Significance analysis of lexical bias in microarray data.
Significance analysis of lexical bias in microarray data.
复制标题
微阵列数据中词汇偏差的显着性分析。
DOI：
10.1186/1471-2105-4-12
复制
发表时间：
2003-04-03
影响因子：
3
通讯作者：
Falkow S
中科院分区：
文献类型：
--
作者：
Kim CC;Falkow S
在微阵列分析中被确定为显著差异调节的基因通常具有功能共性，例如是相同生化途径的组成部分。这导致某些词在基因列表中被低估或高估。区分生物学上有意义的趋势和注释和分析过程的工件是至关重要的，因为只有真正的生物学趋势才对进一步的实验感兴趣。目前有许多复杂的方法可以识别重要的词汇趋势，但是这些方法对于大多数微阵列用户的实际使用来说通常过于繁琐。我们开发了一个工具，LACK，用于计算微阵列数据集中明显词法偏差的统计显著性。通过与随机生成的数据集进行比较，评估用户指定的搜索词列表在差异调节基因列表中的频率是否具有统计学意义。输入文件和用户界面的简单性目标是普通微阵列用户，他们希望在不需要生物信息学技能的情况下对分析数据集中的明显词汇趋势进行统计测量。该软件以Perl源代码或Windows可执行文件的形式提供。我们在实验室中使用LACK根据我们的微阵列数据生成生物学假设。我们用一个例子来证明该程序的实用性，在这个例子中，我们证实了阳离子螯合剂双吡啶对肠沙门氏菌血清型鼠伤寒沙门氏菌的SPI-2致病性岛的显著上调。
Genes that are determined to be significantly differentially regulated in microarray analyses often appear to have functional commonalities, such as being components of the same biochemical pathway. This results in certain words being under- or overrepresented in the list of genes. Distinguishing between biologically meaningful trends and artifacts of annotation and analysis procedures is of the utmost importance, as only true biological trends are of interest for further experimentation. A number of sophisticated methods for identification of significant lexical trends are currently available, but these methods are generally too cumbersome for practical use by most microarray users. We have developed a tool, LACK, for calculating the statistical significance of apparent lexical bias in microarray datasets. The frequency of a user-specified list of search terms in a list of genes which are differentially regulated is assessed for statistical significance by comparison to randomly generated datasets. The simplicity of the input files and user interface targets the average microarray user who wishes to have a statistical measure of apparent lexical trends in analyzed datasets without the need for bioinformatics skills. The software is available as Perl source or a Windows executable. We have used LACK in our laboratory to generate biological hypotheses based on our microarray data. We demonstrate the program's utility using an example in which we confirm significant upregulation of SPI-2 pathogenicity island of Salmonella enterica serovar Typhimurium by the cation chelator dipyridyl.
登录
查看更多内容
DOI：
10.1073/pnas.091062498
发表时间：
2001-04-24
影响因子：
11.1
作者：
Tusher, VG;Tibshirani, R;Chu, G
通讯作者：
Chu, G
DOI：
10.1073/pnas.97.26.14674
发表时间：
2000-12-19
影响因子：
11.1
作者：
Zimmer, DP;Soupene, E;Kustu, S
通讯作者：
Kustu, S
影响因子：
30.8
作者：
Jenssen, TK;Lægreid, A;Hovig, E
通讯作者：
Hovig, E
影响因子：
2.9
作者：
Blaschke, Christian;Oliveros, Juan C.;Valencia, Alfonso
通讯作者：
Valencia, Alfonso
影响因子：
3.2
作者：
Chan, K;Baker, S;Falkow, S
通讯作者：
Falkow, S