Sample Size Calculation for Differential Expression Analysis of RNA-Seq Data

Stephanie Page Hoskins (), Derek Shyr () and Yu Shyr ()
Additional contact information
Stephanie Page Hoskins: Vanderbilt University, Center for Quantitative Sciences
Derek Shyr: Harvard T.H. Chan School of Public Health, Department of Biostatistics
Yu Shyr: Vanderbilt University, Center for Quantitative Sciences

A chapter in Frontiers of Biostatistical Methods and Applications in Clinical Oncology, 2017, pp 359-379 from Springer

Abstract: Abstract The Holy Grail of precision medicine is the comprehensive integration of patient genotypic with phenotypic data to develop personalized disease prevention and treatment strategies. Next-generation sequencing technologies (NGS) and other types of high-throughput assays have exploded in popularity in recent years, thanks to their ability to produce an enormous volume of data quickly and at relatively low cost compared to more traditional laboratory methods. The ability to generate big data brings us one step closer to the realization of precision medicine; nevertheless, across the life cycle of such data, from experimental design to data capture, management, analysis, and utilization, many challenges remain. In this paper, we reviewed and discussed several statistical methods to estimate sample size based on the Poisson and Negative Binomial distributions for RNAseq experimental design.

Keywords: Cancer genomics; Next-generation sequencing; RNA-seq data; Sample size calculation (search for similar items in EconPapers)
Date: 2017
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-981-10-0126-0_22

Ordering information: This item can be ordered from
http://www.springer.com/9789811001260

DOI: 10.1007/978-981-10-0126-0_22

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().