压缩和索引对齐的读集
Compressing and Indexing Aligned Readsets
摘要：
在本文中，我们将展示如何使用一个或多个组装或部分组装的基因组作为其读集的压缩全文索引的基础。具体来说，我们通过将组装的基因组作为主干并在其比对的起始位置处将与其比对的读段嫁接到其上来构建标记树。接下来，我们计算得到的标签树的扩展Burrows-Wheeler变换（XBWT），并在其上构建压缩的全文索引。虽然这个索引偶尔会返回假阳性，但它通常比其他方法更紧凑。遵循对具有许多重复的数据集的既定实践，我们通过查看转换后的字符串中的运行次数来比较不同的全文索引。对于人类Chr 19读集，我们的初步实验表明，从EBWT中消除分隔符字符将运行次数减少了19%，从2.2亿减少到1.78亿，并且使用XBWT将其进一步减少了15%，减少到1.5亿。
英文摘要：
In this paper we show how to use one or more assembled or partially assembled genome as the basis for a compressed full-text index of its readset. Specifically, we build a labelled tree by taking the assembled genome as a trunk and grafting onto it the reads that align to it, at the starting positions of their alignments. Next, we compute the eXtended Burrows-Wheeler Transform (XBWT) of the resulting labelled tree and build a compressed full-text index on that. Although this index can occasionally return false positives, it is usually much more compact than the alternatives. Following the established practice for datasets with many repetitions, we compare different full-text indices by looking at the number of runs in the transformed strings. For a human Chr19 readset our preliminary experiments show that eliminating separators characters from the EBWT reduces the number of runs by 19\%, from 220 million to 178 million, and using the XBWT reduces it by a further 15\%, to 150 million.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
