<![CDATA[BOL: ALE: a Generic Assembly Likelihood Evaluation Framework for Assessing the Accuracy of Genome and Metagenome Assemblies]]> https://bioinformaticsonline.com/bookmarks/view/27076/ale-a-generic-assembly-likelihood-evaluation-framework-for-assessing-the-accuracy-of-genome-and-metagenome-assemblies? https://bioinformaticsonline.com/bookmarks/view/27076/ale-a-generic-assembly-likelihood-evaluation-framework-for-assessing-the-accuracy-of-genome-and-metagenome-assemblies Tue, 26 Apr 2016 03:38:43 -0500 https://bioinformaticsonline.com/bookmarks/view/27076/ale-a-generic-assembly-likelihood-evaluation-framework-for-assessing-the-accuracy-of-genome-and-metagenome-assemblies <![CDATA[ALE: a Generic Assembly Likelihood Evaluation Framework for Assessing the Accuracy of Genome and Metagenome Assemblies]]> Assembly Likelihood Evaluation (ALE) framework that overcomes these limitations, systematically evaluating the accuracy of an assembly in a reference-independent manner using rigorous statistical methods. This framework is comprehensive, and integrates read quality, mate pair orientation and insert length (for paired-end reads), sequencing coverage, read alignment and k-mer frequency. ALE pinpoints synthetic errors in both single and metagenomic assemblies, including single-base errors, insertions/deletions, genome rearrangements and chimeric assemblies presented in metagenomes. At the genome level with real-world data, ALE identifies three large misassemblies from the Spirochaeta smaragdinae finished genome, which were all independently validated by Pacific Biosciences sequencing. At the single-base level with Illumina data, ALE recovers 215 of 222 (97%) single nucleotide variants in a training set from a GC-rich Rhodobacter sphaeroides genome. Using real Pacific Biosciences data, ALE identifies 12 of 12 synthetic errors in a Lambda Phage genome, surpassing even Pacific Biosciences' own variant caller, EviCons. In summary, the ALE framework provides a comprehensive, reference-independent and statistically rigorous measure of single genome and metagenome assembly accuracy, which can be used to identify misassemblies or to optimize the assembly process.

More at http://www.ncbi.nlm.nih.gov/pubmed/23303509

Address of the bookmark: http://sc932.github.io/ALE/about.html

]]> Neel https://bioinformaticsonline.com/bookmarks/view/27076/ale-a-generic-assembly-likelihood-evaluation-framework-for-assessing-the-accuracy-of-genome-and-metagenome-assemblies#item-annotation-2387 Tue, 26 Apr 2016 03:57:05 -0500 https://bioinformaticsonline.com/bookmarks/view/27076/ale-a-generic-assembly-likelihood-evaluation-framework-for-assessing-the-accuracy-of-genome-and-metagenome-assemblies#item-annotation-2387 <![CDATA[Comment by Jit]]> Thanks for reporting the updated tool for assembly validation, you can also try following methods/pipelines

  • CEGMA (formally discontinued but still useful)
  • BUSCO (we have issues with fish, seems not to be tailored to that group of organisms, developers tell us they are fixing it)
  • linkage map? or other map (RAD-tag based). (software?)
  • BioNanoGenomics can be used for QC also
  • Use a genome browser to get a feeling for your results, e.g. IGV; add assembly, BAM files, annotation, transcripts mapped and browse
]]> Jit