BrainImageR: Spatiotemporal gene set analysis referencing the human brain

Linker, S.; Hsu, J. Y.; Pfaff, A.; Amatya, D.; Ko, S.-M.; Voter, S.; Wong, Q.; Gage, F. H.

doi:10.1101/229302

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bioRxiv · 10.1101/229302

BrainImageR: Spatiotemporal gene set analysis referencing the human brain

Linker, S.·Hsu, J. Y.·Pfaff, A.·Amatya, D.·Ko, S.-M.·Voter, S.·Wong, Q.·Gage, F. H.

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Abstract

RATIONALENeurological molecular analyses such as transcriptomics, epigenetics, and genome-wide association studies must be assessed in the context of the human brain in order to generate biologically meaningful inferences. It is often difficult to access primary human brain tissue; therefore, approximations are made using in vitro modeling or by identifying disease-associated genes from DNA extracted from blood. Gene sets from these studies are then compared to the post-mortem human brain to provide an assessment of the brain region and the developmental time point that a gene set is most closely associated with. However, most analyses of postmortem datasets are achieved by building new computational tools each time in-house, which can cause discrepancies from study to study, indicating that the field is in need of a user-friendly suite of tools to examine spatiotemporal expression with respect to the postmortem brain. Such a tool will be of use to the molecular interrogation of neurological and psychiatric disorders, with direct advantages for the disease-modeling and human genetics communities.\n\nRESULTSWe have developed brainImageR, an R package that calculates both the spatial and temporal association of a dataset with post-mortem gene expression data from the Allen Brain Atlas. BrainImageR performs a robust analysis of gene set enrichment to identify enriched anatomical regions, provides a global high-resolution visualization of these enrichments across the human brain, and predicts when in developmental time the sample is most closely matched to, a task that has become increasingly important in the field of in vitro neuronal modeling. These functionalities of brainImageR enable a quick and efficient characterization of a given dataset across normal human brain development.\n\nAVAILABILITY AND IMPLEMENTATIONBrainImageR is released under the Creative Commons CC BY-SA 4.0 license and the source code can be downloaded through github at https://github.com/saralinker/brainImageR.\n\nCONTACTgage@salk.edu

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Linker, S., Hsu, J. Y., Pfaff, A., Amatya, D., Ko, S.-M., Voter, S., Wong, Q., Gage, F. H.. 2017-12-06. BrainImageR: Spatiotemporal gene set analysis referencing the human brain. https://doi.org/10.1101/229302

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