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超越测序:以PJL为例重新审视注释

Beyond sequencing: re-visiting annotations for PJL as a test case.

作者信息

Khan Waqasuddin, Ghani Aisha, Azmi Muhammad Bilal, Razzak Safina Abdul

机构信息

Jamil-ur-Rahman Center for Genome Research, Dr. Panjwani Center for Molecular Medicine and Drug Research, International Center for Chemical and Biological Sciences, University of Karachi, Karachi, 75270, Pakistan.

Department of Biochemistry, Dow Medical College, Dow University of Health Sciences, Baba-E-Urdu Road, Karachi, 74200, Pakistan.

出版信息

BMC Res Notes. 2019 Jul 31;12(1):467. doi: 10.1186/s13104-019-4508-5.

Abstract

OBJECTIVES

Current developments in sequencing techniques have enabled rapid and high-throughput generation of sequence data. However, there is a growing gap between the generation of raw sequencing data and the extraction of meaningful biological information. Variant annotation is a crucial step in the analysis of genome sequencing data. Incorrect or incomplete annotations can cause researchers to dilute interesting variants in a pool of false positives. We require consistent, accurate and reliable annotation of variants for making diagnostic and treatment decisions. Current annotation depends on the set of transcripts, and software used can be managed, with sufficient care, in the research context. Careful thought needs to be given to the choice of transcript sets and software packages for variant annotation in sequencing studies. In this project, the main objective is to analyze the genetic variants observed in Pakistani population data within the 1000 genomes project (1KGP).

RESULTS

We characterized only SNVs and InDels types of genetic variations, in total ~ 1.4 million variants. Besides this, we also annotated the genetic variants with multiple annotations tools, ANNOVAR and SnpEff and compared the differential results. Our population-specific catalogue will enhance future studies on the functional impact at protein level.

摘要

目标

测序技术的当前发展已实现序列数据的快速和高通量生成。然而,原始测序数据的生成与有意义的生物学信息的提取之间的差距正在不断扩大。变异注释是基因组测序数据分析中的关键步骤。不正确或不完整的注释可能导致研究人员在大量假阳性中忽略有趣的变异。我们需要对变异进行一致、准确和可靠的注释,以便做出诊断和治疗决策。当前的注释依赖于转录本集合,并且在研究背景下,所使用的软件在经过充分谨慎管理后是可行的。在测序研究中,需要仔细考虑用于变异注释的转录本集合和软件包的选择。在本项目中,主要目标是分析在千人基因组计划(1KGP)中的巴基斯坦人群数据中观察到的遗传变异。

结果

我们仅对单核苷酸变异(SNV)和插入缺失(InDel)类型的遗传变异进行了特征分析,总共约140万个变异。除此之外,我们还使用多种注释工具ANNOVAR和SnpEff对遗传变异进行注释,并比较了差异结果。我们的人群特异性目录将加强未来关于蛋白质水平功能影响的研究。

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The variant call format and VCFtools.变异调用格式和 VCFtools。
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