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Phan JH, Wu PY, Wang MD. Improving the Flexibility of RNA-Seq Data Analysis Pipelines. IEEE Int Workshop Genomic Signal Process Stat. 2012;2012:70-73doi: 10.1109/GENSIPS.2012.6507729.
Phan, J. H., Wu, P. Y., & Wang, M. D. (2012). Improving the Flexibility of RNA-Seq Data Analysis Pipelines. IEEE International Workshop on Genomic Signal Processing and Statistics : [proceedings]. IEEE International Workshop on Genomic Signal Processing and Statistics, 201270-73. https://doi.org/10.1109/GENSIPS.2012.6507729
Phan, John H, et al. "Improving the Flexibility of RNA-Seq Data Analysis Pipelines." IEEE International Workshop on Genomic Signal Processing and Statistics : [proceedings]. IEEE International Workshop on Genomic Signal Processing and Statistics vol. 2012 (2012): 70-73. doi: https://doi.org/10.1109/GENSIPS.2012.6507729
Phan JH, Wu PY, Wang MD. Improving the Flexibility of RNA-Seq Data Analysis Pipelines. IEEE Int Workshop Genomic Signal Process Stat. 2012 Dec;2012:70-73. doi: 10.1109/GENSIPS.2012.6507729. PMID: 27536420; PMCID: PMC4985025.
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IEEE Int Workshop Genomic Signal Process Stat. 2012 Dec;2012:70-73. doi: 10.1109/GENSIPS.2012.6507729.

Improving the Flexibility of RNA-Seq Data Analysis Pipelines.

IEEE International Workshop on Genomic Signal Processing and Statistics : [proceedings]. IEEE International Workshop on Genomic Signal Processing and Statistics

John H Phan, Po-Yen Wu, May D Wang

Affiliations

  1. Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, USA, [email protected].
  2. Department of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, USA, [email protected].
  3. Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, USA, [email protected].

PMID: 27536420 PMCID: PMC4985025 DOI: 10.1109/GENSIPS.2012.6507729

Abstract

Accurate quantification of gene or isoform expression with RNA-Seq depends on complete knowledge of the transcriptome. Because a complete genomic annotation does not yet exist, novel isoform discovery is an important component of the RNA-Seq quantification process. Thus, a typical RNA-Seq pipeline includes a transcriptome mapping step to quantify known genes and isoforms, and a reference genome mapping step to discover new genes and isoforms. Several tools implement this approach, but are limited in that they force the use of a single mapping algorithm at both the transcriptome and reference genome mapping stages. The choice of mapping algorithm could affect quantification accuracy on a per-dataset basis. Thus, we describe a method that enables the merging of transcriptome and reference genome mapping stages provided that they conform to the standard SAM/BAM format. This procedure could potentially improve the accuracy of gene or isoform quantification by increasing flexibility when selecting RNA-Seq data analysis pipelines. We demonstrate an example of a flexible RNA-Seq pipeline by assessing its potential for novel isoform discovery and by validating its quantification performance using qRT-PCR.

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