STORMSeq: an open-source, user-friendly pipeline for processing personal genomics data in the cloud.
The increasing public availability of personal complete genome sequencing data has ushered in an era of democratized genomics. However, read mapping and variant calling software is constantly improving and individuals with personal genomic data may prefer to customize and update their variant calls. Here, we describe STORMSeq (Scalable Tools for Open-Source Read Mapping), a graphical interface cloud computing solution that does not require a parallel computing environment or extensive technical experience. This customizable and modular system performs read mapping, read cleaning, and variant calling and annotation. At present, STORMSeq costs approximately $2 and 5-10 hours to process a full exome sequence and $30 and 3-8 days to process a whole genome sequence. We provide this open-access and open-source resource as a user-friendly interface in Amazon EC2.
Biomedical Informatics Training Program, Stanford University School of Medicine, Stanford, California, United States of America ; Department of Genetics, Stanford University School of Medicine, Stanford, California, United States of America.
Konrad J
KJ
Karczewski
Biomedical Informatics Training Program, Stanford University School of Medicine, Stanford, California, United States of America ; Department of Genetics, Stanford University School of Medicine, Stanford, California, United States of America.
Guy Haskin
GH
Fernald
Biomedical Informatics Training Program, Stanford University School of Medicine, Stanford, California, United States of America ; Department of Genetics, Stanford University School of Medicine, Stanford, California, United States of America.
Alicia R
AR
Martin
Department of Genetics, Stanford University School of Medicine, Stanford, California, United States of America.
Michael
M
Snyder
Department of Biomedical Informatics, Columbia University, New York, New York, United States of America.
Nicholas P
NP
Tatonetti
Department of Genetics and Genomic Sciences, Mount Sinai School of Medicine, New York, New York, United States of America.
Joel T
JT
Dudley
D015894:Genome, Human; D006801:Humans; D014584:User-Computer Interface