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

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Abstract

Summary:

Single-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 paralellization 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 datasets 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 optimized standalone computer. Falco also allows users to utilize low-cost spot instances of Amazon Web Services, providing a ˜65% reduction in cost of analysis.

Availability and Implementation:

Falco is available via a GNU General Public License at https://github.com/VCCRI/Falco/

Contact:

j.ho@victorchang.edu.au

Supplementary information:

Supplementary data are available at Bioinformatics online.

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