RNA 定序 (RNA-seq) 是一種有助於分析生物樣本中 RNA 分子數量的技術。它提供了對基因表達的深入瞭解。例如，它可以揭示不同條件下的細胞基因表達模式，並有助於探索條件轉錄本多樣性。RNA-seq 對於發現新基因、剖析複雜的基因網路以及找出潛在的致病機制至關重要。基因的調控有多方面的變因，因著選擇性剪接，一個基因可能轉錄成不同的isoform，從而增加蛋白質功能的多樣性，在生物不同發育階段也扮演著重要角色。這些異構物在不同的細胞類型和組織中表達，並在特定的生理和病理條件下發揮獨特的功能。此外，異構物變化的異常可能導致疾病，如癌症、神經退行性疾病和心血管疾病。不僅如此，啟動子的變化、失調也被證實與癌症有密且的關聯，對於不同環境的刺激，啟動子也會產生不同的使用情形。由於分析 RNA-seq 資訊重要性，大量的分析工具已被開發出來，因著多樣性的提高，過於複雜的工具組合、分析流程都使得研究人員進一步分析困難重重，並且這些工具通常需要高技術的生物資訊學人員才能操作，其結果的呈現方式可能也會讓使用者難以收集和詮釋。為了解決這個問題，我們開發了一個可自動化進行多種 RNA-seq 管線的工具，如果要探索多種管線，可簡化資料預處理步驟，以及降低學習工具的成本。此外，所開發的工具有系統地進行以下分析，以萃取不同實驗條件下的候選基因列表: (1)差異表達分析、(2)isoform變化、(3)啟動子變化，以及(4)篩選內部核糖體入口位點(IRES)，以進行 cap-indepent 轉譯分析。我們使用國立陽明交通大學生化暨分子生物研究所張崇德助理教授所提供的RNA-seq 之結果上展示了此工具的用法。我們也開發在虛擬機上簡單的單機版使用者友善網頁介面，只需點擊幾下滑鼠，不同面向的候選基因就能在數小時內被開發的工具篩選出來。總的來說，這項工作提出了一個友善的網頁使用者介面，方便整合使用現有的 RNA-seq 分析管道，並從設計的實驗中系統性地找出候選基因清單。

RNA sequencing (RNA-seq) is a technique used to analyze the number of RNA molecules in a biological sample. It provides insights into gene expression, revealing patterns of cellular gene expression under different conditions and exploring conditional transcript diversity. RNA-seq is essential for discovering new genes, dissecting complex gene networks, and identifying potential disease-causing mechanisms. Gene regulation is multifactorial, and selective splicing can result in a gene being transcribed into different isoforms, increasing the functional diversity of proteins and playing a critical role in various stages of biological development. The isoforms are expressed in various cell types and tissues, carrying out distinct functions under specific physiological and pathological conditions. Abnormalities in isoform changes can contribute to diseases like cancer, neurodegenerative diseases, and cardiovascular diseases. Furthermore, alterations and dysregulation of the promoter are closely associated with cancer. The promoter is utilized differently in response to various environmental stimuli. Due to the importance of analyzing RNA-seq information, a large number of analytical tools have been developed. However, the increased diversity and overly complex combinations of these tools have made it difficult for researchers to analyze them further. Additionally, these tools often require highly skilled bioinformaticians to operate, and the presentation of the results may be challenging for users to collect and interpret. To solve this problems, we have developed a tool that automates multiple RNA-seq pipelines, simplifies data preprocessing when exploring multiple pipelines, and reduces the learning costs for users. In addition, the developed tool systematically performs the following analyses to extract a list of candidate genes under different experimental conditions: (1) differential expression analysis, (2) isoform changes, (3) promoter changes, and (4) We demonstrated the use of this tool on the results of RNA-seq provided by Assistant Professor Chung-Te CHANG at the Institute of Biochemistry and Molecular Biology, National Yang Ming Chiao Tung University. We also developed a simple stand-alone user-friendly web interface on a virtual machine. With just a few mouse clicks, candidate genes of different orientations can be screened out by the developed tool within a few hours. Overall, this work presents a user-friendly web user interface that facilitates the integration of existing RNA-seq analysis pipelines and the systematic identification of candidate gene lists from designed experiments.

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