired de Bruijn Graph (PDBG) approach incorporates the mate-pair information directly in the assembly graph structure. However, the PDBG approach faces difficulties when the variation in the insert sizes is high. To address this problem, we first transform mate-pairs into edge-pair histograms that allow one to better estimate the distance between edges in the assembly graph that represent regions linked by multiple mate-pairs. Further, we combine the ideas of mate-pair transformation and PDBGs to construct new data structures for genome assembly: pathsets and pathset graphs.

One of the key advances in genome assembly that has led to a significant improvement in contig lengths has been utilization of paired reads (mate-pairs). While in most assemblers, mate-pair information is used in a post-processing step, the recently proposed Paired de Bruijn Graph (PDBG) approach incorporates the mate-pair information directly in the assembly graph structure. However, the PDBG approach faces difficulties when the variation in the insert sizes is high. To address this problem, we first transform mate-pairs into edge-pair histograms that allow one to better estimate the distance between edges in the assembly graph that represent regions linked by multiple mate-pairs. Further, we combine the ideas of mate-pair transformation and PDBGs to construct new data structures for genome assembly: pathsets and pathset graphs.

International audience; Clustering hypertext document collection is an important task in Information Retrieval. Most clustering methods are based on document content and do not take into account the hyper-text links. Here we propose a novel PageRank based clustering (PRC) algorithm which uses the hypertext structure. The PRC algorithm produces graph partitioning with high modularity and coverage. The comparison of the PRC algorithm with two content based clustering algorithms shows that there is a good match between PRC clustering and content based clustering.