人类基因组数据质量评估研究

严维军; 赵正宜; 熊行创

doi:10.12338/j.issn.2096-9015.2023.0089

人类基因组数据质量评估研究

doi: 10.12338/j.issn.2096-9015.2023.0089

中国计量科学研究院，北京 100029

基金项目: 国家重点研发计划（2021YFF0600100）。

详细信息

作者简介:
严维军（1998-），中国计量科学研究院在读研究生，研究方向：人类基因组数据质量评估，邮箱：yanweijun@nim.ac.cn

通讯作者:
熊行创（1979-），中国计量科学研究院研究员，研究方向：测试计量数据质量评估，邮箱： xiongxch@nim.ac.cn

中图分类号: TB99
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- 文章访问数: 287
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- 被引次数: 0
出版历程
- 收稿日期: 2023-03-27
- 录用日期: 2023-05-09
- 修回日期: 2023-05-23
- 网络出版日期: 2023-08-07

A Study on Quality Assessment of Human Genome Data

National Institute of Metrology, Beijing 100029, China

摘要

摘要: 随着高通量测序技术的发展，研究人员现已具备对人类基因组测序数据进行深度分析和处理的能力，数据质量无疑成为影响数据分析结果可信度的决定性因素。因此，精确的数据质量评估成为至关重要的环节，其目的在于避免不必要的损失并确保结果的准确性。学术界和产业界都高度重视数据质量的评估，提出了大量的质量评估方法并开发了大量的工具，例如FastQC、Qualimap等软件工具，以及各类标准物质和标准参考数据，为数据质量评估提供了有力支持。然而，系统的研究各个质量评估环节的工具集以及对各类工具集的特点汇总相对较少，数据的质量评估的过程仍存在诸多问题和挑战。为评估人类基因组数据工作提供帮助，深入分析了上述问题的解决策略，并提供了一些具有实践意义的建议，以期提供参考。
- 计量学 /
- 人类基因组 /
- 数据 /
- 质量评估 /
- 评估指标 /
- 工具
Abstract: In the wake of the advancements in high-throughput sequencing technology, researchers are now equipped with the capacity to conduct in-depth analyses and processing of human genome sequencing data. The quality of these data inevitably serves as a pivotal factor impacting the credibility of analysis results. As such, precise quality assessment becomes a paramount process to circumvent needless loss and to ascertain the accuracy of outcomes. Both the academic and industrial communities place significant emphasis on data quality assessment, having introduced numerous methods for such assessment and developed a multitude of tools like FastQC and Qualimap software, along with various standard materials and standard reference data, which collectively underpin data quality assessment. However, there are scant systematic investigations of toolsets employed in each assessment stage and summarizations of toolset characteristics. Furthermore, the process of data quality assessment is laden with numerous issues and challenges. To aid human genome data assessment endeavors, this paper delves into potential solutions for these problems and puts forth several practically significant suggestions for reference.
- metrology /
- human genome /
- data /
- quality assessment /
- assessment metrics /
- tools

HTML全文

图 1 人类基因组测序数据质量评估总流程图

Figure 1. Comprehensive flowchart of human genome sequencing data quality assessment

下载: 全尺寸图片幻灯片

表 1 各类对齐前质量评估工具的评估指标比较

Table 1. Comparison of evaluation metrics for various pre-alignment quality assessment tools

评估指标	FastQC	fastp	NGS QC Toolkit	HTQC	SolexaQA	SOAPnuke	BIGpre	FastQ Screen
总读取数量	√	√	√	√	√	√
读长分布	√	√	√	√	√
碱基分布	√	√	√	√		√
GC含量	√	√	√				√
质量分数	√	√	√	√	√	√	√
接头序列的污染	√	√
其他物种的污染								√
序列重复水平	√	√
过度表达的序列	√
k-mer分析	√	√

下载: 导出CSV

表 2 各类对齐前质量评估工具的特点和下载链接

Table 2. Characteristics and download links for various pre-alignment quality assessment tools

工具	特点	下载链接
FastQC	评估指标较为全面	https://www.bioinformatics.babraham.ac.uk/projects/fastqc/
HTQC	评估、序列修剪	https://sourceforge.net/projects/htqc/
NGS QC Toolkit	评估、序列修剪	https://github.com/mjain-lab/NGSQCToolkit
fastp	双端测序评估、修剪	https://github.com/OpenGene/fastp
SolexaQA	序列根据质量分类	https://solexaqa.sourceforge.net/
BIGpre	检测、处理重复序列	http://bigpre.sourceforge.net/
FastQ Screen	污染评估	https://www.bioinformatics.babraham.ac.uk/projects/fastq_screen/
SOAPnuke	MapReduce加速	https://github.com/BGI-flexlab/SOAPnuke
RabbitQC	充分利用硬件加速	https://github.com/ZekunYin/RabbitQC

下载: 导出CSV

表 3 流行的短读取对齐工具

Table 3. Popular tools for short read alignment

工具	优点	下载链接
Bowtie2	支持间隙、局部和双端对齐模式	https://github.com/BenLangmead/bowtie2
BWA-MEM2	使用 FM 索引和8x压缩	https://github.com/bwa-mem2/bwa-mem2
Gapped BLAST	支持间隙对齐	https://blast.ncbi.nlm.nih.gov/Blast.cgi
Subread	采用种子和投票策略	https://subread.sourceforge.net/
HISAT2	采用分层索引	https://github.com/DaehwanKimLab/hisat2

下载: 导出CSV

表 4 各类对齐后质量评估工具的评估指标

Table 4. Evaluation metrics for various post-alignment quality assessment tools

评估指标	Picard	QPLOT	Qualimap2	SAMstat	verifyBamID
映射率	√	√	√	√
插入尺寸	√	√	√
序列重复水平	√	√	√
碱基分布	√	√	√	√
映射质量	√	√	√	√
覆盖深度	√	√	√
GC含量	√	√	√
错配率	√	√	√	√
覆盖深度	√	√
覆盖率	√	√
污染估计	√	√			√

下载: 导出CSV

表 5 各类对齐后质量评估工具的特点和下载链接

Table 5. Characteristics and download links for various post-alignment quality assessment tools

工具	特点	下载链接
SAMstat	评估指标统计	https://samstat.sourceforge.net/
QPLOT	评估指标统计	https://github.com/statgen/qplot
Qualimap2	多样本处理	http://qualimap.conesalab.org/
Picard	自定义所需评估指标	https://github.com/broadinstitute/picard
verifyBamID	检测污染	https://github.com/Griffan/VerifyBamID

下载: 导出CSV

表 6 流行的短读取对齐工具

Table 6. Popular tools for short read alignment

工具	方法	下载链接
VarScan2	启发式方法	https://github.com/dkoboldt/varscan
SomaticSniper	联合基因型分析	https://github.com/genome/somatic-sniper
SAMtools	联合基因型分析	https://github.com/samtools/samtools
Strelka	等位基因频率分析	https://github.com/target/strelka
MuTect	等位基因频率分析	https://github.com/broadinstitute/mutect
MuTect2	单倍型模型	https://github.com/broadinstitute/gatk
FreeBayes	单倍型模型	https://github.com/freebayes/freebayes
Strelka2	分层单倍型模型	https://github.com/Illumina/strelka

下载: 导出CSV

表 7 各类变异可信度质量评估工具的特点和下载链接

Table 7. Characteristics and download links for various mutation confidence quality assessment tools

工具	特点	下载链接
hap.py	将 VCF 与标准数据集进行比较	https://github.com/Illumina/hap.py
rtg-tools	在单倍型水平上进行变异比较	https://github.com/RealTimeGenomics/rtg-tools/
vgraph	使用变异图比较遗传变异	https://github.com/bioinformed/vgraph/
VBT-TrioAnalysis	变体比较和孟德尔违规检测	https://github.com/sbg/VBT-TrioAnalysis

下载: 导出CSV

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