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bioRxiv · 10.1101/064006

Falco: A quick and flexible single-cell RNA-seq processing framework on the cloud

Andrian Yang·Michael Troup·Joshua W.K. Ho
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Abstract

SummarySingle-cell RNA-seq (scRNA-seq) is increasingly used in a range of biomedical studies. Nonetheless, current RNA-seq analysis tools are not specifically designed to efficiently process scRNA-seq data due to their limited scalability. Here we introduce Falco, a cloud-based framework to enable paralellisation of existing RNA-seq processing pipelines using big data technologies of Apache Hadoop and Apache Spark for performing massively parallel analysis of large scale transcriptomic data. Using two public scRNA-seq data sets and two popular RNA-seq alignment/feature quantification pipelines, we show that the same processing pipeline runs 2.6 - 145.4 times faster using Falco than running on a highly optimised single node analysis. Falco also allows user to the utilise low-cost spot instances of Amazon Web Services (AWS), providing a 65% reduction in cost of analysis.\n\nAvailabilityFalco is available via a GNU General Public License at https://github.com/VCCRI/Falco/\n\nContactj.ho@victorchang.edu.au\n\nSupplementary informationSupplementary data are available at BioRXiv online.

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Andrian Yang, Michael Troup, Joshua W.K. Ho. 2016-07-15. Falco: A quick and flexible single-cell RNA-seq processing framework on the cloud. https://doi.org/10.1101/064006

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