GOurmet: a tool for quantitative comparison and visualization of gene expression profiles based on gene ontology (GO) distributions.
GOurmet: a tool for quantitative comparison and visualization of gene expression profiles based on gene ontology (GO) distributions.
复制标题
美食：基于基因本体论（GO）分布的基因表达谱的定量比较和可视化的工具。
DOI：
10.1186/1471-2105-7-151
复制
发表时间：
2006-03-17
影响因子：
3
通讯作者：
Mills, JC
中科院分区：
文献类型：
--
作者：
Doherty, JM;Carmichael, LK;Mills, JC
在各种实验条件下，来自特定细胞和组织的不断扩大的基因表达谱（EPs）群体是研究人员有效利用的重要但困难的资源。最近已经开发出软件工具，使用与EP中基因相关的基因本体（GO）术语的分布来识别相对于其他EP，该EP中过度或不足代表的特定生物功能或过程。此外，还可以使用每个EP固有的GO术语分布，将该EP作为一个整体与其他EP联系起来。由于GO术语注释以可变粒度的树状级联组织，因此该方法允许用户关联（例如，通过分层聚类）不同长度和来自不同平台（例如，GeneChip， SAGE， EST库）的ep。在这里，我们介绍了GOurmet，这是一个软件包，它可以计算单个表达谱（EP）中基因所代表的GO术语的分布，基于这些集成的GO术语分布对多个EP进行聚类，并为用户提供几种可视化和比较EP的工具。GOurmet在荟萃分析中特别有用，用于检查通过不同实验程序获得的特定细胞类型（例如，组织特异性干细胞）的EPs。GOurmet还引入了一个新工具，Targetoid plot，它允许用户在任何聚类分析中动态呈现单个元素之间的多维关系。Targetoid绘图工具允许用户选择任何元素作为绘图的中心，然后程序将集群中的所有其他元素表示为与所选中心元素相似的函数。GOurmet是一个用户友好的、基于gui的软件包，它极大地促进了对多个EPs生成的结果的分析。聚类分析的特点是一个动态的目标图，它可以推广到任何聚类应用程序中。
The ever-expanding population of gene expression profiles (EPs) from specified cells and tissues under a variety of experimental conditions is an important but difficult resource for investigators to utilize effectively. Software tools have been recently developed to use the distribution of gene ontology (GO) terms associated with the genes in an EP to identify specific biological functions or processes that are over- or under-represented in that EP relative to other EPs. Additionally, it is possible to use the distribution of GO terms inherent to each EP to relate that EP as a whole to other EPs. Because GO term annotation is organized in a tree-like cascade of variable granularity, this approach allows the user to relate (e.g., by hierarchical clustering) EPs of varying length and from different platforms (e.g., GeneChip, SAGE, EST library). Here we present GOurmet, a software package that calculates the distribution of GO terms represented by the genes in an individual expression profile (EP), clusters multiple EPs based on these integrated GO term distributions, and provides users several tools to visualize and compare EPs. GOurmet is particularly useful in meta-analysis to examine EPs of specified cell types (e.g., tissue-specific stem cells) that are obtained through different experimental procedures. GOurmet also introduces a new tool, the Targetoid plot, which allows users to dynamically render the multi-dimensional relationships among individual elements in any clustering analysis. The Targetoid plotting tool allows users to select any element as the center of the plot, and the program will then represent all other elements in the cluster as a function of similarity to the selected central element. GOurmet is a user-friendly, GUI-based software package that greatly facilitates analysis of results generated by multiple EPs. The clustering analysis features a dynamic targetoid plot that is generalizable for use with any clustering application.
登录
查看更多内容
影响因子：
12.3
作者：
Glenisson P;Coessens B;Van Vooren S;Mathys J;Moreau Y;De Moor B
通讯作者：
De Moor B
影响因子：
4.8
作者：
Mills, JC;Andersson, N;Gordon, JI
通讯作者：
Gordon, JI
影响因子：
3
作者：
Stevens, JR;Doerge, RW
通讯作者：
Doerge, RW
影响因子：
56.9
作者：
Ramalho-Santos, M;Yoon, S;Melton, DA
通讯作者：
Melton, DA
DOI：
10.1073/pnas.192574799
发表时间：
2002-11-12
影响因子：
11.1
作者：
Mills, JC;Andersson, N;Gordon, JI
通讯作者：
Gordon, JI