A method for similarity search of genomic positional expression using CAGE

Efficient Approximation of Statistical Significance in Local Trend Analysis of Dependent Time Series

Biological time series data plays an important role in exploring the dynamic changes of biological systems, while the determinate patterns of association between various biological factors can further deepen the understanding of biological system functions and the interactions between them. At present, local trend analysis (LTA) has been commonly conducted in many biological fields, where the biological time series data can be the sequence at either the level of gene expression or OTU abundance, etc., A local trend score can be obtained by taking the similarity degree of the upward, constant or downward trend of time series data as an indicator of the correlation between different biological factors. However, a major limitation facing local trend analysis is that the permutation test conducted to calculate its statistical significance requires a time-consuming process. Therefore, the problem attracting much attention from bioinformatics scientists is to develop a method of evaluating the statistical significance of local trend scores quickly and effectively. In this paper, a new approach is proposed to evaluate the efficient approximation of statistical significance in the local trend analysis of dependent time series, and the effectiveness of the new method is demonstrated through simulation and real data set analysis.

Gepoclu: a software tool for identifying and analyzing gene positional clusters in large-scale gene expression analysis

Background

The notion that genes are non-randomly organized within the chromosomes of eukaryotic organisms has recently received strong experimental support. Clusters of co-expressed and co-localized genes have been recognized as playing key roles in a number of functional pathways and adaptive responses including organism development, differentiation, disease states and aging. The identification of genes arranged in close proximity with each other within a particular temporal and spatial transcriptional program is anticipated to unravel possible functional links and reciprocal interactions.

Results

We developed a novel software tool Gepoclu (Gene Positional Clustering) that automatically selects genes based on expression values from multiple sources, including microarray, EST and qRT-PCR, and performs positional clustering. Gepoclu provides expression-based gene selection from multiple experimental sources, position-based gene clustering and cluster visualization functionalities, all as parts of the same fully integrated, and interactive, package. This means rapid iterations while exploring for emergent behavior, and full programmability of the filtering and clustering steps.

Conclusions

Gepoclu is a useful data-mining tool for exploring relationships among transcriptional data deriving form different sources. It provides an easy interactive environment for analyzing positional clustering behavior of co-expressed genes, and at the same time it is fully programmable, so that it can be customized and extended to support specific analysis needs.

Integrative analysis of the human cis-antisense gene pairs, miRNAs and their transcription regulation patterns

Cis-antisense gene pairs (CASGPs) can transcribe mRNAs from an opposite strand of a given locus. To classify and understand diverse CASGP phenomena in the human we compiled a genome-wide catalog of CASGPs and integrated these sequences with microarray, SAGE and miRNA data. Using the concept of overlapping regions and clustering of SA transcripts by chromosome coordinates, we identified up to 9000 overlapping antisense loci. Four thousand three hundred and seventy-four of these CASGPs form 1759 complex gene architectures. We found that ∼35% (6347/18160) of RefSeq genes are overlapped with the antisense transcripts. About 30% of Affymetrix U133 microarray initial sequences map transcripts of ∼35% CASGPs and reveal mostly concordant expression in CASGPs. We found strong significant overrepresentation of human miRNA genes in loci of CASGPs. We developed a data-driven model of cross-talk between co-expressed CASGPs and DICER1-mediated miRNA pathway in normal spermatogenesis and in severe teratozoospermia. Specifically, we revealed complex SA structural–functional gene module composing the protein-coding genes, WDR6, DALRD3, NDUFAF3 and ncRNA precursors, mir-425 and mir-191, which could provide downregulation of ncRNA pathway via direct targeting DICER1 and basonuclin 2 transcripts by mir-425 and mir-191 in normal spermatogenesis, but this mechanism is switched off in severe teratozoospermia. The database is available from http://globalisland.bii.a-star.edu.sg/∼jiangtao/sas/index3.php?link =about