Abstract

RNA-seq data analysis pipelines are generally composed of sequence alignment, expression quantification, expression normalization, and differentially expressed gene (DEG) detection. Each step has numerous specific tools or algorithms, so we cannot explore all combinatorial pipelines and provide a comprehensive comparison of pipeline performance. To understand the mechanism of RNA-seq data analysis pipelines and provide some useful information for pipeline selection, we believe it is necessary to analyze the interactions among pipeline components. In this paper, by combining different alignment algorithms with the same quantification, normalization, and DEG detection tools, we construct nine RNA-seq pipelines to analyze the impact of RNA-seq alignment on downstream applications of gene expression estimates. Specifically, we find moderate linear correlation between the number of DEGs detected and the percentage of reads aligned with zero mismatch.


Original document

The different versions of the original document can be found in:

http://dx.doi.org/10.1109/globalsip.2014.7032351
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5010085,
http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7032351,
https://academic.microsoft.com/#/detail/2068222106
Back to Top

Document information

Published on 01/01/2014

Volume 2014, 2014
DOI: 10.1109/globalsip.2014.7032351
Licence: CC BY-NC-SA license

Document Score

0

Views 0
Recommendations 0

Share this document

Keywords

claim authorship

Are you one of the authors of this document?