BACKGROUND Alignment of sequence reads generated by next-generation sequencing is an integral part of most pipelines analyzing next-generation sequencing data. A number of tools designed to quickly align a large volume of sequences are already available. However, most existing tools lack explicit guarantees about their output. They also do not support searching genome assemblies, such as the human genome assembly GRCh38, that include primary and alternate sequences and placement information for alternate sequences to primary sequences in the assembly. FINDINGS This paper describes SRPRISM (Single Read Paired Read Indel Substitution Minimizer), an alignment tool for aligning reads without splices. SRPRISM has features not available in most tools, such as (i) support for searching genome assemblies with alternate sequences, (ii) partial alignment of reads with a specified region of reads to be included in the alignment, (iii) choice of ranking schemes for alignments, and (iv) explicit criteria for search sensitivity. We compare the performance of SRPRISM to GEM, Kart, STAR, BWA-MEM, Bowtie2, Hobbes, and Yara using benchmark sets for paired and single reads of lengths 100 and 250 bp generated using DWGSIM. SRPRISM found the best results for most benchmark sets with error rate of up to ∼2.5% and GEM performed best for higher error rates. SRPRISM was also more sensitive than other tools even when sensitivity was reduced to improve run time performance. CONCLUSIONS We present SRPRISM as a flexible read mapping tool that provides explicit guarantees on results.

中文翻译：

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SRPRISM（Single Read Paired Read Indel Substitution Minimizer）：一种高效的对齐器，用于具有明确保证的组件。


背景技术由下一代测序生成的序列读数的比对是分析下一代测序数据的大多数流程的组成部分。许多旨在快速比对大量序列的工具已经可用。然而，大多数现有工具缺乏对其输出的明确保证。它们也不支持搜索基因组组件，例如人类基因组组件 GRCh38，其中包括主要序列和备用序列以及组件中备用序列与主要序列的放置信息。研究结果 本文描述了 SRPRISM（单读段配对读段插入缺失替换最小化器），这是一种用于比对无拼接读段的比对工具。 SRPRISM 具有大多数工具所不具备的功能，例如（i）支持使用备用序列搜索基因组组装体，（ii）将读数与要包含在比对中的指定读数区域进行部分比对，（iii）选择排序方案用于对齐，以及（iv）搜索敏感性的明确标准。我们使用使用 DWGSIM 生成的长度为 100 bp 和 250 bp 的配对和单个读取的基准集，将 SRPRISM 与 GEM、Kart、STAR、BWA-MEM、Bowtie2、Hobbes 和 Yara 的性能进行比较。 SRPRISM 发现大多数基准测试集的最佳结果，错误率高达 ∼2.5%，而 GEM 在错误率较高的情况下表现最好。即使降低灵敏度以提高运行时性能，SRPRISM 也比其他工具更灵敏。结论 我们将 SRPRISM 作为一种灵活的读映射工具，为结果提供明确的保证。