A Seriation Approach for Visualization-Driven Discovery of Co-Expression Patterns in Serial Analysis of Gene Expression (SAGE) Data

摘要: Background: Serial Analysis of Gene Expression (SAGE) is a DNA sequencing-based method for large-scale gene expression profiling that provides an alternative to microarray analysis. Most analyses SAGE data aimed at identifying co-expressed genes have been accomplished using various versions clustering approaches often result in number false positives. Principal Findings: Here we explore the use seriation, statistical approach ordering sets objects based on their similarity, pattern discovery data. For this specific task implement seriation heuristic term ‘progressive construction contigs’ constructs local chains related elements by sequentially rearranging margins correlation matrix. We apply analysis simulated and experimental compare our results those obtained with algorithm developed specifically show simulations performance compares favorably noisy Conclusions: visualization-based Using both data, demonstrate able identify groups more accurately than Our suggest useful whose applicability should be further pursued.