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TAAPP:原核生物平铺阵列分析管道。

TAAPP: Tiling Array Analysis Pipeline for Prokaryotes.

机构信息

College of Veterinary Medicine, Mississippi State University, MS 39762, USA.

出版信息

Genomics Proteomics Bioinformatics. 2011 Apr;9(1-2):56-62. doi: 10.1016/S1672-0229(11)60008-9.

Abstract

High-density tiling arrays provide closer view of transcription than regular microarrays and can also be used for annotating functional elements in genomes. The identified transcripts usually have a complex overlapping architecture when compared to the existing genome annotation. Therefore, there is a need for customized tiling array data analysis tools. Since most of the initial tiling arrays were conducted in eukaryotes, data analysis methods are well suited for eukaryotic genomes. For using whole-genome tiling arrays to identify previously unknown transcriptional elements like small RNA and antisense RNA in prokaryotes, existing data analysis tools need to be tailored for prokaryotic genome architecture. Furthermore, automation of such custom data analysis workflow is necessary for biologists to apply this powerful platform for knowledge discovery. Here we describe TAAPP, a web-based package that consists of two modules for prokaryotic tiling array data analysis. The transcript generation module works on normalized data to generate transcriptionally active regions (TARs). The feature extraction and annotation module then maps TARs to existing genome annotation. This module further categorizes the transcription profile into potential novel non-coding RNA, antisense RNA, gene expression and operon structures. The implemented workflow is microarray platform independent and is presented as a web-based service. The web interface is freely available for academic use at http://lims.lsbi.mafes.msstate.edu/TAAPP-HTML/.

摘要

高密度平铺阵列比常规微阵列提供更接近转录的观察,并且还可以用于注释基因组中的功能元件。与现有基因组注释相比,鉴定的转录本通常具有复杂的重叠结构。因此,需要定制的平铺阵列数据分析工具。由于最初的大多数平铺阵列都是在真核生物中进行的,因此数据分析方法非常适合真核生物基因组。为了使用全基因组平铺阵列来鉴定原核生物中以前未知的转录元件,如小 RNA 和反义 RNA,需要针对原核生物基因组结构对现有的数据分析工具进行定制。此外,这种定制数据分析工作流程的自动化对于生物学家将这个强大的平台应用于知识发现是必要的。在这里,我们描述了 TAAPP,这是一个基于网络的软件包,由两个模块组成,用于原核平铺阵列数据分析。转录本生成模块在归一化数据上运行以生成转录活性区域 (TARs)。然后,特征提取和注释模块将 TARs 映射到现有基因组注释。该模块进一步将转录谱分类为潜在的新型非编码 RNA、反义 RNA、基因表达和操纵子结构。实现的工作流程与微阵列平台无关,并以基于网络的服务呈现。该网络界面可免费用于学术用途,网址为 http://lims.lsbi.mafes.msstate.edu/TAAPP-HTML/。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fbc3/5054164/596b319e3af8/gr1.jpg

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