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Friday, February 16
PS2 Poster Session 2 and Refreshments Fri, Feb 16, 5:15 PM - 6:30 PM
Salons F-I

Empirical Comparisons of Differential Expression Analysis Pipelines for RNA-Sequencing Data (303649)

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Suzanne Fei, ONPRC BBU 
*Lina Gao, Biostatistics Shared Resource (OHSU BSR); Biostatistics and Bioinformatics Unit (ONPRC BBU) 
Jessica Minnier, Oregon Health & Science University 
Motomi Mori, OHSU BSR, OHSU-PSU school of public health 
Byung Park, OHSU BSR, ONPRC BBU, OHSU-PSU school of public health 

Keywords: RNA-seq, differential expression, OMICS, High Dimensional Data Analysis

Next-generation sequencing technologies, especially RNA-sequencing (RNA-seq), has been quickly recognized as a revolutionary tool for transcriptome studies. Many bioinformatics and biostatistics tools for analyzing RNA-seq have been developed for the multiple sequential steps. Even though RNA-seq has been used in a wide variety of applications, no clear consensus has been reached regarding the best practices, and the field is continued to evolve at a rapid pace (Conesa et. al, 2016). We empirically compared various established pipelines using the published data sets to learn the impact of procedures of quantitation on finding differentially expressed genes and downstream bioinformatics analyses. Although there is a limitation of using real data to compare different pipelines because no ground truth is known and it is impossible to know which method is more accurate than another [Fonseca, 2014], we hope that this empirical, systematic evaluation of different pipelines will guide us to establish institutional standard operating procedures for RNA-seq data analysis. We also report on the experiences of delivering and communicating statistical results to biomedical investigators.