PLOS ONE2014-01-22 3:19 AM

A Field Guide to Genomics Research 基因组学研究的领域指南

Abstract
High-throughput technologies are enabling scientists to profile genomes, transcriptomes, proteomes, and metabolomes at an unprecedented scale [1]. All this “-omics” research (let's call it genomics for simplicity) is exciting—and game changing—but it's also fraught with dangers for the tenderfoot. Here, we've put together a brief “field guide” for those wishing to visit the genomics frontier, in which we use caricatures to illustrate various pitfalls that can beset those who inhabit this new territory. By documenting the behaviors of these common types, we hope to guide researchers in their quest to apply sound practices when designing genomics experiments and analyzing the resulting data. Many of the tendencies we have encountered are not specific to genomics research, but they are particularly acute in this field due to its interdisciplinary nature and the complexity of the data it produces.
Drawing upon our own experiences in various roles on genomics projects—and at the risk of generalizing—we note the prevalence of no fewer than six different character traits that lead to problems in experimental design (“the farmer”), data interpretation (“the gold miner” and “the cowboy”), collaboration (“the hermit” and “the master and servant”), and civic virtue (“the jailer”). This list is not comprehensive, but we hope it will guide new adventurers in the approaches and attitudes needed to stake their claim in this novel terrain. 论文摘要 高通量技术使得科学家能以前所未有的规模来描绘染色体,转录物,蛋白质体和代谢组。所有这些“xx组学”研究 (简单起见姑且称之为基因组学)令人无比激动且改写了研究历史,同时对初涉者来说也险阻重重。在此我们为那些渴望一览基因组学未垦地的探索者们给出一份简短“涉域指南”,通过漫画形式来形象扫盲各式陷阱,以免那些有志于在新领域终生死磕的新手们在各种陷阱里挂掉。通过记录这些常见类型的惯例特征,我们希望在求索路上引导研究者在设计基因组实验和分析所得数据时进行正确演练。许多我们已遇到的研究趋势并不特限于基因组学研究,但由于其产生的跨学科性和数据复杂性使得它们在这一领域中尤其敏感。根据我们在基因组学项目各种角色体验所得的经验和风险概述,我们注意到不下六种不同性格特征的患病率导致了实验设计(“农夫”),数据解读(“黄金矿工”和“牛仔”),合作(“隐士”和“主仆”),和公民美德(“狱卒”)出现问题。这个列表并不全面, 但我们希望它会引领新领域内敢于在方法和态度上放手一博的新探索。

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