CRCNS: Computational Approach to Assess Replicability of Neurobehavior Phenotypes

CRCNS：评估神经行为表型可重复性的计算方法

基本信息

批准号：
9471546
负责人：
MOLLY A BOGUE
金额：
$ 25.23万
依托单位：
JACKSON LABORATORY
依托单位国家：
美国
项目类别：
财政年份：
2017
资助国家：
美国
起止时间：
2017-09-01 至 2020-05-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9471546
关键词：
Address Adopted Affect Algorithmic Software Analysis of Variance Animal Disease Models Behavior Behavioral Biochemistry Bioinformatics Biological Sciences Biometry Categories Code Collaborations Color Communities Complex Computational Science Computer software Confusion Coupled Data Databases Diagnostic Discipline Doctor of Philosophy Ensure Environment Faculty Failure Future Genes Genetic Genetically Engineered Mouse Genotype Head Health Human Institution International Investments Israel Journals Knowledge Laboratories Laboratory mice Left Maine Measures Medicine Methods Modeling Molecular Genetics Mollies Mouse Strains Mus Nature Neurobiology Neurologic Neurosciences Online Systems Operations Research Phenotype Policies Positioning Attribute Problem Solving Process Proteins Protocols documentation Published Comment Publishing Reagent Recommendation Reproducibility Research Research Personnel Research Proposals Resources Schools Science Scientist Standardization Testing The Jackson Laboratory Therapeutic Time Training Training Programs United States National Institutes of Health Universities Validation Work Zoology base behavior measurement behavioral study computational neuroscience cost cost effective data integration data sharing experience experimental study gaze gene function genetic strain improved mammalian genome mathematical sciences mutant neurobehavior neurobehavioral neurobehavioral disorder phenome phenotypic data pre-clinical research prevent programs relating to nervous system statistics tool user-friendly web app web interface

项目摘要

PROJECT DESCRIPTION (as submitted to NSF) CRCNS: US - Israel Data Sharing Proposal: Computational Approaches to Assess Replicability of Neurobehavioral Phenotypes Molly Bogue, Ph.D. (PI) Yoav Benjamini, Ph.D. (PI) The Jackson Laboratory Department of Statistics and Operations Research Bar Harbor, Maine USA School of Mathematical Sciences Sagol School ofNeuroscience Tel Aviv University ISRAEL Ilan Golani, Ph.D. (Co-Inv) Department of Zoology Wise Faculty of Life Sciences Sago! School of Neuroscience Tel Aviv University ISRAEL Iliana Oozes, Ph.D. (Co-Inv) Dept. of Human Molecular Genetics and Biochemistry Saclder Faculty of Medicine Sago! School of Neuroscience Tel Aviv University ISRAEL Neri Kaflcafi, Ph.D. (Co-Inv) Department of Statistics and Operations Research School of Mathematical Sciences Tel Aviv University ISRAEL Prior NSF and/or CRCNS Support: None 35 Introduction We are submitting a revised computational neuroscience proposal. Our original proposal received positive comments from reviewers last year under the Research Proposal mechanism. For example: "All reviewers were very enthusiastic about the transformative potential of solving the problem being addressed in the proposal, and were also enthusiastic about the basic framework underlying the proposed solution." However, previous reviewers thought our proposal was better aligned with the Data Sharing mechanism. Unfortunately, NSF-BSF did not support Data Sharing last year. This year it does and so we are reapplying under the Data Sharing mechanism. We have revised and improved our application to address previous reviewers' concerns. Their concerns can be grouped in four categories: 1) difficulty in acquiring new data, 2) challenge in dealing with sparse data, 3) lack of specific details about our approach, and 4) misconception that The Jackson Laboratory is a for-profit organization and that this would affect data release. JAX is a not-for-profit research institution and is a world leader in providing public bioinformatics resources for the laboratory mouse without any restrictions. Background and Significance Concernsaboutreplicabilityofneurobehavioralphenotypes The scientific and lay communities have become increasingly concerned with published "discoveries" that are not replicable [10-12]. Prominent institutions and journals, including NIH [13], Science [14] and Nature [15], have recently announced policy positions on the subject, yet there is still confusion and debate regarding how the problem should be addressed. While documented in all scientific fields, the problem was specifically noted in preclinical research [16] including mouse neurological and behavioral studies [7]. Note: To prevent confusion, we use the term "replicability" for replicating results in other studies and "reproducibility" for reproducing conclusions within the same study [17, 18]. ANOVA Variance Replicable Prnportlon of total variance G* L ns Yes 0% 100% Gxl ns G* L * Yes 0% 100% Gxl ns G* L * Yes 0'1/o 100% Gxl ns G ns L * No 0% 100% Gxl * g1 g2 Figure 1. Illustration of the significance of the main effects of Genotype (G), Laboratory (L) and the Genotype x Laboratory (GxL) interaction. Data for four different behavioral measures are depicted in the left panel across three laboratories (color coded) for two genotypes (g). ANOVA results for each are shown where *=significant; ns=not significant. Proportion of total variance (%) is illustrated by color-coded horizontal bars. Replicability, based on the significance of GxL, is indicated on the right for each measure. Measuring quantitative phenotypes of genetically engineered mouse strains has become a central strategy for discovering mammalian gene function, and for characterizing animal models of disease in which putative cures can be researched (for reviews see [19, 20]). The International Mouse Phenotyping Consortium (IMPC) [21, 22] coordinates an international effort to phenotype thousands of mutant strains, eventually achieving a functional annotation of most of the ~20,000 protein-coding genes in the mammalian genome. An essential aspect of this work is making high- throughput phenotyping data accessible to the scientific community in public databases [23, 24]. The utility of this undertaking, however, critically depends on the ability to replicate phenotyping results in other laboratories. This large project is but one example of the general need for replicability of mouse phenotyping, which has been repeatedly raised and discussed (e.g., [27 25 ,7] with no satisfactory solution yet adopted. Any solution that is likely to be adopted by experimentalists for 36

项目描述（提交给NSF） CRCN：美国 - 以色列数据共享建议：计算方法评估神经行为表型的可复制性莫莉·博格（Molly Bogue），博士（PI）Yoav Benjamini博士（PI）杰克逊实验室统计与运营研究部缅因州巴港数学科学学院 sagol seaduroscience 特拉维夫大学以色列 Ilan Golani博士（共插入）动物学系明智的生命科学学院西马！神经科学学校特拉维夫大学以色列 Iliana Oozes博士（共插入）人分子遗传学和生物化学系萨克尔德医学学院西马！神经科学学校特拉维夫大学以色列 Neri Kaflcafi博士（共插入）统计和运营研究部数学科学学院特拉维夫大学以色列先前的NSF和/或CRCN支持：无 35 介绍我们正在提交经过修订的计算神经科学建议。我们的原始提议得到了积极的态度去年根据研究建议机制的评论。例如：“全部评论者对解决问题的变革潜力非常热情在提案中解决，也对提议的基本框架充满热情解决方案。”但是，以前的审稿人认为我们的建议与数据共享更好地保持一致机制。不幸的是，NSF-BSF去年不支持数据共享。今年这样做，所以我们在数据共享机制下重新申请。我们已经修订并改善了我们的应用程序解决以前的审稿人的疑虑。他们的担忧可以分为四类：1）困难获取新数据，2）处理稀疏数据的挑战，3）缺乏有关我们的具体细节方法，以及4）误解杰克逊实验室是一个营利性组织，这是会影响数据发布。 Jax是一家非营利研究机构，是世界领导者实验室鼠标的公共生物信息学资源无限制。背景和意义关注纳罗巴甲型型科学和外行社区已经越来越关注已发表的“发现” 不可复制[10-12]。重要的机构和期刊，包括NIH [13]，科学[14]和大自然[15]，最近宣布了有关该主题的政策立场，但仍然存在混乱和有关如何解决问题的辩论。虽然在所有科学领域都记录了在临床前研究中特别注意了问题[16]，包括小鼠神经和行为。研究[7]。注意：为防止混乱，我们使用“可复制性”一词来复制其他结果在同一研究中得出结论的研究和“可重复性” [17，18]。方差分析差异可复制总差异的prnportlon g* 是的 0％100％ GXL NS g* L *是 0％100％ GXL NS g* L *是 0'1/o 100％ GXL NS G NS L *不 0％100％ GXL * G1 G2 图1。说明了主要影响的重要性基因型（G），实验室（L）和基因型X实验室（GXL）相互作用。四种不同行为措施的数据在三个实验室的左面板中描绘（颜色编码）两种基因型（G）。每个方差分析的结果是显示在其中 *=显着; NS =不重要。比例的总方差（％）用颜色编码的水平说明酒吧。基于GXL的重要性的可复制性是在右侧指示每个度量。测量定量表型基因工程的小鼠菌株具有成为发现的核心策略哺乳动物基因功能，以及表征疾病的动物模型可以研究哪种假定治疗方法（因为评论参见[19，20]）。国际小鼠表型联盟（IMPC） [21，22]协调国际努力对于表型数千种突变菌株，最终获得功能注释在约20,000个蛋白质编码基因中的大多数在哺乳动物基因组中。必不可少的这项工作的方面使可以访问的吞吐量表型数据公共科学界数据库[23，24]。这个实用性然而，承诺依赖于复制表型结果的能力在其他实验室。这个大项目是但是一般需要的一个例子小鼠表型的可复制性，这是反复提出和讨论（例如[27 25，7]，没有令人满意的解决方案尚未采用。任何解决方案可能被实验者采用 36