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QC-Chain: Fast and Holistic Quality Control Method for Next-Generation Sequencing Data
Zhou, Qian1,2; Su, Xiaoquan1,2; Wang, Anhui1,2,3; Xu, Jian1,2; Ning, Kang1,2
2013-04-02
Source PublicationPLOS ONE
Volume8Issue:4Pages:e60234
Abstract Next-generation sequencing (NGS) technologies have been widely used in life sciences. However, several kinds of sequencing artifacts, including low-quality reads and contaminating reads, were found to be quite common in raw sequencing data, which compromise downstream analysis. Therefore, quality control (QC) is essential for raw NGS data. However, although a few NGS data quality control tools are publicly available, there are two limitations: First, the processing speed could not cope with the rapid increase of large data volume. Second, with respect to removing the contaminating reads, none of them could identify contaminating sources de novo, and they rely heavily on prior information of the contaminating species, which is usually not available in advance. Here we report QC-Chain, a fast, accurate and holistic NGS data quality-control method. The tool synergeticly comprised of user-friendly tools for (1) quality assessment and trimming of raw reads using Parallel-QC, a fast read processing tool; (2) identification, quantification and filtration of unknown contamination to get high-quality clean reads. It was optimized based on parallel computation, so the processing speed is significantly higher than other QC methods. Experiments on simulated and real NGS data have shown that reads with low sequencing quality could be identified and filtered. Possible contaminating sources could be identified and quantified de novo, accurately and quickly. Comparison between raw reads and processed reads also showed that subsequent analyses (genome assembly, gene prediction, gene annotation, etc.) results based on processed reads improved significantly in completeness and accuracy. As regard to processing speed, QC-Chain achieves 7–8 time speed-up based on parallel computation as compared to traditional methods. Therefore, QC-Chain is a fast and useful quality control tool for read quality process and de novo contamination filtration of NGS reads, which could significantly facilitate downstream analysis.
QC-Chain is publicly available at: http://www.computationalbioenergy.org/qc-chain.html; Next-generation sequencing (NGS) technologies have been widely used in life sciences. However, several kinds of sequencing artifacts, including low-quality reads and contaminating reads, were found to be quite common in raw sequencing data, which compromise downstream analysis. Therefore, quality control (QC) is essential for raw NGS data. However, although a few NGS data quality control tools are publicly available, there are two limitations: First, the processing speed could not cope with the rapid increase of large data volume. Second, with respect to removing the contaminating reads, none of them could identify contaminating sources de novo, and they rely heavily on prior information of the contaminating species, which is usually not available in advance. Here we report QC-Chain, a fast, accurate and holistic NGS data quality-control method. The tool synergeticly comprised of user-friendly tools for (1) quality assessment and trimming of raw reads using Parallel-QC, a fast read processing tool; (2) identification, quantification and filtration of unknown contamination to get high-quality clean reads. It was optimized based on parallel computation, so the processing speed is significantly higher than other QC methods. Experiments on simulated and real NGS data have shown that reads with low sequencing quality could be identified and filtered. Possible contaminating sources could be identified and quantified de novo, accurately and quickly. Comparison between raw reads and processed reads also showed that subsequent analyses (genome assembly, gene prediction, gene annotation, etc.) results based on processed reads improved significantly in completeness and accuracy. As regard to processing speed, QC-Chain achieves 7-8 time speed-up based on parallel computation as compared to traditional methods. Therefore, QC-Chain is a fast and useful quality control tool for read quality process and de novo contamination filtration of NGS reads, which could significantly facilitate downstream analysis. QC-Chain is publicly available at: http://www.computationalbioenergy.org/qc-chain.html.
SubtypeArticle
Subject Area功能基因组
WOS HeadingsScience & Technology
DOI10.1371/journal.pone.0060234
WOS KeywordSHORT READ ALIGNMENT ; ULTRAFAST ; ARB
Indexed BySCI
Language英语
WOS Research AreaScience & Technology - Other Topics
WOS SubjectMultidisciplinary Sciences
WOS IDWOS:000317717300074
Citation statistics
Document Type期刊论文
Identifierhttp://ir.qibebt.ac.cn/handle/337004/1621
Collection单细胞中心组群
Affiliation1.Chinese Acad Sci, CAS Key Lab Biofuels, Qingdao Inst Bioenergy & Bioproc Technol, Qingdao, Shandong, Peoples R China
2.Chinese Acad Sci, Shandong Key Lab Energy Genet, Qingdao Inst Bioenergy & Bioproc Technol, Qingdao, Shandong, Peoples R China
3.China Three Gorges Univ, Coll Comp & Informat Technol, Yichang, Hubei, Peoples R China
Recommended Citation
GB/T 7714
Zhou, Qian,Su, Xiaoquan,Wang, Anhui,et al. QC-Chain: Fast and Holistic Quality Control Method for Next-Generation Sequencing Data[J]. PLOS ONE,2013,8(4):e60234.
APA Zhou, Qian,Su, Xiaoquan,Wang, Anhui,Xu, Jian,&Ning, Kang.(2013).QC-Chain: Fast and Holistic Quality Control Method for Next-Generation Sequencing Data.PLOS ONE,8(4),e60234.
MLA Zhou, Qian,et al."QC-Chain: Fast and Holistic Quality Control Method for Next-Generation Sequencing Data".PLOS ONE 8.4(2013):e60234.
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