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GenAp specifications


Unique identifier OMICS_11117
Name GenAp
Software type Framework/Library
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux
Programming languages Scala
License Apache License version 2.0
Computer skills Advanced
Stability Stable
Maven, Java
Maintained Yes


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  • person_outline Christos Kozanitis

Publication for GenAp

GenAp citations


Integrating clinical decision support systems for pharmacogenomic testing into clinical routine a scoping review of designs of user system interactions in recent system development

BMC Med Inform Decis Mak
PMCID: 5461630
PMID: 28587608
DOI: 10.1186/s12911-017-0480-y

[…] s reported that the provided pharmacogenomic summary reports were clinically relevant (“strongly agree”: 10%, “somewhat agree”: 76%) [].Laerum et al. evaluated the pharmacogenomic CDSS reports of the genAP project in a simulated environment with nine participating physicians. All physicians rated the contents of the pharmacogenomics CDSS as useful, trustworthy, clearly presented and worthwhile log […]


Heads in the Cloud: A Primer on Neuroimaging Applications of High Performance Computing

PMCID: 4896536
PMID: 27279746
DOI: 10.4137/MRI.S23558

[…] he infrastructure and platform (PaaS), in which case users are responsible for installing their own analysis software. Although Compute Canada has a cloud solution for life science researchers called GenAp (, most of Compute Canada’s cloud solutions are of the latter type, where users need to install all of the necessary software (including the operating system). T […]


Refined mapping of autoimmune disease associated genetic variants with gene expression suggests an important role for non coding RNAs

PMCID: 5391837
PMID: 26898941
DOI: 10.1016/j.jaut.2016.01.002

[…] s were extracted from the BluePrint epigenome project ( and the ENCODE data from the UCSC browser ( These regions were intersected with gSNPs and their proxies (r2 ≥ 0.8). See for more information about the cell lines. […]

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GenAp institution(s)
Department of Computer Science, University of California Berkeley, Berkeley, CA, USA
GenAp funding source(s)
This research is supported in part by NIH BD2K Award 1-U54HG007990-01 and NIH Cancer Cloud Pilot Award HHSN261201400006C, NSF CISE Expeditions Award CCF-1139158, LBNL Award 7076018, and DARPA XData Award FA8750-12-2-0331, and gifts from Amazon Web Services, Google, SAP, The Thomas and Stacey Siebel Foundation, Adatao, Adobe, Apple, Inc., Blue Goji, Bosch, C3Energy, Cisco, Cray, Cloudera, EMC2, Ericsson, Facebook, Guavus, Huawei, Informatica, Intel, Microsoft, NetApp, Pivotal, Samsung, Schlumberger, Splunk, Virdata and VMware.

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