mRNA-Seq计数数据过分散的统计方法

Q3 Computer Science

Open Bioinformatics Journal Pub Date : 2013-12-13 DOI:10.2174/1875036201307010034

Hui Zhang, S. Pounds, Li Tang

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引用次数: 10

摘要

新一代测序(NGS)技术的最新发展为全转录组的超高通量测序mRNA (mRNA-seq)打开了大门。mRNA-seq使研究人员能够全面搜索疾病的潜在生物学决定因素，并最终发现新的预防和治疗解决方案。不幸的是，鉴于mRNA-seq数据的复杂性，数据生成已经超出了当前的分析能力，阻碍了这一领域的研究步伐。因此，迫切需要开发新的统计方法来解决与mRNA-seq数据相关的问题。这篇综述解决了mRNA计数数据中存在过分散的共同挑战。综述了目前过度色散建模的方法，如负二项法、准似然泊松法和两阶段自适应法;介绍相关统计理论;并讨论它们在mRNA-seq计数数据中的应用。

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Statistical Methods for Overdispersion in mRNA-Seq Count Data

Recent developments in Next-Generation Sequencing (NGS) technologies have opened doors for ultra high throughput sequencing mRNA (mRNA-seq) of the whole transcriptome. mRNA-seq has enabled researchers to comprehensively search for underlying biological determinants of diseases and ultimately discover novel preventive and therapeutic solutions. Unfortunately, given the complexity of mRNA-seq data, data generation has outgrown current analytical capacity, hindering the pace of research in this area. Thus, there is an urgent need to develop novel statistical methodology that addresses problems related to mRNA-seq data. This review addresses the common challenge of the presence of overdispersion in mRNA count data. We review current methods for modeling overdispersion, such as negative binomial, quasi-likelihood Poisson method, and the two-stage adaptive method; introduce related statistical theories; and discuss their applications to mRNA-seq count data.

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来源期刊

Open Bioinformatics Journal Computer Science-Computer Science (miscellaneous)

CiteScore

2.40

自引率

0.00%

发文量

期刊介绍： The Open Bioinformatics Journal is an Open Access online journal, which publishes research articles, reviews/mini-reviews, letters, clinical trial studies and guest edited single topic issues in all areas of bioinformatics and computational biology. The coverage includes biomedicine, focusing on large data acquisition, analysis and curation, computational and statistical methods for the modeling and analysis of biological data, and descriptions of new algorithms and databases. The Open Bioinformatics Journal, a peer reviewed journal, is an important and reliable source of current information on the developments in the field. The emphasis will be on publishing quality articles rapidly and freely available worldwide.