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High-throughput next generation sequencing (NGS) technologies have created an opportunity for detecting copy number variations (CNVs) more accurately. However, efficient and precise detection of CNVs remains challenging due to high levels of noise and biases, data heterogeneity and the “big data” nature of NGS data. In this work, we introduce a novel preprocessing pipeline to improve the detection...
Detecting copy number variants (CNVs) is an essential part in variant calling process. Here, we describe a novel method ERDS-pe to detect CNVs from whole-exome sequencing (WES) data. ERDS-pe first employs principal component analysis to normalize WES data. Then, ERDS-pe incorporates read depth signal and single-nucleotide variation information together as a hybrid signal into a paired hidden Markov...
Next-generation sequencing (NGS) has revolutionized the detection of structural variation in genome. Among NGS strategies, read depth is widely used and paramorphism information contained inside is generally ignored. We develop an algorithm that can fully exploit both read depth and paramorphism information. We embed mutation procedure in our system model for estimating prior likelihood of single...
Biological network inference is a crucial problem to solve in Bioinformatics as most of biological process are based on bio molecular interactions. Many researchers have worked on especially the inference of gene regulatory networks where a node and edge represent a gene and regulation relationship respectively assuming that a gene can regulate another gene indirectly. However, a gene expression level...
Exome sequencing provides us an effective way to discover genetic factors that might be associated with phenotypes for complex diseases. Compared with the whole-genome sequencing, exome sequencing can satisfy the high sequencing coverage requirement while under the limited budge constraint. However, due to the nature that exons are distributed sparsely along the genome, and the technical variability...
The scale of comparative genomics data frequently overwhelms current data visualization methods on conventional (desktop) displays. This paper describes two types of solution that take advantage of wall-sized high-resolution displays (WHirDs), which have orders of magnitude more display real estate (i.e., pixels) than desktop displays. The first allows users to view detailed graphics of copy number...
Pathway maps are an important source of information when analyzing functional implications of experimental data on biological processes. However, associating large quantities of data with nodes on a pathway map and allowing in depth-analysis at the same time is a challenging task. While a wide variety of approaches for doing so exist, they either do not scale beyond a few experiments or fail to represent...
Copy number variations (CNVs) are the gains or losses on the genomic DNA from several kilo-bases to hundreds of kilo-bases, which has been proven that more than 12% of genomes could be affected by such variants. Newly developed microarray technologies which were allowed to investigate copy number variants in a genome run slowly and are limited to detect small-sized CNV flexibly. Here we propose a...
Whole genome sequencing enables a high resolution view of the human genome and enables unique insights into copy number variations on an unprecedented scale. Numerous tools and studies have already been introduced that provide confirmatory evidence and new genomic structure variation data in individuals as well as across populations. We utilize two such tools, CNV-seq and FREEC to compare their outputs...
We have developed a novel quantum dot (QD) enabled copy number variation (CNV) quantification assay. Current CNV detection techniques are not able to reliably quantify less than a twofold difference. The assay employed a QD to physically transform the target copy number into different electrophoretic mobility (EM) levels that could be assessed by the electrophoresis. We built a model to predict the...
Copy number variation (CNV) detection using SNP array data is challenging due to the low signal-to-noise ratio. In this study, we propose a principal component analysis (PCA) based correction to eliminate variance in CNV data induced by potential confounding factors. Simulations show a substantial improvement in CNV detection accuracy after correction. We also observe a significant improvement in...
Glioblastoma is the most aggressive form of brain cancer. Transcriptional aberrations may play an important role in etiology of glioblastoma, which might be caused through genomic alterations: nucleotide mutation, copy number variation, DNA mythelation. Here, we explored another possible mechanism involving cooperative deregulation of microRNAs (miRNAs) and transcription factors (TFs). Several miRNA-TF...
Detection of genomic DNA copy number variations (CNVs) can provide a complete and more comprehensive view of human disease. In this paper, we incorporate DNA copy number variation data derived from SNP arrays into a computational shrunken model and formalize the detection of copy number variations as a case-control classification problem. By shrinkage, the number of relevant CNVs to disease can be...
As an extension to hidden Markov models, the hidden semi-Markov models allow the probability distribution of staying in the same state to be a general distribution. Therefore, hidden semi-Markov models are good at modeling sequences with succession of homogenous zones by choosing appropriate state duration distributions. Hidden semi-Markov models are generative models. Most times they are trained...
This study developed a method to identify disease-correlated pathways by integrating copy numbers (CN) and gene expression (GE). To evaluate the correlation between CN and GE, a suitable window size was assessed by simulation. Gene Set Enrichment Analysis (GSEA) was utilized to identify the possible pathways by CN, GE, and their correlations, respectively. Each of those enriched pathways was further...
Epistasis usually contributes to many well known diseases making the traits more complex and harder to study. The interactions between multiple genes and their alleles of different loci often mask the effects of a single gene at particular locus resulting in a complex trait. So the analysis of epistasis uncovers the facts about the mechanisms and pathways involved in a disease by analyzing biological...
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