Alevin-fry-atac enables rapid and memory frugal mapping of single-cell ATAC-seq data using virtual colors for accurate genomic pseudoalignment.

Noor Pratap Singh, Jamshed Khan, Rob Patro
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Abstract

Ultrafast mapping of short reads via lightweight mapping techniques such as pseudoalignment has significantly accelerated transcriptomic and metagenomic analyses, often with minimal accuracy loss compared to alignment-based methods. However, applying pseudoalignment to large genomic references, like chromosomes, is challenging due to their size and repetitive sequences. We introduce a new and modified pseudoalignment scheme that partitions each reference into "virtual colors…. These are essentially overlapping bins of fixed maximal extent on the reference sequences that are treated as distinct "colors" from the perspective of the pseudoalignment algorithm. We apply this modified pseudoalignment procedure to process and map single-cell ATAC-seq data in our new tool alevin-fry-atac . We compare alevin-fry-atac to both Chromap and Cell Ranger ATAC . Alevin-fry-atac is highly scalable and, when using 32 threads, is approximately 2.8 times faster than Chromap (the second fastest approach) while using approximately one third of the memory and mapping slightly more reads. The resulting peaks and clusters generated from alevin-fry-atac show high concordance with those obtained from both Chromap and the Cell Ranger ATAC pipeline, demonstrating that virtual colorenhanced pseudoalignment directly to the genome provides a fast, memory-frugal, and accurate alternative to existing approaches for single-cell ATAC-seq processing. The development of alevin-fry-atac brings single-cell ATAC-seq processing into a unified ecosystem with single-cell RNA-seq processing (via alevin-fry ) to work toward providing a truly open alternative to many of the varied capabilities of CellRanger . Furthermore, our modified pseudoalignment approach should be easily applicable and extendable to other genome-centric mapping-based tasks and modalities such as standard DNA-seq, DNase-seq, Chip-seq and Hi-C.

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Alevin-fry-atac 利用虚拟颜色进行精确的基因组伪配对,实现了单细胞 ATAC-seq 数据的快速和内存节俭映射。
通过伪配对等轻量级映射技术将短读数超快地映射到转录组和元基因组参考序列,已成功地大大加快了几类分析的速度,而且与基于配对的方法相比,准确性不会有太大损失。然而,由于参考序列或 "目标"(即染色体)的大小很大,而且单个参考序列中存在重复序列,因此将伪配对应用于大型参考序列(如基因组)并非易事。这可能会导致单个参考文献中的 k- mer 有多个匹配位置,而当一个读数的 k- mer 匹配颜色汇总时,又会导致假阳性映射和错误的参考文献分配。即使读数被确定映射到了适当的参考文献,参考文献中 k- mer 多重匹配的增加也会妨碍确定读数的正确大致位置,而这在将短读数映射到基因组的应用中往往是至关重要的。我们提出了一种新的改进型伪配准方案,将每个参考文献划分为 "虚拟颜色"。这些虚拟颜色基本上是参考序列上固定最大范围的重叠区域,从伪配准算法的角度来看,它们被视为不同的 "颜色"。被映射的 k- mer 会被分配一个虚拟颜色 ID,它编码了 k- mer 所在的参考序列和参考序列内 bin 的组合。当对一个读数中的 k- mer 进行聚合时,会对虚拟颜色而不是原始颜色(参照)进行交集,以确定兼容的目标集(仓)。然后将虚拟颜色映射回原始参考序列,以提供最终映射。将原始参考序列投影到虚拟颜色空间,以及对伪对齐程序进行相应修改,都可以在调用程序时动态应用,而无需对底层索引本身进行任何修改。这使得设置和修改与实例相适应的参数变得高效而简单,并使该方法具有广泛的适用性。我们在新工具 alevin-fry-atac 中应用这种修改过的伪配准程序处理和映射单细胞 ATAC-seq 数据。我们将 alevin-fry-atac 与 Chromap 和 Cell Ranger ATAC 进行了比较。Alevin-fry-atac 具有很高的可扩展性,在使用 32 个线程时,比 Chromap(第二快的方法)快约 1.78 倍,同时内存使用量少约 3 倍,映射的读数略多。由 alevin-fry-atac 生成的峰和簇与 Chromap 和 Cell Ranger ATAC 管道生成的峰和簇显示出很高的一致性,这表明直接对基因组进行虚拟颜色增强的伪配准为单细胞 ATAC-seq 处理提供了一种快速、内存节省和精确的替代方法。levin-fry-atac的开发将单细胞ATAC-seq处理与单细胞RNA-seq处理(通过levin-fry)纳入了一个统一的生态系统,为CellRanger的多种功能提供了一个真正开放的替代方案。此外,我们修改过的伪配准方法应该很容易应用和扩展到其他以基因组为中心的基于图谱的任务和模式,如标准 DNA-seq、DNase-seq、Chip-seq 和 Hi-C。
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