Accurate Estimation of Expression Levels of Homologous Genes in RNA-seq Experiments

miRNA data analysis: next-gen sequencing

MicroRNAs (miRNAs) are short, noncoding RNAs that have the capacity to bind, capture, and silence hundreds of genes within and across diverse signaling pathways 1(Bartel, Cell 136:215-33, 2009) Specific sets of miRNAs characterize specific cell lineages of normal organisms and an increasing number of diseases have been shown to be associated with the dysregulation of specific miRNAs. Deep sequencing platforms have revealed unexpected complexity in relation to miRNAs, including 5' and 3'-end-length heterogeneity and RNA editing. These insights not uncovered by previous microarray-based studies underscore the importance of data analysis tools that enable users to rapidly and easily analyze the unprecedented amounts of small RNA sequencing data that is emerging from next-generation sequencing platforms, such as Illumina/Solexa, SOLiD, and 454. In this chapter, we summarize the increasing number of analysis platforms that are available for miRNA discovery and profiling and the identification of functional miRNA-mRNA pairs in the context of biology and disease. We also discuss in greater detail our contributions to this effort.

IsoLasso: a LASSO regression approach to RNA-Seq based transcriptome assembly

The new second generation sequencing technology revolutionizes many biology-related research fields and poses various computational biology challenges. One of them is transcriptome assembly based on RNA-Seq data, which aims at reconstructing all full-length mRNA transcripts simultaneously from millions of short reads. In this article, we consider three objectives in transcriptome assembly: the maximization of prediction accuracy, minimization of interpretation, and maximization of completeness. The first objective, the maximization of prediction accuracy, requires that the estimated expression levels based on assembled transcripts should be as close as possible to the observed ones for every expressed region of the genome. The minimization of interpretation follows the parsimony principle to seek as few transcripts in the prediction as possible. The third objective, the maximization of completeness, requires that the maximum number of mapped reads (or ?expressed segments? in gene models) be explained by (i.e., contained in) the predicted transcripts in the solution. Based on the above three objectives, we present IsoLasso, a new RNA-Seq based transcriptome assembly tool. IsoLasso is based on the well-known LASSO algorithm, a multivariate regression method designated to seek a balance between the maximization of prediction accuracy and the minimization of interpretation. By including some additional constraints in the quadratic program involved in LASSO, IsoLasso is able to make the set of assembled transcripts as complete as possible. Experiments on simulated and real RNA-Seq datasets show that IsoLasso achieves, simultaneously, higher sensitivity and precision than the state-of-art transcript assembly tools.

miRNAkey: a software for microRNA deep sequencing analysis

MOTIVATION

MicroRNAs (miRNAs) are short abundant non-coding RNAs critical for many cellular processes. Deep sequencing (next-generation sequencing) technologies are being readily used to receive a more accurate depiction of miRNA expression profiles in living cells. This type of analysis is a key step towards improving our understanding of the complexity and mode of miRNA regulation.

RESULTS

miRNAkey is a software package designed to be used as a base-station for the analysis of miRNA deep sequencing data. The package implements common steps taken in the analysis of such data, as well as adds unique features, such as data statistics and multiple read determination, generating a novel platform for the analysis of miRNA expression. A user-friendly graphical interface is applied to determine the analysis steps. The tabular and graphical output contains general and detailed reports on the sequence reads and provides an accurate picture of the differentially expressed miRNAs in paired samples.

AVAILABILITY AND IMPLEMENTATION

See http://ibis.tau.ac.il/miRNAkey

CONTACT

nshomron@post.tau.ac.il

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.