Physical Sciences and Mathematics Commons^™

Estimation Of Alternative Splicing Isoform Frequencies From Rna-Seq Data, Marius Nicolae, Serghei Mangul, Ion I. Măndoiu, Alexander Zelikovskiy

Computer Science Faculty Publications

Background: Massively parallel whole transcriptome sequencing, commonly referred as RNA-Seq, is quickly becoming the technology of choice for gene expression profiling. However, due to the short read length delivered by current sequencing technologies, estimation of expression levels for alternative splicing gene isoforms remains challenging.

Results: In this paper we present a novel expectation-maximization algorithm for inference of isoform- and genespecific expression levels from RNA-Seq data. Our algorithm, referred to as IsoEM, is based on disambiguating information provided by the distribution of insert sizes generated during sequencing library preparation, and takes advantage of base quality scores, strand and read pairing information …

A Trend Pattern Assessment Approach To Microarray Gene Expression Profiling Data Analysis, Kahai Cao, Qiuming Zhu, Javeed Iqbal, John W.C. Chan

Computer Science Faculty Publications

We study the problem of how to assess the reliability of a statistical measurement on data set containing unknown quantity of noises, inconsistencies, and outliers. A practical approach that analyzes the dynamical patterns (trends) of the statistical measurements through a sequential extreme-boundary-points (EBP) weed-out process is explored. We categorize the weed-out trend patterns (WOTP) and examine their relation to the reliability of the measurement. The approach is applied to the processes of extracting genes that are predictive to BCL2 translocations and to clinical survival outcomes of diffuse large B-cell lymphoma (DLBCL) from DNA Microarray gene expression profiling data sets. Fisher’s …

Algorithmic Fusion Of Gene Expression Profiling For Diffuse Large B-Cell Lymphoma Outcome Prediction, Qiuming Zhu, Hongmei Cui, Kahai Cao, Wing C. Chan

Computer Science Faculty Publications

Many different methods and techniques have been investigated for the processing and analysis of microarray gene expression profiling datasets. It is noted that the accuracy and reliability of the results are often dependent on the measurement approaches applied, and no single measurement so far is guaranteed to generate a satisfactory result. In this paper, an algorithmic fusion approach is presented for extracting genes that are predictive to clinical outcomes (survival-fatal) of diffuse large B-cell lymphoma on a set of microarray data for gene expression profiling. The approach integrates a set of measurements from different aspects in terms of the discrepancy …