生物
不育
男性不育
计算生物学
可视化
基因
地图集(解剖学)
计算机科学
人工智能
遗传学
解剖
怀孕
作者
Eisa Mahyari,Katinka A. Vigh‐Conrad,Clément Daube,Ana C. Lima,Jingtao Guo,Douglas T. Carrell,James M. Hotaling,Kenneth I. Aston,Donald F. Conrad
摘要
Abstract Background Single‐cell RNA‐seq (scRNA‐Seq) has been widely adopted to study gene expression of the human testis. Several datasets of scRNA‐Seq from human testis have been generated from different groups processed with different informatics pipelines. An integrated atlas of scRNA‐Seq expression constructed from multiple donors, developmental ages, and fertility states would be widely useful for the testis research community. Objective To describe the generation and use of the human infertility single‐cell testis atlas (HISTA), an interactive web tool for understanding human spermatogenesis through scRNA‐Seq analysis. Methods We obtained scRNA‐Seq datasets derived from 12 donors, including healthy adult controls, juveniles, and several infertility cases, and reprocessed these data using methods to remove batch effects. Using Shiny, an open‐source environment for data visualization, we created numerous interactive tools for exploring the data, some of which support simple statistical hypothesis testing. We used the resulting HISTA browser and its underlying data to demonstrate HISTA's value for testis researchers. Results A primary application of HISTA is to search by a single gene or a set of genes; thus, we present various analyses that quantify and visualize gene expression across the testis cells and pathology. HISTA also contains machine‐learning‐derived gene modules (“components”) that capture the entire transcriptional landscape of the testis tissue. We show how the use of these components can simplify the highly complex data in HISTA and assist with the interpretation of genes with unknown functions. Finally, we demonstrate the diverse ways HISTA can be used for new data analysis, including hypothesis testing. Discussion and conclusions HISTA is a research environment that can help scientists organize and understand the high‐dimensional transcriptional landscape of the human testis. HISTA has already contributed to published testis research and can be updated as needed with input from the research community or downloaded and modified for individual needs.
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