BBSRC-NSF/BIO: Integrative analysis and Visualisation of Fly Cell Atlas datasets to enable cross-species comparisons

果蝇（Drosophila melanogaster）在上个世纪一直是遗传学研究的基础。它被用于许多研究领域作为选择的模式生物，因为它提供了在实验室中研究遗传学并将发现应用于人类遗传学的能力。它作为一个模型的使用是由于两个因素：第一，它的遗传密码可以在实验室中相对容易地操纵，这加上一个短的生命周期，提供了一种手段，通过它可以快速研究基因或途径的功能。其次，绝大多数基本的生化机制和途径在苍蝇和人类之间是保守的。事实上，导致人类疾病的基因中有75%在苍蝇中发现，因此，在苍蝇中收集的数据可以用于深入了解人类体内的相同过程。一种新技术--单细胞RNA测序（scRNA-seq）的出现，提供了关于哪些基因是从单细胞中开启或最活跃的信息。在果蝇群落中，这提供了将细胞簇和细胞类型快速映射到整个解剖结构并将其与表型和功能联系起来的能力。来自不同物种的scRNA-seq数据集数量的增加导致了单细胞表达图谱（scEA）的发展。这是一个门户网站，使用户能够更容易地可视化和解释这些数据。预计果蝇单细胞数据的水平将从10个数据集增加到2020年的约100个数据集，并在2021年进一步增加两倍。科学利用这些数据的关键将是用户不仅能够有效地分析苍蝇数据，而且能够检查苍蝇数据与人类或小鼠数据集之间的相互联系。在这个项目中，我们将提供一种方法，通过这种方法，苍蝇数据集可以很容易地被解释，并通过scEA链接到小鼠和人类数据集。scEA目前拥有超过50万个检测的scRNA-seq数据，其中包括人类细胞图谱（HCA）和小鼠细胞图谱（MCA）的数据。该项目将开发分析管道，以联合收割机现有和新兴的数据集，以及必要的计算基础设施来托管Fly Cell Atlas（FCA）数据集。ScEA将为用户提供一个易于导航的Web服务，具有探索性查询功能，此外还有数据下载功能，用于进一步的数据分析。这项服务将与现有的果蝇资源、Flybase、Virtual Fly Brain和哈佛大学的果蝇资源完全整合。该项目还将制定数据集注释程序。该注释步骤为数据添加了额外的科学信息，为用户提供了更高水平的生物学理解，从而有助于解释和分析。该注释将扩展现有的FlyBase解剖本体，该本体是用于描述苍蝇解剖结构的受控词汇表结构，这将确保新资源和现有资源之间的完全兼容性。scEA将开发并提供一种方法，通过这种方法可以轻松地可视化和挖掘细胞类型的数据，同时还为苍蝇社区提供将其科学专业知识贡献给注释的能力。将进一步开发scEA用户界面，以提供更高水平的跨物种查询能力，因为所产生的FCA将在scEA内与HCA、MCA和任何其他数据集相关联，从而实现跨物种比较，这将有助于发现新的生物学见解。该项目旨在为果蝇群体提供连接、再利用和再分析数据集的实用解决方案，从而缩小将模式生物（如果蝇）的生物学发现转化为人类发现的差距，反之亦然。该项目将使这一比较分析的结果迅速提供给不断增长的用户群体。

The fruit fly, Drosophila melanogaster, has for the last century been fundamental to the study of genetics. It is used in many areas of research as the model organism of choice, as it provides the ability to study genetics in the laboratory and apply findings to human genetics. Its use as a model is due to two factors: First, its genetic code can be relatively easily manipulated in the laboratory and this coupled with a short life cycle, provides a means by which a gene or pathway function can be rapidly studied. Secondly, the vast majority of the fundamental biochemical mechanisms and pathways are conserved between fly and humans. Indeed, 75% of the genes that cause human disease are found in fly and, thus, the data collected in the fly can be used to provide insights into the same processes within humans. The emergence of a new technology, single cell RNA sequencing (scRNA-seq), has provided information as to which genes are switched on or most active from a single cell. Within the fly community this provides the ability to quickly map clusters of cells and cell types to the whole anatomy and link this to both phenotype and function. The increasing number of scRNA-seq datasets from different species has resulted in the development of the Single Cell Expression Atlas (scEA). This is a web portal which enables users to more easily visualise and interpret this data. It is anticipated that the level of fly single cell data will increase from 10 datasets to ~100 in 2020 and further two-fold increase in 2021. Key to the scientific exploitation of this data will be the ability of users to not only effectively analyse the fly data but also to examine the interconnections between fly data and human or mouse datasets. In this project we will provide the means by which fly datasets can be easily interpreted and also linked to mouse and human datasets via scEA. The scEA currently hosts scRNA-seq data for over 500K assays and this includes data for the Human Cell Atlas (HCA) and Mouse Cell Atlas (MCA), amongst others. This project will enable analysis pipelines to be developed to combine the available and emerging datasets, alongside the necessary computational infrastructure to host the Fly Cell Atlas (FCA) datasets. ScEA will provide users with an easy to navigate web service with exploratory querying capability, in addition to data download capabilities for further data analysis. The service will be fully integrated with the established fly resources, Flybase, Virtual Fly Brain and the Drosophila Resources at Harvard University. This project will also develop a process for annotation of the datasets. This annotation step adds additional scientific information to the data which provides the user with a greater level of biological understanding and so aids the interpretation and analysis. This annotation will expand on the existing FlyBase anatomy ontology which is a structure of controlled vocabularies used to describe the anatomy of the fly this will ensure that there is full compatibility across new and existing resources. The scEA will develop and provide the means by which the data can be easily visualised and mined for cell types, while also providing the fly community with the ability to contribute their scientific expertise to the annotation. The scEA user interface will be further developed to provide a greater level of cross species query ability as the resulting FCA will be linked within scEA to the HCA, MCA and any further datasets enabling cross species comparisons which will aid in the discovery of novel biological insights. This project aims to provide the fly community with practical solutions for connecting, re-using and reanalysing datasets and so will close the gap in translating biological discoveries in model organisms, such as the fruit fly, to humans and vice versa. This project will make the results of this comparative analysis rapidly available to the growing user community.