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1
Single-cell RNA counting at allele and isoform resolution using Smart-seq3.基于 Smart-seq3 技术进行等位基因和异构体分辨率的单细胞 RNA 计数
Nat Biotechnol. 2020 Jun;38(6):708-714. doi: 10.1038/s41587-020-0497-0. Epub 2020 May 4.
2
GFF Utilities: GffRead and GffCompare.
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3
RefShannon: A genome-guided transcriptome assembler using sparse flow decomposition.RefShannon:一种基于基因组指导的使用稀疏流分解的转录组组装方法。
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4
Opportunities and challenges in long-read sequencing data analysis.长读测序数据分析中的机遇与挑战。
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5
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Transcriptome assembly from long-read RNA-seq alignments with StringTie2.基于长读 RNA-seq 比对的转录组组装与 StringTie2。
Genome Biol. 2019 Dec 16;20(1):278. doi: 10.1186/s13059-019-1910-1.
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Accurate assembly of transcripts through phase-preserving graph decomposition.通过保留相位的图分解实现转录本的精确组装。
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使用Scallop2对多端RNA测序数据进行精确组装。

Accurate assembly of multi-end RNA-seq data with Scallop2.

作者信息

Zhang Qimin, Shi Qian, Shao Mingfu

机构信息

Department of Computer Science and Engineering, School of Electrical Engineering and Computer Science, The Pennsylvania State University.

Huck Institutes of the Life Sciences, The Pennsylvania State University.

出版信息

Nat Comput Sci. 2022 Mar;2(3):148-152. doi: 10.1038/s43588-022-00216-1. Epub 2022 Mar 28.

DOI:10.1038/s43588-022-00216-1
PMID:36713932
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9879047/
Abstract

Modern RNA-sequencing protocols can produce multi-end data, where multiple reads originating from the same transcript are attached to the same barcode. The long-range information in the multi-end reads is beneficial in phasing complicated spliced isoforms, but assembly algorithms that leverage such information are lacking. Here we introduce Scallop2, a reference-based assembler optimized for multi-end RNA-seq data. The algorithmic core of Scallop2 consists of three steps: (1) using an algorithm to "bridge" multi-end reads into single-end phasing paths in the context of a splice graph, (2) employing a method to refine erroneous splice graphs by utilizing multi-end reads that fail to bridge, and (3) piping the refined splice graph and the bridged phasing paths into an algorithm that integrates multiple phase-preserving decompositions. Tested on 561 cells in two Smart-seq3 datasets and on 10 Illumina paired-end RNA-seq samples, Scallop2 substantially improves the assembly accuracy compared to two popular assemblers StringTie2 and Scallop.

摘要

现代RNA测序方案可以产生多端数据,即源自同一转录本的多个读段被连接到同一个条形码上。多端读段中的长程信息有助于对复杂的剪接异构体进行定相,但缺乏利用此类信息的组装算法。在此,我们介绍了Scallop2,这是一种针对多端RNA-seq数据优化的基于参考的组装器。Scallop2的算法核心由三个步骤组成:(1)在剪接图的背景下,使用一种算法将多端读段“桥接”成单端定相路径;(2)采用一种方法,通过利用未能桥接的多端读段来细化错误的剪接图;(3)将细化后的剪接图和桥接后的定相路径输入到一个整合多个保相分解的算法中。在两个Smart-seq3数据集的561个细胞和10个Illumina双端RNA-seq样本上进行测试,与两种流行的组装器StringTie2和Scallop相比,Scallop2显著提高了组装准确性。