The correctness of large scale analysis of genomic data

IF 1.8 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Foundations of Computing and Decision Sciences Pub Date : 2021-12-01 DOI:10.2478/fcds-2021-0024
Pawel Wojciechowski, Karol Krause, P. Lukasiak, J. Błażewicz
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Abstract

Abstract Implementing a large genomic project is a demanding task, also from the computer science point of view. Besides collecting many genome samples and sequencing them, there is processing of a huge amount of data at every stage of their production and analysis. Efficient transfer and storage of the data is also an important issue. During the execution of such a project, there is a need to maintain work standards and control quality of the results, which can be difficult if a part of the work is carried out externally. Here, we describe our experience with such data quality analysis on a number of levels - from an obvious check of the quality of the results obtained, to examining consistency of the data at various stages of their processing, to verifying, as far as possible, their compatibility with the data describing the sample.
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基因组数据大规模分析的正确性
从计算机科学的角度来看,实施大型基因组计划是一项艰巨的任务。除了收集许多基因组样本并对其进行测序外,在其生产和分析的每个阶段都要处理大量数据。数据的有效传输和存储也是一个重要问题。在这样一个项目的执行过程中,需要保持工作标准并控制结果的质量,如果部分工作是外部执行的,这可能会很困难。在这里,我们描述了我们在多个层面上进行此类数据质量分析的经验——从对所获得结果质量的明显检查,到在处理的各个阶段检查数据的一致性,再到尽可能地验证它们与描述样本的数据的兼容性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Foundations of Computing and Decision Sciences
Foundations of Computing and Decision Sciences COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-
CiteScore
2.20
自引率
9.10%
发文量
16
审稿时长
29 weeks
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