RT Journal Article
SR Electronic
T1 Pheno4J: a gene to phenotype graph database
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 142257
DO 10.1101/142257
A1 Sajid Mughal
A1 Ismail Moghul
A1 Jing Yu
A1 Tristan Clark
A1 David S Gregory
A1 Nikolas Pontikos
YR 2017
UL http://biorxiv.org/content/early/2017/05/25/142257.abstract
AB Summary Efficient storage and querying of large amounts of genetic and phenotypic data is crucial to contemporary clinical genetic research. This introduces computational challenges for classical relational databases, due to the sparsity and sheer volume of the data. Our Java based solution loads annotated genetic variants and well phenotyped patients into a graph database to allow fast efficient storage and querying of large volumes of structured genetic and phenotypic data. This abstracts technical problems away and lets researchers focus on the science rather than the implementation. We have also developed an accompanying webserver with end-points to facilitate querying of the database.Availability and Implementation The Java code and python code is available at https://github.com/phenopolis/pheno4iContact n.pontikos{at}ucl.ac.uk