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    Cancer. Potential of the synthetic lethality principle (2013)
    American Association for the Advancement of Science (AAAS)
    Details
    Publication Date: 2013-11-16
    Description: 〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Nijman, Sebastian M B -- Friend, Stephen H -- New York, N.Y. -- Science. 2013 Nov 15;342(6160):809-11. doi: 10.1126/science.1244669.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/24233712" target="_blank"〉PubMed〈/a〉
    Keywords: Animals ; Drosophila melanogaster/genetics ; Gene Targeting ; *Genes, Lethal ; *Genes, Modifier ; Genetic Therapy/*methods ; Humans ; Immunotherapy ; Molecular Targeted Therapy ; Mutation ; Neoplasms/*genetics/*therapy ; Saccharomyces cerevisiae/genetics ; Tumor Suppressor Proteins/genetics
    Print ISSN: 0036-8075
    Electronic ISSN: 1095-9203
    Topics: Biology , Chemistry and Pharmacology , Computer Science , Medicine , Natural Sciences in General , Physics
    Published by American Association for the Advancement of Science (AAAS)
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  • 2
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    A thesaurus of genetic variation for interrogation of repetitive genomic regions (2015)
    Oxford University Press
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    Publication Date: 2015-05-29
    Description: Detecting genetic variation is one of the main applications of high-throughput sequencing, but is still challenging wherever aligning short reads poses ambiguities. Current state-of-the-art variant calling approaches avoid such regions, arguing that it is necessary to sacrifice detection sensitivity to limit false discovery. We developed a method that links candidate variant positions within repetitive genomic regions into clusters. The technique relies on a resource, a thesaurus of genetic variation, that enumerates genomic regions with similar sequence. The resource is computationally intensive to generate, but once compiled can be applied efficiently to annotate and prioritize variants in repetitive regions. We show that thesaurus annotation can reduce the rate of false variant calls due to mappability by up to three orders of magnitude. We apply the technique to whole genome datasets and establish that called variants in low mappability regions annotated using the thesaurus can be experimentally validated. We then extend the analysis to a large panel of exomes to show that the annotation technique opens possibilities to study variation in hereto hidden and under-studied parts of the genome.
    Keywords: Computational Methods, Genomics
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
    Published by Oxford University Press
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  • 3
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    Comparison of genetic variants in matched samples using thesaurus annotation (2016)
    Oxford University Press
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    Publication Date: 2016-02-27
    Description: Motivation: Calling changes in DNA, e.g. as a result of somatic events in cancer, requires analysis of multiple matched sequenced samples. Events in low-mappability regions of the human genome are difficult to encode in variant call files and have been under-reported as a result. However, they can be described accurately through thesaurus annotation—a technique that links multiple genomic loci together to explicate a single variant. Results: We here describe software and benchmarks for using thesaurus annotation to detect point changes in DNA from matched samples. In benchmarks on matched normal/tumor samples we show that the technique can recover between five and ten percent more true events than conventional approaches, while strictly limiting false discovery and being fully consistent with popular variant analysis workflows. We also demonstrate the utility of the approach for analysis of de novo mutations in parents/child families. Availability and implementation: Software performing thesaurus annotation is implemented in java; available in source code on github at GeneticThesaurus ( https://github.com/tkonopka/GeneticThesaurus ) and as an executable on sourceforge at geneticthesaurus ( https://sourceforge.net/projects/geneticthesaurus ). Mutation calling is implemented in an R package available on github at RGeneticThesaurus ( https://github.com/tkonopka/RGeneticThesaurus ). Supplementary information: Supplementary data are available at Bioinformatics online. Contact: tomasz.konopka@ludwig.ox.ac.uk
    Print ISSN: 1367-4803
    Electronic ISSN: 1460-2059
    Topics: Biology , Computer Science , Medicine
    Published by Oxford University Press
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