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10.1093/bioinformatics/btv226 http://scihub22266oqcxt.onion/10.1093/bioinformatics/btv226 C4765875!4765875!26072514     free     free     free       Bioinformatics 2015 ; 31 (12): i9-i16 Nephropedia Template TP {{tp|p=26072514|t=2015. De novo meta-assembly of ultra-deep sequencing data |pdf=|usr=}}{{26072514}} gab.com Text De novo meta-assembly of ultra-deep sequencing data JO: Bioinformatics http://www.kidney.de/pget.php?&tw=1&pmid=26072514 #FOAvip We introduce a new divide and conquer approach to deal with the problem of de novo genome assembly in the presence of ultra-deep sequencing data (i.e. coverage of 1000x or higher). Our proposed meta-assembler Slicembler partitions the input data into optimal-sized ?slices? and uses a standard assembly tool (e.g. Velvet, SPAdes, IDBA_UD and Ray) to assemble each slice individually. Slicembler uses majority voting among the individual assemblies to identify long contigs that can be merged to the consensus assembly. To improve its efficiency, Slicembler uses a generalized suffix tree to identify these frequent contigs (or fraction thereof). Extensive experimental results on real ultra-deep sequencing data (8000x coverage) and simulated data show that Slicembler significantly improves the quality of the assembly compared with the performance of the base assembler. In fact, most of the times, Slicembler generates error-free assemblies. We also show that Slicembler is much more resistant against high sequencing error rate than the base assembler.Availability and implementation: Slicembler can be accessed at http://slicembler.cs.ucr.edu/.Contact:hamid.mirebrahim@email.ucr.edu Twit Text FOAVip De novo meta-assembly of ultra-deep sequencing data ????Bioinformatics http://www.kidney.de/pget.php?&tw=1&pmid=26072514 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=26072514 #FOAvip English Wikipedia <ref>{{Cite pmid|26072514}}</ref> De novo meta-assembly of ultra-deep sequencing data #MMPMID26072514 Mirebrahim H; Close TJ; Lonardi S Bioinformatics 2015[Jun]; 31 (12): i9-i16 PMID26072514show ga We introduce a new divide and conquer approach to deal with the problem of de novo genome assembly in the presence of ultra-deep sequencing data (i.e. coverage of 1000x or higher). Our proposed meta-assembler Slicembler partitions the input data into optimal-sized ?slices? and uses a standard assembly tool (e.g. Velvet, SPAdes, IDBA_UD and Ray) to assemble each slice individually. Slicembler uses majority voting among the individual assemblies to identify long contigs that can be merged to the consensus assembly. To improve its efficiency, Slicembler uses a generalized suffix tree to identify these frequent contigs (or fraction thereof). Extensive experimental results on real ultra-deep sequencing data (8000x coverage) and simulated data show that Slicembler significantly improves the quality of the assembly compared with the performance of the base assembler. In fact, most of the times, Slicembler generates error-free assemblies. We also show that Slicembler is much more resistant against high sequencing error rate than the base assembler.Availability and implementation: Slicembler can be accessed at http://slicembler.cs.ucr.edu/.Contact:hamid.mirebrahim@email.ucr.edu äDe novo meta-assembly of ultra-deep sequencing data (epmc).pdf DeepDyve Pubget Overpricing