Strategies for analyzing highly enriched IP-chip datasets.
Strategies for analyzing highly enriched IP-chip datasets.
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DOI：
10.1186/1471-2105-10-305
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发表时间：
2009-09-22
影响因子：
3
通讯作者：
Tavaré S
中科院分区：
文献类型：
--
作者：
Knott SR;Viggiani CJ;Aparicio OM;Tavaré S
染色质免疫沉淀镶嵌阵列（ChIP芯片）已被用来检查功能，如蛋白质结合和组蛋白修饰的基因组范围内的各种类型的细胞。来自后一研究的阵列数据通常具有高比例的富集探针，其信号变化相当大（由于细胞群体中的异质性），这使得它们的标准化和下游分析变得困难。在这里，我们提出了分析这些实验的策略，我们的讨论集中在分析溴脱氧尿苷（BrdU）免疫沉淀平铺阵列（BrdU-IP-chip）数据集。BrdU-IP-芯片实验绘制了最近复制的大基因组区域，并具有与组蛋白修饰/定位数据相似的特征。为了准备这样的数据进行下游分析，我们采用了一种动态规划算法，确定了一组推定的未富集的探针，我们使用的阵列内和阵列之间的归一化。我们还介绍了第二个动态规划算法，采用先验知识来识别和量化这些数据集中的阳性信号。高度丰富的IP芯片数据集通常难以用传统的阵列归一化和分析策略进行分析。在这里，我们提出并测试了一套分析工具，其标准化和量化，允许准确识别和分析富集区域。
Chromatin immunoprecipitation on tiling arrays (ChIP-chip) has been employed to examine features such as protein binding and histone modifications on a genome-wide scale in a variety of cell types. Array data from the latter studies typically have a high proportion of enriched probes whose signals vary considerably (due to heterogeneity in the cell population), and this makes their normalization and downstream analysis difficult. Here we present strategies for analyzing such experiments, focusing our discussion on the analysis of Bromodeoxyruridine (BrdU) immunoprecipitation on tiling array (BrdU-IP-chip) datasets. BrdU-IP-chip experiments map large, recently replicated genomic regions and have similar characteristics to histone modification/location data. To prepare such data for downstream analysis we employ a dynamic programming algorithm that identifies a set of putative unenriched probes, which we use for both within-array and between-array normalization. We also introduce a second dynamic programming algorithm that incorporates a priori knowledge to identify and quantify positive signals in these datasets. Highly enriched IP-chip datasets are often difficult to analyze with traditional array normalization and analysis strategies. Here we present and test a set of analytical tools for their normalization and quantification that allows for accurate identification and analysis of enriched regions.
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影响因子：
56.9
作者：
Raghuraman, MK;Winzeler, EA;Fangman, WL
通讯作者：
Fangman, WL
DOI：
10.1073/pnas.0405088102
发表时间：
2005-05-03
影响因子：
11.1
作者：
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通讯作者：
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影响因子：
1.1
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作者：
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通讯作者：
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影响因子：
64.8
作者：
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通讯作者：
Diffley, JFX