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1.
Genome Res ; 23(3): 519-29, 2013 Mar.
Artículo en Inglés | MEDLINE | ID: mdl-23204306

RESUMEN

High-throughput RNA sequencing (RNA-seq) promises to revolutionize our understanding of genes and their role in human disease by characterizing the RNA content of tissues and cells. The realization of this promise, however, is conditional on the development of effective computational methods for the identification and quantification of transcripts from incomplete and noisy data. In this article, we introduce iReckon, a method for simultaneous determination of the isoforms and estimation of their abundances. Our probabilistic approach incorporates multiple biological and technical phenomena, including novel isoforms, intron retention, unspliced pre-mRNA, PCR amplification biases, and multimapped reads. iReckon utilizes regularized expectation-maximization to accurately estimate the abundances of known and novel isoforms. Our results on simulated and real data demonstrate a superior ability to discover novel isoforms with a significantly reduced number of false-positive predictions, and our abundance accuracy prediction outmatches that of other state-of-the-art tools. Furthermore, we have applied iReckon to two cancer transcriptome data sets, a triple-negative breast cancer patient sample and the MCF7 breast cancer cell line, and show that iReckon is able to reconstruct the complex splicing changes that were not previously identified. QT-PCR validations of the isoforms detected in the MCF7 cell line confirmed all of iReckon's predictions and also showed strong agreement (r(2) = 0.94) with the predicted abundances.


Asunto(s)
Algoritmos , Simulación por Computador , Secuenciación de Nucleótidos de Alto Rendimiento/métodos , Empalme del ARN , Análisis de Secuencia de ARN/métodos , Femenino , Humanos , Células MCF-7 , Precursores del ARN/genética , Precursores del ARN/metabolismo , ARN Mensajero/genética , ARN Mensajero/metabolismo , Transcriptoma , Proteína p53 Supresora de Tumor/genética , Proteína p53 Supresora de Tumor/metabolismo
2.
Nucleic Acids Res ; 40(Web Server issue): W615-21, 2012 Jul.
Artículo en Inglés | MEDLINE | ID: mdl-22638571

RESUMEN

High-throughput sequencing (HTS) technologies are providing an unprecedented capacity for data generation, and there is a corresponding need for efficient data exploration and analysis capabilities. Although most existing tools for HTS data analysis are developed for either automated (e.g. genotyping) or visualization (e.g. genome browsing) purposes, such tools are most powerful when combined. For example, integration of visualization and computation allows users to iteratively refine their analyses by updating computational parameters within the visual framework in real-time. Here we introduce the second version of the Savant Genome Browser, a standalone program for visual and computational analysis of HTS data. Savant substantially improves upon its predecessor and existing tools by introducing innovative visualization modes and navigation interfaces for several genomic datatypes, and synergizing visual and automated analyses in a way that is powerful yet easy even for non-expert users. We also present a number of plugins that were developed by the Savant Community, which demonstrate the power of integrating visual and automated analyses using Savant. The Savant Genome Browser is freely available (open source) at www.savantbrowser.com.


Asunto(s)
Genómica/métodos , Secuenciación de Nucleótidos de Alto Rendimiento , Programas Informáticos , Gráficos por Computador , Mutación INDEL , Internet , Polimorfismo de Nucleótido Simple , Población/genética
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