Methods and systems for computer-generated predictive application of neuroimaging and gene expression mapping data
The present disclosure relates to computer generated topographies from computer correlations of neurobehavioral phenotype mapping data and gene expression mapping data. Neurobehavioral phenotype mapping data is obtained for a selected phenotype and correlated with gene expression mapping data for one or more genes to define a phenotype-gene pair topography for each phenotype-gene pair. A score for each phenotype-gene pair is determined based on the correlation. The scores are used to identify genes, or drug targets, associated with the respective gene of the respective phenotype-gene pair. Conversely, gene expression mapping data is obtained for a selected gene and correlated with neurobehavioral phenotype mapping data for one or more phenotypes to define a gene-phenotype topography for each gene-phenotype pair. A score for each gene-phenotype pair is determined based on the correlation. The scores are used to identify a phenotype associated with the respective phenotype-gene pair.
1. A computing device, comprising:
a memory that stores computer instructions;
a processor that, when executing the computer instructions, performs actions to:
generate a neurophenotype topography for a selected neurobehavioral phenotype based on neurobehavioral phenotype mapping data for the selected neurobehavioral phenotype;
generate a genotype topography for each respective gene of a plurality of genes based on gene expression mapping data for the respective gene;
define a plurality of phenotype-gene pair topographies between the selected neurobehavioral phenotype and the plurality of genes, each phenotype-gene pair topography for each respective phenotype-gene pair being defined based on the neurophenotype topography of the selected neurobehavioral phenotype and the genotype topography of the respective gene for the respective phenotype-gene pair;
determine a quantitative score for each of the plurality of phenotype-gene pair topographies based on a correlation between the neurophenotype topography of the selected neurobehavioral phenotype and the genotype topography of the respective gene for the respective phenotype-gene pair;
select one or more of the plurality of phenotype-gene pair topographies having a respective score above a selected threshold; and
cause the respective genes of the selected one or more phenotype-gene pair topographies to be displayed on a display device for a user, the display device being configured to receive inputs from the user.
2. The computing device of claim 1 , wherein the processor, when executing the computer instructions, further performs actions to identify one or more respective neural drug targets associated with the respective genes of the selected one or more phenotype-gene pair topographies.
3. The computing device of claim 1 , wherein the processor generates the neurophenotype topography by executing further computer instructions to generate the neurophenotype topography from the neurobehavioral phenotype mapping data for each of a plurality of people having the selected neurobehavioral phenotype.
4. The computing device of claim 1 , wherein the processor determines the score for each of the plurality of phenotype-gene pair topographies by executing further computer instructions to determine a statistical significance for each phenotype-gene pair topography based on an alignment between the gene expression mapping data for the respective gene with the neurobehavioral phenotype mapping data.
5. The computing device of claim 1 , wherein the processor selects the one or more phenotype-gene pair topographies by executing further computer instructions to select a target phenotype-gene pair topography having a highest determined measure of association between the neurophenotype topography of the selected neurobehavioral phenotype and the genotype topography of the respective gene for the target phenotype-gene pair topography.
6. The computing device of claim 1 , wherein the gene expression mapping data for each of the plurality of genes includes gene expression mapping data for a plurality of gene expressions from a plurality of people without the selected neurobehavioral phenotype.
7. The computing device of claim 6 , wherein the processor generates the genotype topography for each respective gene by executing further computer instructions to select a representative probe for each of the plurality of genes across the plurality of gene expressions for the plurality of people.
8. The computing device of claim 1 , wherein the processor generates the genotype topography for each respective gene by executing further computer instructions to map gene expression mapping samples to locations in brain structures, wherein causing the respective genes of the selected one or more phenotype-gene pair topographies to be displayed on the display device includes sending, to a second processor at the display device:
the respective genes of the selected one or more phenotype-gene pair topographies; and
one or more instructions to display a graphical representation of the respective genes on the display device.
9. The computing device of claim 1 , wherein the processor generates the genotype topography for each respective gene by executing further computer instructions to filter gene expression mapping samples by excluding samples with measured expression levels below a threshold level above background signals.
10. The computing device of claim 1 , wherein the processor generates the genotype topography for each respective gene by executing further computer instructions to impute probe values in gene expression mapping samples that are missing probe values.
11. The computing device of claim 1 , wherein the processor generates the genotype topography for each respective gene by executing further computer instructions to remove extraneous biases from the gene expression mapping data.
12. The computing device of claim 11 , wherein the processor removes the extraneous biases by executing further computer instructions to de-mean and normalize z-scores across gene probes used to capture the gene expression mapping data.
13. The computing device of claim 1 , wherein the processor generates the genotype topography for each respective gene by executing further computer instructions to increase a signal-to-noise ratio in the gene expression mapping data.
14. The computing device of claim 13 , wherein the processor increases the signal-to-noise ratio by executing further computer instructions to average expression levels of the gene expression mapping data for samples mapped onto a same surface vertex.
15. The computing device of claim 1 , wherein the processor generates the genotype topography for each respective gene by executing further computer instructions to interpolate sparse gene expression samples from sampled brain regions to other non-sampled brain regions.
16. The computing device of claim 15 , wherein the processor interpolates the sparse gene expression samples by executing further computer instructions to generate at least one of parcellated cortical or subcortical maps or a dense cortical or subcortical map.
17. The computing device of claim 1 , wherein the processor generates the genotype topography for each respective gene by executing further computer instructions to assign a weight value for each of a plurality of brain regions in the gene expression mapping data.
18. The computing device of claim 1 , wherein the processor generates the neurobehavioral topography by executing further computer instructions to assign a weight value for each of a plurality of brain regions in the neurobehavioral phenotype mapping data.
19. The computing device of claim 18 , wherein the processor assigns the weight value for each of the plurality of brain regions by executing further computer instructions to:
assign a first set of weight values above a threshold value for a first set of brain regions of the plurality of brain regions in the neurobehavioral phenotype mapping data; and
assign a second set of weight values below the threshold value for a second set of brain regions of the plurality of brain regions in the neurobehavioral phenotype mapping data.
20. The computing device of claim 18 , wherein the processor assigns the weight value for each of the plurality of brain regions by executing further computer instructions to assign a masking weight value to a target brain region of the plurality of brain regions to remove information associated with the target brain region from the neurobehavioral phenotype mapping data.
21. The computing device of claim 1 , wherein the processor defines the plurality of phenotype-gene pair topographies by executing further computer instructions to define at least one combination phenotype-gene pair topography between the neurobehavioral phenotype topography and a combination of genotype topographies for a combination of genes.
22. The computing device of claim 21 , wherein the processor, when executing the computer instructions, further performs actions to:
select the at least one combination phenotype-gene pair topography as the one or more of the plurality of phenotype-gene pair topographies having the respective score above the selected threshold; and
display the combination of genes to the user.
23. The computing device of claim 1 , wherein the processor, when executing the computer instructions, further performs actions to:
identify combinations of genes or neural drug targets by combining gene expression mapping data that exhibits improved alignment with the neurobehavioral phenotype mapping data relative to the alignment of gene expression mapping data and neurobehavioral phenotype mapping data for each separate gene or neural drug target.
24. The computing device of claim 1 , wherein the display device is a touch sensitive screen.
25. A method, comprising:
obtaining, by a computing device, neurobehavioral phenotype mapping data for a selected neurobehavioral phenotype;
generate a neurophenotype topography for the selected neurobehavioral phenotype based on the neurobehavioral phenotype mapping data for the selected neurobehavioral phenotype;
obtaining, by the computing device, gene expression mapping data for a plurality of genes;
generate a genotype topography for each respective gene of the plurality of genes based on the gene expression mapping data for the respective gene;
determining, by the computing device, a quantitative score for each respective phenotype-gene pair between the selected neurobehavioral phenotype and a respective gene of the plurality of genes based on a correlation between the neurobehavioral phenotype mapping data for the selected neurobehavioral phenotype and the gene expression mapping data for the respective gene of the respective phonotype-gene pair; and
causing, by the computing device, the determined score for each phenotype-gene pair to be presented to a user on a display device, the display device being configured to receive inputs from the user.