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Using False Discovery Rates to Benchmark SNP-callers in next-generation sequencing projects

机译:使用错误发现率在下一代测序项目中对SNP调用者进行基准测试

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摘要

Sequence alignments form the basis for many comparative and population genomic studies. Alignment tools provide a range of accuracies dependent on the divergence between the sequences and the alignment methods. Despite widespread use, there is no standard method for assessing the accuracy of a dataset and alignment strategy after resequencing. We present a framework and tool for determining the overall accuracies of an input read dataset, alignment and SNP-calling method providing an isolate in that dataset has a corresponding, or closely related reference sequence available. In addition to this tool for comparing False Discovery Rates (FDR), we include a method for determining homozygous and heterozygous positions from an alignment using binomial probabilities for an expected error rate. We benchmark this method against other SNP callers using our FDR method with three fungal genomes, finding that it was able achieve a high level of accuracy. These tools are available at .
机译:序列比对形成许多比较和群体基因组研究的基础。比对工具根据序列和比对方法之间的差异提供一定范围的精确度。尽管已广泛使用,但尚无用于重新排序后评估数据集和对齐策略准确性的标准方法。我们提供了一种框架和工具,用于确定输入读取数据集的总体准确性,比对和SNP调用方法,以提供该数据集中的隔离株具有相应的或紧密相关的参考序列。除了此用于比较错误发现率(FDR)的工具之外,我们还提供了一种方法,该方法使用预期错误率的二项式概率根据比对确定纯合和杂合位置。我们使用具有三个真菌基因组的FDR方法,将该方法与其他SNP调用者进行了基准比较,发现它能够达到很高的准确性。这些工具可在上找到。

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