Illumina CRAM files for "Characterization of large-scale structural variants using Linked-Reads" (Part 2 of 2)

Here we propose novel algorithms to characterize large (&gt;40 Kbp) interspersed segmental duplications, (&gt; 80 Kbp) inversions, (&gt; 100 Kbp) deletions, and (&gt; 100 Kbp) translocations using Linked-Read sequencing data. Linked-Read sequencing provides long range information, where Illumina reads are tagged with barcodes that can be used to assign short reads to pools of larger (30-50 Kbp) molecules. <br> Our methods rely on split molecule sequence signature that we have previously described. Similar to the split read, split molecules refer to large segments of DNA that span an SV breakpoint. Therefore, when mapped to the reference genome, the mapping of these segments would be discontinuous. <br> We redesign our earlier algorithm, VALOR, to specifically leverage Linked-Read sequencing data to discover large <br> structural variation. We implement our new algorithms in a new software package, called VALOR2.本研究提出了全新的算法，可借助链接读长测序（Linked-Read sequencing）数据，对长度大于40千碱基对（Kbp）的散在节段重复、大于80千碱基对的倒位、大于100千碱基对的缺失以及大于100千碱基对的易位进行表征。 链接读长测序可提供长程基因组信息，其技术原理是为Illumina测序读段标记条形码，借此可将短读段分配至更大的（30~50千碱基对）分子池中。 本研究方法依托于我们此前已报道的裂分子序列特征。与裂读（split read）类似，裂分子指的是跨越结构变异（Structural Variation，SV）断点的大片段DNA。因此，当将这些片段比对至参考基因组时，其比对结果将呈现不连续性。 我们对早期开发的算法VALOR进行了重新设计，使其能够专门利用链接读长测序数据来鉴定大片段结构变异。我们将新算法集成至一款全新的软件包中，并将其命名为VALOR2。