Clustering Gene Expression Data Based on Predicted Differential Effects of GV Interaction
نویسندگان
چکیده
Microarray has become a popular biotechnology in biological and medical research. However, systematic and stochastic variabilities in microarray data are expected and unavoidable, resulting in the problem that the raw measurements have inherent "noise" within microarray experiments. Currently, logarithmic ratios are usually analyzed by various clustering methods directly, which may introduce bias interpretation in identifying groups of genes or samples. In this paper, a statistical method based on mixed model approaches was proposed for microarray data cluster analysis. The underlying rationale of this method is to partition the observed total gene expression level into various variations caused by different factors using an ANOVA model, and to predict the differential effects of GV (gene by variety) interaction using the adjusted unbiased prediction (AUP) method. The predicted GV interaction effects can then be used as the inputs of cluster analysis. We illustrated the application of our method with a gene expression dataset and elucidated the utility of our approach using an external validation.
منابع مشابه
Modification of the Fast Global K-means Using a Fuzzy Relation with Application in Microarray Data Analysis
Recognizing genes with distinctive expression levels can help in prevention, diagnosis and treatment of the diseases at the genomic level. In this paper, fast Global k-means (fast GKM) is developed for clustering the gene expression datasets. Fast GKM is a significant improvement of the k-means clustering method. It is an incremental clustering method which starts with one cluster. Iteratively ...
متن کاملDifferential genes expression analysis of invasive aspergillosis: a bioinformatics study based on mRNA/microRNA
Invasive aspergillosis is a severe opportunistic infection with high mortality in immunocompromised patients. Recently, the roles of microRNAs have been taken into consideration in the immune system and inflammatory responses. Using bioinformatics approaches, we aimed to study the microRNAs related to invasive aspergillosis to understand the molecular pathways involved in the disease pathogenes...
متن کاملخوشهبندی دادههای بیانژنی توسط عدم تشابه جنگل تصادفی
Background: The clustering of gene expression data plays an important role in the diagnosis and treatment of cancer. These kinds of data are typically involve in a large number of variables (genes), in comparison with number of samples (patients). Many clustering methods have been built based on the dissimilarity among observations that are calculated by a distance function. As increa...
متن کاملNetwork-based transcriptome analysis in salt tolerant and salt sensitive maize (Zea mays L.) genotypes
Identification of genes involved in salinity stress tolerance provides deeper insight into molecular mechanisms underlying salinity tolerance in maize. The present study was conducted in the faculty of agriculture of Urmia university, Iran, in 2018, with the aim of identifying genetic differences between two maize genotypes in tolerance to salinity stress, and the results of gene expression wer...
متن کاملDifferential Expression of Arabidopsis thaliana Acid Phosphatases in Response to Abiotic Stresses
The objective of this research is to identify Arabidopsis thaliana genes encoding acid phosphatases induced by phosphate starvation. Multiple alignments of eukaryotic acid phosphatase amino acid sequences led to the classification of these proteins into four groups including purple acid phosphatases (PAPs). Specific primers were degenerated and designed based on conserved sequences of PAPs isol...
متن کامل