Abstract
BackgroundOne of the challenges in the analysis of microarray data is to integrate and compare the selected (e.g., differential) gene lists from multiple experiments for common or unique underlying biological themes. A common way to approach this problem is to extract common genes from these gene lists and then subject these genes to enrichment analysis to reveal the underlying biology. However, the capacity of this approach is largely restricted by the limited number of common genes shared by datasets from multiple experiments, which could be caused by the complexity of the biological system itself.ResultsWe now introduce a new Pathway Pattern Extraction Pipeline (PPEP), which extends the existing WPS application by providing a new pathway-level comparative analysis scheme. To facilitate comparing and correlating results from different studies and sources, PPEP contains new interfaces that allow evaluation of the pathway-level enrichment patterns across multiple gene lists. As an exploratory tool, this analysis pipeline may help reveal the underlying biological themes at both the pathway and gene levels. The analysis scheme provided by PPEP begins with multiple gene lists, which may be derived from different studies in terms of the biological contexts, applied technologies, or methodologies. These lists are then subjected to pathway-level comparative analysis for extraction of pathway-level patterns. This analysis pipeline helps to explore the commonality or uniqueness of these lists at the level of pathways or biological processes from different but relevant biological systems using a combination of statistical enrichment measurements, pathway-level pattern extraction, and graphical display of the relationships of genes and their associated pathways as Gene-Term Association Networks (GTANs) within the WPS platform. As a proof of concept, we have used the new method to analyze many datasets from our collaborators as well as some public microarray datasets.ConclusionThis tool provides a new pathway-level analysis scheme for integrative and comparative analysis of data derived from different but relevant systems. The tool is freely available as a Pathway Pattern Extraction Pipeline implemented in our existing software package WPS, which can be obtained at
Highlights
One of the challenges in the analysis of microarray data is to integrate and compare the selected gene lists from multiple experiments for common or unique underlying biological themes
Pathway pattern extraction pipeline dissects pathwaylevel enrichment patterns for biological themes The first version of WholePathwayScope or WPS provides a platform for pattern extraction at the gene-level and allows generation of gene-term association networks (GTANs) [4]. In this newly developed high-throughput pathway pattern extraction pipeline (PPEP), we extended that capacity into a pathway-level pattern extraction method that retrieves the patterned pathways based on enrichment levels of pathways across gene lists or datasets
Only microarray data is utilized here as examples, any source of high throughput (HTP) data would be suitable for the analysis with Pathway Pattern Extraction Pipeline (PPEP)
Summary
The major features and functionalities of the newly developed pathway pattern extraction pipeline (PPEP) in WPS are illustrated using example data . Perturbation of apoptosis-related processes is http://www.biomedcentral.com/1471-2105/10/200 well known to play critical role in carcinogenesis These observations suggested that our pathway pattern extraction method provided by the PPEP was able to uncover many of the significant terms, which were missed by the conventional gene-level based enrichment approach. The pathway pattern extraction generated a list of 16 terms, which were visualized in a heatmap using the enrichment scores of each term for each sample (Figure 4, see Additional file 16 for the real data) Many of these 16 GO terms appeared to be quite specific to testis-related functions such as development of primary male sexual characteristics, fusion of sperm to egg plasma membrane, male gamete generation, male sex differentiation, spermatogenesis, which obviously are exactly what were expected from the analysis. We used our PPEP to seek common and unique biological themes in two-class comparison in another case study (See Additional file (Additional file and 19)), which showed great flexibility and capacity of the PPEP in such circumstances
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