PT  - JOURNAL ARTICLE
AU  - Sajid Mughal
AU  - Ismail Moghul
AU  - Jing Yu
AU  - Tristan Clark
AU  - David S Gregory
AU  - Nikolas Pontikos
TI  - Pheno4J: a gene to phenotype graph database
AID  - 10.1101/142257
DP  - 2017 Jan 01
TA  - bioRxiv
PG  - 142257
4099  - http://biorxiv.org/content/early/2017/05/25/142257.short
4100  - http://biorxiv.org/content/early/2017/05/25/142257.full
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