On the optimal trimming of high-throughput mRNA sequence data.

On the optimal trimming of high-throughput mRNA sequence data.
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DOI:
10.3389/fgene.2014.00013
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发表时间:
2014
影响因子:
3.7
通讯作者:
Macmanes MD
Macmanes MD
中科院分区:
生物学3区
文献类型:
--
作者:
Macmanes MD

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高通量测序技术的广泛和快速采用为研究人员提供了深入了解进化变化背后的基因组水平过程的机会,也许更重要的是,基因型和表型之间的联系。特别是,对功能生物学和适应性感兴趣的研究人员已经使用这些技术对特定组织的mRNA转录组进行测序,而这些转录组又经常与其他组织或其他具有不同表型的个体进行比较。虽然这些技术非常强大,但需要仔细注意数据质量。特别是,由于高通量测序比传统的Sanger测序更容易出错,因此高质量的序列reads修剪应该是所有数据处理管道中的重要步骤。虽然存在一些用于质量修剪的软件包,但没有开发出修剪细节的一般指导方针。在这里,使用经验推导的序列数据,我提供了关于修剪的最佳强度的一般建议,特别是在mRNA-Seq研究中。虽然非常积极的质量修剪是常见的,但这项研究表明,更温和的修剪,特别是那些Phred评分<2或<5的核苷酸,对于大多数研究来说是最理想的。
The widespread and rapid adoption of high-throughput sequencing technologies has afforded researchers the opportunity to gain a deep understanding of genome level processes that underlie evolutionary change, and perhaps more importantly, the links between genotype and phenotype. In particular, researchers interested in functional biology and adaptation have used these technologies to sequence mRNA transcriptomes of specific tissues, which in turn are often compared to other tissues, or other individuals with different phenotypes. While these techniques are extremely powerful, careful attention to data quality is required. In particular, because high-throughput sequencing is more error-prone than traditional Sanger sequencing, quality trimming of sequence reads should be an important step in all data processing pipelines. While several software packages for quality trimming exist, no general guidelines for the specifics of trimming have been developed. Here, using empirically derived sequence data, I provide general recommendations regarding the optimal strength of trimming, specifically in mRNA-Seq studies. Although very aggressive quality trimming is common, this study suggests that a more gentle trimming, specifically of those nucleotides whose Phred score <2 or <5, is optimal for most studies across a wide variety of metrics.
DOI: 10.7717/peerj.113
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期刊: PeerJ
影响因子: 2.7
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