BibSonomy publications for /user/dzerbino/SoftwareMon Sep 17 20:19:41 CEST 2007BMC BioinformaticsFeb64Minimus: a fast, lightweight genome assembler82007Chromosome Software Alignment, Base Mapping, Algorithms, Data, User-Computer Analysis, Sequence, Sequence DNA, Design, Software, Interface Molecular BACKGROUND: Genome assemblers have grown very large and complex in response to the need for algorithms to handle the challenges of large whole-genome sequencing projects. Many of the most common uses of assemblers, however, are best served by a simpler type of assembler that requires fewer software components, uses less memory, and is far easier to install and run. RESULTS: We have developed the Minimus assembler to address these issues, and tested it on a range of assembly problems. We show that Minimus performs well on several small assembly tasks, including the assembly of viral genomes, individual genes, and BAC clones. In addition, we evaluate Minimus' performance in assembling bacterial genomes in order to assess its suitability as a component of a larger assembly pipeline. We show that, unlike other software currently used for these tasks, Minimus produces significantly fewer assembly errors, at the cost of generating a more fragmented assembly. CONCLUSION: We find that for small genomes and other small assembly tasks, Minimus is faster and far more flexible than existing tools. Due to its small size and modular design Minimus is perfectly suited to be a component of complex assembly pipelines. Minimus is released as an open-source software project and the code is available as part of the AMOS project at Sourceforge.Mon Sep 17 20:19:41 CEST 2007Genome ResFeb2330--40ProbCons: Probabilistic consistency-based multiple sequence alignment152005Sequence, Algorithms, Acid Computational (Genetics) Software, Validation, Software Alignment, Benchmarking, Variation Molecular Protein, Data, Sequence Amino Biology, Databases, To study gene evolution across a wide range of organisms, biologists need accurate tools for multiple sequence alignment of protein families. Obtaining accurate alignments, however, is a difficult computational problem because of not only the high computational cost but also the lack of proper objective functions for measuring alignment quality. In this paper, we introduce probabilistic consistency, a novel scoring function for multiple sequence comparisons. We present ProbCons, a practical tool for progressive protein multiple sequence alignment based on probabilistic consistency, and evaluate its performance on several standard alignment benchmark data sets. On the BAliBASE, SABmark, and PREFAB benchmark alignment databases, ProbCons achieves statistically significant improvement over other leading methods while maintaining practical speed. ProbCons is publicly available as a Web resource.Mon Sep 17 20:19:41 CEST 2007J Comput BiolMay4394--407Gene maps linearization using genomic rearrangement distances142007Algorithms, Computational Genome, Biology, Software Genomics, DNA, Analysis, Sequence A preliminary step to most comparative genomics studies is the annotation of chromosomes as ordered sequences of genes. Different genetic mapping techniques often give rise to different maps with unequal gene content and sets of unordered neighboring genes. Only partial orders can thus be obtained from combining such maps. However, once a total order O is known for a given genome, it can be used as a reference to order genes of a closely related species characterized by a partial order P. Our goal is to find a linearization of P that is as close as possible to O, in term of a given genomic distance. We first prove NP-completeness complexity results considering the breakpoint and the common interval distances. We then focus on the breakpoint distance and give a dynamic programming algorithm whose running time is exponential for general partial orders, but polynomial when the partial order is derived from a bounded number of genetic maps. A time-efficient greedy heuristic is then given for the general case and is empirically shown to produce solutions within 10% of the optimal solution, on simulated data. Applications to the analysis of grass genomes are presented.Mon Sep 17 20:19:41 CEST 2007Genome ResJan1149--59Hierarchical scaffolding with Bambus142004Benchmarking, anthracis Wolbachia, Haplotypes, Bacterial, Mapping, Brucella, Databases, Genetic, Dogs, Computational Software Algorithms, Biology, Genome, Validation, Shewanella, Animals, Contig Staphylococcus, Software, Bacillus Genomics, The output of a genome assembler generally comprises a collection of contiguous DNA sequences (contigs) whose relative placement along the genome is not defined. A procedure called scaffolding is commonly used to order and orient these contigs using paired read information. This ordering of contigs is an essential step when finishing and analyzing the data from a whole-genome shotgun project. Most recent assemblers include a scaffolding module; however, users have little control over the scaffolding algorithm or the information produced. We thus developed a general-purpose scaffolder, called Bambus, which affords users significant flexibility in controlling the scaffolding parameters. Bambus was used recently to scaffold the low-coverage draft dog genome data. Most significantly, Bambus enables the use of linking data other than that inferred from mate-pair information. For example, the sequence of a completed genome can be used to guide the scaffolding of a related organism. We present several applications of Bambus: support for finishing, comparative genomics, analysis of the haplotype structure of genomes, and scaffolding of a mammalian genome at low coverage. Bambus is available as an open-source package from our Web site.