fRNAkenseq a Powered-by-iPlant RNA Sequencing Analysis Platform


Meeting Abstract

39-7  Tuesday, Jan. 5 09:30  fRNAkenseq: a Powered-by-iPlant RNA Sequencing Analysis Platform HUBBARD, A.H.*; TREIBLE, W.R.; BOMHOFF, M.D.; DAVIS, R.V; LYONS, E; SCHMIDT, C.J.; University of Delaware; University of Delaware; University of Arizona; University of Delaware; University of Arizona; University of Delaware allenhub@udel.edu

We present fRNAkenseq: a novel, server based software platform for integrating various RNA sequencing analyses into a single powered-by-iPlant tool. fRNAkenseq is a complete analysis package, using iPlant compute resources to facilitate RNAseq analysis in a continuous workflow from FastQ file to enrichment analysis. fRNAkenseq implements a lightweight user interface and requires no prior computational experience. fRNAkenseq has access to the 20,000+ genome files (FASTA and Annotation) compiled by iPlant, from sources as diverse as NCBI, BGI, JGI and Ensembl, with the option for users to upload their own draft genome through another powered-by-iPlant tool, CoGE. fRNAkenseq is ideal for storage and access of boutique or draft genomes with an emphasis on downstream RNAseq analysis. This is made possible by iPlant’s data storage system. Using iPlant’s computational resources and existing powered-by-iPlant platforms, fRNAkenseq leverages the Tuxedo pipeline and several R Bioconductor packages into a scalable workflow that requires no prior computational experience. Thus, it is an ideal tool for biologists and biostatisticians working with large-scale data. Capitalizing on its integration with the Powered by iPlant Program and use of iPlant APIs, fRNAkenseq allows access to thousands of curated annotation and FASTA files of all species from the NCBI database, making them easily available for RNA seq analysis. To aid the transition from data to insight, fRNAkenseq employs the visualization abilities of cummeRbund and access to pathway resources. By combining multiple analyses in a scalable fashion, fRNAkenseq provides a functional tool that enables researchers to select the most promising genes for further investigation from mRNA sequencing as well as manage the challengingly large sequence files.

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