LongGF: computational algorithm and software tool for fast and accurate detection of gene fusions by long-read transcriptome sequencing.
LongGF: computational algorithm and software tool for fast and accurate detection of gene fusions by long-read transcriptome sequencing.
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DOI：
10.1186/s12864-020-07207-4
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发表时间：
2020-12-29
期刊：
影响因子：
4.4
通讯作者：
Wang K
中科院分区：
文献类型：
--
作者：
Liu Q;Hu Y;Stucky A;Fang L;Zhong JF;Wang K
长读长 RNA-Seq 技术可以生成包含大部分或整个 mRNA/cDNA 分子的读长，因此它们有望解决短读长 RNA-Seq 技术（通常生成 <“150”bp 读长）的遗传局限性。然而，考虑到高碱基识别错误率和比对错误的存在，普遍缺乏从长读长RNA-seq数据中检测基因融合的软件工具。在本研究中，我们开发了一种快速计算工具 LongGF，可以从长读长的 RNA-seq 数据（包括 cDNA 测序数据和直接 mRNA 测序数据）中高效检测候选基因融合。我们在数十个模拟长读长RNA-seq数据集上评估了LongGF，并证明了其在基因融合检测方面的优越性能。我们还在 Nanopore 直接 mRNA 测序数据集和由 10 种癌细胞系混合生成的 PacBio 测序数据集上测试了 LongGF，发现与现有计算工具相比，LongGF 在检测已知基因融合方面取得了更好的性能。此外，我们在急性髓性白血病的 Nanopore cDNA 测序数据集上测试了 LongGF，并在碱基分辨率中精确定位了易位（之前在细胞遗传学分辨率中已知）的确切位置，并通过桑格测序进一步验证。总之，LongGF将极大地促进从长读RNA-Seq数据中发现候选基因融合事件，特别是在癌症样本中。 LongGF 用 C++ 实现，可从 https://github.com/WGLab/LongGF 获取。
Long-read RNA-Seq techniques can generate reads that encompass a large proportion or the entire mRNA/cDNA molecules, so they are expected to address inherited limitations of short-read RNA-Seq techniques that typically generate < 150 bp reads. However, there is a general lack of software tools for gene fusion detection from long-read RNA-seq data, which takes into account the high basecalling error rates and the presence of alignment errors. In this study, we developed a fast computational tool, LongGF, to efficiently detect candidate gene fusions from long-read RNA-seq data, including cDNA sequencing data and direct mRNA sequencing data. We evaluated LongGF on tens of simulated long-read RNA-seq datasets, and demonstrated its superior performance in gene fusion detection. We also tested LongGF on a Nanopore direct mRNA sequencing dataset and a PacBio sequencing dataset generated on a mixture of 10 cancer cell lines, and found that LongGF achieved better performance to detect known gene fusions over existing computational tools. Furthermore, we tested LongGF on a Nanopore cDNA sequencing dataset on acute myeloid leukemia, and pinpointed the exact location of a translocation (previously known in cytogenetic resolution) in base resolution, which was further validated by Sanger sequencing. In summary, LongGF will greatly facilitate the discovery of candidate gene fusion events from long-read RNA-Seq data, especially in cancer samples. LongGF is implemented in C++ and is available at https://github.com/WGLab/LongGF.
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影响因子：
4.6
作者：
Kumar S;Vo AD;Qin F;Li H
通讯作者：
Li H
影响因子：
14.9
作者：
Asmann YW;Hossain A;Necela BM;Middha S;Kalari KR;Sun Z;Chai HS;Williamson DW;Radisky D;Schroth GP;Kocher JP;Perez EA;Thompson EA
通讯作者：
Thompson EA
影响因子：
16.6
作者：
Byrne A;Beaudin AE;Olsen HE;Jain M;Cole C;Palmer T;DuBois RM;Forsberg EC;Akeson M;Vollmers C
通讯作者：
Vollmers C
DOI：
10.1093/bioinformatics/btv488
发表时间：
2015-12-15
期刊：
Bioinformatics (Oxford, England)
影响因子：
--
作者：
Hayer KE;Pizarro A;Lahens NF;Hogenesch JB;Grant GR
通讯作者：
Grant GR
影响因子：
5.8
作者：
Li, Heng
通讯作者：
Li, Heng