Published in

Nature Research, Nature Biotechnology, 3(38), p. 288-292, 2020

DOI: 10.1038/s41587-019-0360-3

Links

Tools

Export citation

Search in Google Scholar

Butler enables rapid cloud-based analysis of thousands of human genomes.

Journal article published in 2020 by Liming Yang, Denis Yuen, Christina K. Yung, Junjun Zhang, Christof von Kalle, Takashi Yugawa, Rui Yamaguchi, Takafumi N. Yamaguchi, Masakazu Yamamoto, Shogo Yamamoto, Hiroki Yamaue, Fan Yang, Huanming Yang, Jean Y. Yang, Lixing Yang and other authors.
This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

Full text: Download

Green circle
Preprint: archiving allowed
Orange circle
Postprint: archiving restricted
Red circle
Published version: archiving forbidden
Data provided by SHERPA/RoMEO

Abstract

AbstractWe present Butler, a computational tool that facilitates large-scale genomic analyses on public and academic clouds. Butler includes innovative anomaly detection and self-healing functions that improve the efficiency of data processing and analysis by 43% compared with current approaches. Butler enabled processing of a 725-terabyte cancer genome dataset from the Pan-Cancer Analysis of Whole Genomes (PCAWG) project in a time-efficient and uniform manner.