Sharif Digital Repository

Association mapping of genetic diseases has attracted extensive research interest during the recent years. However, most of the methodologies introduced so far suffer from spurious inference of the associated sites due to population inhomogeneities. In this paper, we introduce a statistical framework to compensate for this shortcoming by equipping the current methodologies with a state-of-the-art clustering algorithm being widely used in population genetics applications. The proposed framework jointly infers the disease-associated factors and the hidden population structures. In this regard, a Markov Chain-Monte Carlo (MCMC) procedure has been employed to assess the posterior probability... 

In the problems of Genome-Wide Association Study (GWAS), the objective is to associate subsequences of individual's genomes to the observable characteristics called phenotypes. The genome containing the biological information of an individual can be represented by a sequence of length G. Many observable characteristics of the individuals can be related to a subsequence of a given length L, called causal subsequence. The environmental affects make the relation between the causal subsequence and the observable characteristics a stochastic function. Our objective in this paper is to detect the causal subsequence of a specific phenotype using a dataset of N individuals and their observed... 

Genome-Wide Association Study (GWAS) addresses the problem of associating subsequences of individuals' genomes to the observable characteristics called phenotypes. In a genome of length G, it is observed that each characteristic is only related to a specific subsequence of it with length L, called the causal subsequence. The objective is to recover the causal subsequence, using a dataset of N individuals' genomes and their observed characteristics. Recently, the problem has been investigated from an information theoretic point of view in [1]. It has been shown that there is a threshold effect for reliable learning of the causal subsequence at Gh ( N L/G ) by characterizing the capacity of... 

The objective of a genome-wide association study (GWAS) is to associate subsequences of individuals' genomes to the observable characteristics called phenotypes (e.g., high blood pressure). Motivated by the GWAS problem, in this paper we introduce the information-theoretic problem of associated subsequence retrieval, where a dataset of N (possibly high-dimensional) sequences of length G, and their corresponding observable (binary) characteristics is given. The sequences are chosen independently and uniformly at random from XG , where X is a finite alphabet. The observable (binary) characteristic is only related to a specific unknown subsequence of length L of the sequences, called associated... 

Association mapping of genetic diseases has attracted extensive research interest during the recent years. However, most of the methodologies introduced so far suffer from spurious inference of the associated sites due to population inhomogeneities. In this paper, we introduce a statistical framework to compensate for this shortcoming by equipping the current methodologies with a state-of-the-art clustering algorithm being widely used in population genetics applications. The proposed framework jointly infers the disease-associated factors and the hidden population structures. In this regard, a Markov Chain-Monte Carlo (MCMC) procedure has been employed to assess the posterior probability... 

Hi-C is a genome-wide chromosome conformation capture technology that detects interactions between pairs of genomic regions and exploits higher order chromatin structures. Conceptually Hi-C data counts interaction frequencies between every position in the genome and every other position. Biologically functional interactions are expected to occur more frequently than transient background and artefactual interactions. To identify biologically relevant interactions, several background models that take biases such as distance, GC content and mappability into account have been proposed. Here we introduce MaxHiC, a background correction tool that deals with these complex biases and robustly... 

Purpose: Endometriosis is a gynecological disease that causes the uterine lining to appear in other organs outside the uterus. As DNA methylation has an important role in this disorder, its profiling can reveal new information to improve the diagnosis and treatment of endometriosis patients. Methods: We conducted a genome-wide methylation profiling of ectopic and eutopic endometrial tissues from women with and without endometriosis using Infinium Human Methylation 450K BeadChip arrays. DNA methylation samples were collected from nine ectopic and nine eutopic endometrial tissues of endometriosis and six endometrial tissues of healthy controls. Results: Correlation heatmaps and the principal... 

Local three-stranded DNA/RNA hybrid regions of genomes (R-loops) have been detected either by binding of a monoclonal antibody (DRIP assay) or by enzymatic recognition by RNaseH. Such a structure has been postulated for mouse and human telomeres, clearly suggested by the identification of the complementary RNA Telomeric repeat-containing RNA “TERRA”. However, the tremendous disparity in the information obtained with antibody-based technology drove us to investigate a new strategy. Based on the observation that DNA/RNA hybrids in a triplex complex genome co-purify with the double-stranded chromosomal DNA fraction, we developed a direct preparative approach from total protein-free cellular...