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

Authors :
Andrian Yang
Troup, Michael
Peijie Lin
Ho, JoshuaW. K.
Source :
Bioinformatics. 3/1/2017, Vol. 33 Issue 5, p767-769. 3p. 2 Charts.
Publication Year :
2017

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. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
13674803
Volume :
33
Issue :
5
Database :
Academic Search Index
Journal :
Bioinformatics
Publication Type :
Academic Journal
Accession number :
121554977
Full Text :
https://doi.org/10.1093/bioinformatics/btw732