Dataset Information

Improving the Flexibility of RNA-Seq Data Analysis Pipelines.

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.

SUBMITTER: Phan JH

PROVIDER: S-EPMC4985025 | biostudies-literature | 2012 Dec

REPOSITORIES: biostudies-literature

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Improving the Flexibility of RNA-Seq Data Analysis Pipelines.

Phan John H JH Wu Po-Yen PY Wang May D MD

IEEE International Workshop on Genomic Signal Processing and Statistics : [proceedings]. IEEE International Workshop on Genomic Signal Processing and Statistics 20121201

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 limite ...[more]

PMID: 27536420

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Project description:BackgroundRNA-Seq is an increasing used methodology to study either coding and non-coding RNA expression. There are many software tools available for each phase of the RNA-Seq analysis and each of them uses different algorithms. Furthermore, the analysis consists of several steps regarding alignment (primary-analysis), quantification, differential analysis (secondary-analysis) and any tertiary-analysis and can therefore be time-consuming to deal with each step separately, in addition to requiring a computer knowledge. For this reason, the development of an automated pipeline that allows the entire analysis to be managed through a single initial command and that is easy to use even for those without computer skills can be useful. Faced with the vast availability of RNA-Seq analysis tools, it is first of all necessary to select a limited number of pipelines to include. For this purpose, we compared eight pipelines obtained by combining the most used tools and for each one we evaluated peak of RAM, time, sensitivity and specificity.ResultsThe pipeline with shorter times, lower consumption of RAM and higher sensitivity is the one consisting in HISAT2 for alignment, featureCounts for quantification and edgeR for differential analysis. Here, we developed ARPIR, an automated pipeline that recurs by default to the cited pipeline, but it also allows to choose, between different tools, those of the pipelines having the best performances.ConclusionsARPIR allows the analysis of RNA-Seq data from groups undergoing different treatment allowing multiple comparisons in a single launch and can be used either for paired-end or single-end analysis. All the required prerequisites can be installed via a configuration script and the analysis can be launched via a graphical interface or by a template script. In addition, ARPIR makes a final tertiary-analysis that includes a Gene Ontology and Pathway analysis. The results can be viewed in an interactive Shiny App and exported in a report (pdf, word or html formats). ARPIR is an efficient and easy-to-use tool for RNA-Seq analysis from quality control to Pathway analysis that allows you to choose between different pipelines.

Dataset Information

Improving the Flexibility of RNA-Seq Data Analysis Pipelines.

Publications

Improving the Flexibility of RNA-Seq Data Analysis Pipelines.

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