Big-data analysis tools for bridging the gap between omics and earth system science

海洋科学的未来在于收集和分析来自滑翔机、卫星和高通量测序等新技术的大数据。这在数学和计算技术方面提出了新的挑战，我们需要对生成的大量数据进行查询，以及允许我们弥合不同数据集之间差距所需的模型。这一挑战的一个重要例子是整合收集的海洋微生物数据集。数据集的范围从群落宏基因组/转录组的测序，细胞大小和分布的测量，到微生物栖息环境中基于滑翔机的温度、盐度和营养物质的测量。该项目的目的是开发新的大数据分析算法和工具来查询、合并和整合这些不同的数据集。为此，我们将采用并开发生物信息学和数据科学方面的尖端技术。我们的新工具将允许研究人员提取隐藏在数据中的模式，从而回答重要的问题，例如原位微生物多样性如何与环境因素相关，以及根据其功能（例如微量气体产生）和生态作用（例如入侵物种）将哪些基因和物种作为目标。在目前的NEXUSS博士项目中，我们正在将牛津纳米孔测序技术应用于破冰船上。我们已经建立了极地微生物的板载和原位测序协议，并期望在2018年秋季之前获得在受控环境条件下生长的单个分离株和混合（模拟）群落的测序数据。然后计划从2019年初开始使用新技术进行年度南极探险，包括马赛克，这是2020年在破冰船上进行的全年探险，将使用各种自主观测系统（如滑翔机）收集数据。所有这些活动将产生大量相互关联的排序和环境数据集。然而，分析这些数据所需的生物信息学和数据集成工具在数据集成的速度和能力方面都远远落后。为了应对这一挑战，我们将首先开发新的生物信息学工具和算法，使我们能够充分利用纳米孔技术，设计新的算法来快速评估测序数据中的多样性和假定的基因功能。在此基础上，我们将采用数据仓库和机器学习等数据科学技术来设计软件，使我们和其他研究人员能够合并数据，从而发现复杂海洋微生物数据集中的突出模式。NEXUSS CDT为环境科学提供尖端智能和自主观测系统的应用和开发方面的最先进，经验丰富的培训，以及全面的个人和专业发展。通过与广泛的学术、研究和工业/政府/政策合作伙伴网络的互动，学生将有广泛的机会扩展他们的多学科视野。该学生将在东安格利亚大学注册。具体培训将包括：数据科学、机器学习、软件开发、生物信息学、编程、序列分析、极性微生物和分子生物学。

The future of ocean science lies in the collection and analysis of big-data coming from new technologies such as gliders, satellites and high-throughput sequencing. This presents new challenges both in terms of the mathematical and computational techniques that we need to interrogate the huge amount of data being generated, as well as the models required to allow us to bridge the gap between disparate datasets. An important example of this challenge is the integration of data sets collected for marine microbes. Data sets range right through sequencing of metagenomes/transcriptomes of communities, measurements of cell sizes and distributions, to glider-based measurements of temperature, salinity, and nutrients in the environments which the microbes inhabit. The aim of this project is to develop new big-data analysis algorithms and tools to interrogate, merge and integrate these diverse datasets. To do this, we will employ and develop cutting-edge techniques in bioinformatics and data science. Our new tools will allow researchers to extract patterns hidden in their data, so as to answer important questions such as how in situ microbial diversity is related to environmental factors, and which genes and species to target in terms of their function (e.g. trace-gas production) and ecological role (e.g. invasive species).In a current NEXUSS PhD project, we are adapting Oxford nanopore-sequencing technology to be used aboard ice-breakers. We have established a protocol for onboard and in situ sequencing of polar microbes and expect to have sequencing data from single isolates and mixed (mock) communities grown in controlled environmental conditions by autumn 2018. Annual Antartic expeditions are then planned using the new technology starting in early 2019 including MOSAiC, a year-round expedition onboard an icebreaker in 2020 which will collect data using various autonomous observing systems such as gliders. All of these activities will result in a huge array of interrelated sequencing and environmental data sets. However, the bioinformatics and data integration tools needed to analyse these data are lagging far behind both in terms of speed and ability to integrate the data. To address this challenge, we will first develop new bioinformatics tools and algorithms allowing us to fully harness the Nanopore technology, devising new algorithms for quickly assessing diversity and putative gene functions in sequencing data. Building on this, we will employ data science techniques such as data-warehousing and machine learning to design software allowing us and other researchers to merge the data so as to discover salient patterns in complex marine microbe datasets.The NEXUSS CDT provides state-of-the-art, highly experiential training in the application and development of cutting-edge Smart and Autonomous Observing Systems for the environmental sciences, alongside comprehensive personal and professional development. There will be extensive opportunities for students to expand their multi-disciplinary outlook through interactions with a wide network of academic, research and industrial / government / policy partners. The student will be registered at The University of East Anglia. Specific training will include: data science, machine learning, software development, bioinformatics, programming, sequence analysis, polar microbes, and molecular biology.