SCSit: A high-efficiency preprocessing tool for single-cell sequencing data from SPLiT-seq.
SCSit: A high-efficiency preprocessing tool for single-cell sequencing data from SPLiT-seq.
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SCSit：一种用于 SPLiT-seq 的单细胞测序数据的高效预处理工具。
DOI：
10.1016/j.csbj.2021.08.021
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发表时间：
2021
影响因子：
6
通讯作者：
Xie SQ
中科院分区：
文献类型：
--
作者：
Luan MW;Lin JL;Wang YF;Liu YX;Xiao CL;Wu R;Xie SQ
Split-Seq通过四轮组合条形码标记RNA的细胞来源，提供了一个低成本的平台来生成单细胞数据。然而，目前缺乏一种自动、快速地对来自Split-Seq的单细胞测序(SCS)数据进行预处理和分类的方法，该方法直接识别和标记组合条形码读数和区分的特殊细胞测序数据。在这里，我们开发了一个高效的拆分序列单细胞测序数据预处理工具(SCSit)，该工具可以直接识别细胞类型的组合条形码和UMI，获得更多的标记读数，并由于插入和缺失的准确比对，显著提高了SCS的保留数据。与Split-Seq中使用的原始方法相比，SCSit的识别读取一致性提高到97%，映射读取是原始读取的两倍。此外，SCSit的运行时间不到原来的10%。它可以准确、快速地分析Split-Seq原始数据并获得标记的读取，并有效地改进Split-Seq平台的单元格数据。SCSit的数据和来源可在GitHub网站https://github.com/shang-qian/SCSit.上查阅
SPLiT-seq provides a low-cost platform to generate single-cell data by labeling the cellular origin of RNA through four rounds of combinatorial barcoding. However, an automatic and rapid method for preprocessing and classifying single-cell sequencing (SCS) data from SPLiT-seq, which directly identified and labeled combinatorial barcoding reads and distinguished special cell sequencing data, is currently lacking. Here, we develop a high-efficiency preprocessing tool for single-cell sequencing data from SPLiT-seq (SCSit), which can directly identify combinatorial barcodes and UMI of cell types and obtain more labeled reads, and remarkably enhance the retained data from SCS due to the exact alignment of insertion and deletion. Compared with the original method used in SPLiT-seq, the consistency of identified reads from SCSit increases to 97%, and mapped reads are twice than the original. Furthermore, the runtime of SCSit is less than 10% of the original. It can accurately and rapidly analyze SPLiT-seq raw data and obtain labeled reads, as well as effectively improve the single-cell data from SPLiT-seq platform. The data and source of SCSit are available on the GitHub website https://github.com/shang-qian/SCSit.
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3.5
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Vieira Braga FA;Teichmann SA;Chen X
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