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Updated: Jul 11, 2025

A Protocol for Using Gene Set Enrichment Analysis to Identify the Appropriate Animal Model for Translational Research

A Protocol for Using Gene Set Enrichment Analysis to Identify the Appropriate Animal Model for Translational Research

Published on: August 16, 2017

使用ExpressAnalyst进行模型和非模型生物的综合基因表达分析.

Jessica Ewald¹, Guangyan Zhou¹, Yao Lu²

¹Institute of Parasitology, McGill University, Montreal, Canada.

Current protocols

|November 6, 2023

概括

ExpressAnalyst提供了一个基于网络的平台,用于全面的转录组学和蛋白质组学分析,从原始读取到功能洞察. 它支持各种数据类型和生物体,通过交互式可视化方便数据探索和理解.

关键词:

不同的表达分析分析差异表达分析.进行元分析.蛋白质组学蛋白质组学转录组学转录组学是指转录组学.视觉分析视觉分析

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Analyzing Multifactorial RNA-Seq Experiments with DiCoExpress

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Comprehensive Workflow for the Genome-wide Identification and Expression Meta-analysis of the ATL E3 Ubiquitin Ligase Gene Family in Grapevine

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Published on: December 22, 2017

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A Protocol for Using Gene Set Enrichment Analysis to Identify the Appropriate Animal Model for Translational Research

A Protocol for Using Gene Set Enrichment Analysis to Identify the Appropriate Animal Model for Translational Research

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Published on: July 29, 2022

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Published on: December 22, 2017

科学领域:

生物信息学是一种生物信息学.
计算生物学计算生物学
基因组学就是基因组学.
蛋白质组学是指蛋白质组学.

背景情况:

转录组学和蛋白质组学数据分析需要集成的平台来进行高效的处理和解释.
现有的工具往往缺乏对各种数据类型,生物和复杂的分析工作流的全面支持.
直观的可视化和功能丰富对于理解生物数据至关重要.

研究的目的:

介绍ExpressAnalyst,这是一个基于网络的平台,用于端到端的转录组学和蛋白质组学数据分析.
为数据处理,微分表达式分析,元分析和功能解释提供统一的环境.
支持对模型和非模型生物体的分析,包括从RNA-seq读取中直接转录组分析.

主要方法:

基于Web的平台,使用FASTQ文件,丰度表或基因/蛋白质列表作为输入.
包括读量化,数据处理,规范化,微分表达式分析和元分析.
采用交互式可视化 (火山图,热图,网络,山脊图) 和功能丰富分析.

主要成果:

ExpressAnalyst能够从原始测序阅读到生物见解进行直观的分析.
支持29种常见的生物体,并为非模型生物体提供转录组概况.
提供11个基本协议,涵盖基本分析任务,包括RNA-seq和蛋白质组学数据.

结论:

ExpressAnalyst为复杂的转录组学和蛋白质组学数据分析提供了一种多功能和用户友好的解决方案.
该平台通过集成的可视化和丰富工具促进了灵活的数据探索和理解.
它使研究人员能够有效地分析各种生物和实验设计中的数据.