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不同管道版本中的工具组合如何影响RNA-seq分析的结果

Louisa Wessels Perelo¹, Gisela Gabernet¹, Daniel Straub¹

¹Quantitative Biology Center (QBiC), University of Tübingen, Otfried-Müller-Str. 37, 72076 Tübingen, Baden-Württemberg, 72076, Germany.

NAR genomics and bioinformatics

|March 8, 2024

概括

对比RNA-seq分析工具对于一致的结果至关重要. 不同的nf-core/rnaseq管道设置显示高基因分类重叠,但在低度基因和基因异型中观察到偏差.

科学领域:

生物信息学是一种生物信息学.
计算生物学计算生物学
基因组学就是基因组学.

背景情况:

数据分析工具,包括RNA测序 (RNA-seq) 管道,经常更新.
这些工具的变化可能会影响随时间推移结果的可比性.
确保长期转录组学研究的一致性对于可靠的数据解释至关重要.

研究的目的:

评估 nf-core/rnaseq 管道内的不同工作流选择对数据可比性的影响.
为了比较各种生物信息学工具和管道版本的性能,用于RNA-seq分析.
确定影响差异性基因表达分析结果的因素.

主要方法:

测试了五种不同的nf-core/rnaseq管道配置:STAR+Salmon,STAR+RSEM,STAR+featureCounts,HISAT2+featureCounts和伪对齐型鱼.
这些配置应用于三个不同的生物数据集:人类,阿拉比多普西斯和斑马鱼,所有这些数据集都包括外部RNA控制联盟 (ERCC) 的尖端插入.
对比分析的重点是内源基因和尖端基因的折叠变化率和差异性表达.

主要成果:

在测试管道设置中观察到差异性基因分类的85%重叠.
发现有偏差的基因主要是表达度较低的基因.
基因异型和外型的数量显著影响了分析结果,以前的功能计数版本对ERCCspike-ins等单异型基因的敏感性更高.

结论:

虽然存在高一致性,但管道设置的变化可以引入偏差,特别是在低表达基因和具有复杂异型结构的基因中.
建议在长期RNA-seq研究中保持管道版本的一致性,以确保数据可比性.
在过渡到新的管道版本时,建议同时运行旧版本和新版本,以验证基因向一致性.

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