Arkas: Rapid reproducible RNAseq analysis [version 1; peer review: 1 approved, 1 approved with reservations]

• Published in: F1000 research 2017, Vol.6, p.586
• Main Authors: Colombo, Anthony R, J. Triche Jr, Timothy, Ramsingh, Giridharan
• Format: Article
• Language: English
• Subjects: Bioinformatics; Gene set enrichment analysis; Genomics
• ISSN: 2046-1402; 2046-1402
• DOI: 10.12688/f1000research.11355.1

The recently introduced Kallisto pseudoaligner has radically simplified the quantification of transcripts in RNA-sequencing experiments.  We offer cloud-scale RNAseq pipelines Arkas-Quantification, which deploys Kallisto for parallel cloud computations, and Arkas-Analysis, which annotates the Kallisto results by extracting structured information directly from source FASTA files with per-contig metadata and calculates the differential expression and gene-set enrichment analysis on both coding genes and transcripts. The biologically informative downstream gene-set analysis maintains special focus on Reactome annotations while supporting ENSEMBL transcriptomes. The Arkas cloud quantification pipeline includes support for custom user-uploaded FASTA files, selection for bias correction and pseudoBAM output. The option to retain pseudoBAM output for structural variant detection and annotation provides a middle ground between de novo transcriptome assembly and routine quantification, while consuming a fraction of the resources used by popular fusion detection pipelines.  Illumina's BaseSpace cloud computing environment, where these two applications are hosted, offers a massively parallel distributive quantification step for users where investigators are better served by cloud-based computing platforms due to inherent efficiencies of scale.