Differential expression analysis for RNA-Seq: An overview of statistical methods and computational software Journal Article
| Authors: | Huang, H. C.; Niu, Y.; Qin, L. X. |
| Article Title: | Differential expression analysis for RNA-Seq: An overview of statistical methods and computational software |
| Abstract: | Deep sequencing has recently emerged as a powerful alternative to microarrays for the high-throughput profiling of gene expression. In order to account for the discrete nature of RNA sequencing data, new statistical methods and computational tools have been developed for the analysis of differential expression to identify genes that are relevant to a disease such as cancer. In this paper, it is thus timely to provide an overview of these analysis methods and tools. For readers with statistical background, we also review the parameter estimation algorithms and hypothesis testing strategies used in these methods. © the authors, publisher and licensee Libertas Academica Limited. |
| Keywords: | neoplasm; bayes theorem; gene expression profiling; genetic variability; statistical analysis; guanine; probability; gene identification; malignant neoplastic disease; regression analysis; bioinformatics; computer program; software; comparative genomic hybridization; rna sequence; genetic algorithm; mathematical analysis; cytosine; overview; statistical methods; null hypothesis; article; rna sequencing; differential expression analysis |
| Journal Title: | Cancer Informatics |
| Volume: | 14 |
| Issue: | Suppl. 1 |
| ISSN: | 1176-9351 |
| Publisher: | Libertas Academica Ltd |
| Date Published: | 2015-12-13 |
| Start Page: | 57 |
| End Page: | 67 |
| Language: | English |
| DOI: | 10.4137/CIN.S21631 |
| PROVIDER: | scopus |
| PMCID: | PMC4678998 |
| PUBMED: | 26688660 |
| DOI/URL: | |
| Notes: | Article -- Export Date: 7 January 2016 -- 57 -- Source: Scopus |
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