Arkas: Rapid reproducible RNAseq analysis

Abstract

The recently introduced Kallisto pseudoaligner has radically simplified the quantification of transcripts in RNA-sequencing experiments. We offer cloud-scale RNAseq pipelines , and Arkas-QuantificationArkas-Analysis available within Illumina's BaseSpace cloud application platform which expedites Kallisto preparatory routines, reliably calculates differential expression, and performs gene-set enrichment of REACTOME pathways Due . to inherit inefficiencies of scale, Illumina's BaseSpace computing platform offers a massively parallel distributive environment improving data management services and data importing. deploys Arkas-Quantification Kallisto for parallel cloud computations and is conveniently integrated downstream from the BaseSpace (SRA) Sequence Read Archive import/conversion application titled . annotates the SRA Import Arkas-Analysis Kallisto results by extracting structured information directly from source FASTA files with per-contig metadata, calculates the differential expression and gene-set enrichment analysis on both coding genes and transcripts. The Arkas cloud pipeline supports ENSEMBL transcriptomes and can be used downstream from the facilitating raw sequencing importing, SRA SRA Import FASTQ conversion, RNA quantification and analysis steps.

Senescence induction universally activates transposable element expression

“…Transcript abundance was quantified by pseudoalignment using Kallisto [29]. Sequenced reads were mapped to a reference transcriptome prepared using Arkas [30], comprised of ENSEMBL human (GRCh38build 81) coding and non-coding transcripts, repetitive elements (RepBase issue 21-03). Arkas managed the preparation of indices, quantification of transcript abundance, and annotation of Kallisto results by leveraging S4-summarized experiment structure.…”

Tximeta: Reference sequence checksums for provenance identification in RNA-seq

“…While other RNA-seq pipelines can import quantification data into R/Bioconductor, tximeta uniquely allows for post hoc identification of the reference sequence provenance. The most directly related RNA-seq software packages create a SummarizedExperiment, or an object of similar shape and function, including Arkas [16], ARMOR [17], htseq [33], featureCounts [34] from the Rsubread package, and summarizeOverlaps [30] from the Geno-micAlignments package. Arkas is a framework for importing transcript-level quantification data into R/Bioconductor, and specifically designed for extracting annotation metadata from Ensembl FASTA files.…”

“…Refgenie is a tool that helps with management of bundles of files associated with reference genomes, and facilitates sharing provenance information across research groups, in that the generation of resources is scripted [15]. Arkas and ARMOR are frameworks for automating bioinformatic analyses for RNA-seq, where metadata can be assembled and attached programmatically to downstream outputs [16,17]. The pepkit framework and the basejump R package assist with organization and management of metadata in bioinformatic pipelines, though these cannot allow for post hoc identification of reference provenance [18,19].…”