School of Mathematics, Shandong University, Jinan, China.
Biomedical Pioneering Innovation Center, Beijing Advanced Innovation Center for Genomics, and School of Life Sciences, Peking University, Beijing, China.
Bioinformatics. 2019 Nov 1;35(21):4264-4271. doi: 10.1093/bioinformatics/btz240.
Full-length transcript reconstruction is essential for single-cell RNA-seq data analysis, but dropout events, which can cause transcripts discarded completely or broken into pieces, pose great challenges for transcript assembly. Currently available RNA-seq assemblers are generally designed for bulk RNA sequencing. To fill the gap, we introduce single-cell RNA-seq assembler, a method that applies explicit strategies to impute lost information caused by dropout events and a combing strategy to infer transcripts using scRNA-seq.
Extensive evaluations on both simulated and biological datasets demonstrated its superiority over the state-of-the-art RNA-seq assemblers including StringTie, Cufflinks and CLASS2. In particular, it showed a remarkable capability of recovering unknown 'novel' isoforms and highly computational efficiency compared to other tools.
scRNAss is free, open-source software available from https://sourceforge.net/projects/single-cell-rna-seq-assembly/files/.
Supplementary data are available at Bioinformatics online.
全长转录本重建对于单细胞 RNA-seq 数据分析至关重要，但由于转录本完全丢弃或碎片化的脱落事件，给转录本组装带来了巨大挑战。目前可用的 RNA-seq 组装器通常是为批量 RNA 测序设计的。为了填补这一空白，我们引入了单细胞 RNA-seq 组装器，该方法应用显式策略来推断由脱落事件引起的丢失信息，并应用梳理策略来推断使用 scRNA-seq 的转录本。
在模拟和生物数据集上的广泛评估表明，它优于包括 StringTie、Cufflinks 和 CLASS2 在内的最新 RNA-seq 组装器。特别是，与其他工具相比，它表现出了显著的恢复未知“新颖”异构体的能力和高效的计算能力。
scRNAss 是免费的、开源软件，可从 https://sourceforge.net/projects/single-cell-rna-seq-assembly/files/ 获得。
补充数据可在 Bioinformatics 在线获得。
