brain-map
DESCRIPTION
http://www.brain-map.org. ALLEN BRAIN ATLAS: ADULT HUMAN. “Whole brain” microarrays: Agilent 8x60k array , starting from 4x44k Agilent Whole Human Genome probe set 2+ probes for 93% of genes [~21k unique Entrez Ids]. Gene Finder. - PowerPoint PPT PresentationTRANSCRIPT
http://www.brain-map.org
ALLEN BRAIN ATLAS: ADULT HUMAN• “Whole brain” microarrays: Agilent 8x60k
array, starting from 4x44k Agilent Whole Human Genome probe set
• 2+ probes for 93% of genes [~21k unique Entrez Ids]
Gene Finder• User navigates to voxel-of-interest in reference
atlas volume and a fixed threshold AGEA correlation map appears
• Get a gene list from ABA is returned.
AGEA Gene Finder Tool enables users to search a local anatomic region of
interest for genes that exhibit localized enrichment
Finding genes with highly localized expression is of neuroscientific interest - structural relationships, evidence for refinement of structural boundaries.
For seed s, correlation value t, find set of voxels N(t,s)
Let B(s) = N(T,s)
Let A(s) be local neighborhood of highest correlated voxels
The Finder Algorithm
Ranked List of Genes
Computation is independent for 16 brain regions R with unique intra‐correlation patterns
Regions include - cortex, hippocampus, striatum, thalamus, olfactory bulb, cerebellar cortex, hypothalamus, midbrain and hindbrain.
Special Regions - Ventricular areas, medial habenula, caudoputamen, deep cortical layers, olfactory nerve layer of the olfactory bulb, zona incerta and inferior
Cortical Map
Genes in superficial layers have sharp drop in correlation depth-wise
Transition not smooth – L5 & L6: column a
Vice-versa; Expression in deep layers reduces correlation in superficial layers
Laminar effects - seeds in somatosensory L6 have lower L4 correlation (column d) than seeds in L2/3
Visualizing Correlations
Allows interpretation of relative correlations across layers and regions.
Mean correlation is highest in the domain containing the seed
Use representation to determine dominant area (columns) or layer (rows) to show that adjacent layers have positive expression correlation
Strongest concordance between L5 and L6
Non-adjacent layers - negative correlation with anatomic proximity: physically distant layers less likely to exhibit gene coexpression.
Multi-dimensional Scaling
Domain-to-domain correlations as measure of similarity Data is visualized by multidimensional scaling (MDS) Clustering method Distance between points (domains) is proportional to
their correlation MDS recapitulates the basic laminar and areal
relationships of the neocortex Proximal and functional relationship of SSp and SSs Lower concordance of VISp with other regions.
Multi Dimensional Scaling
Multidimensional Scaling
From amatrix of
distances…
Kruskal & Wish, 1978
MDS
…itcalculatesa map…
MDSWhat does the MDS algorithm do?
…but itcannot tell
theorientationand themeaning ofthe axes.
Tuesday, May 5, 2009
MDSShepard, 1963:
• Morse-codes presented in pairs to naïve observers (each possiblecombination)
• Task - Same/different• Confusion matrix (% same responses): can be interpreted as adissimilarity matrix
MDS Algorithm
• Given a set of similarities (or distances) between every pairof N items• Find a representation of the items in few dimensions
• Inter-item proximities “nearly” match the original similarities(or distances)
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Tuesday, May 5, 2009
Objective
Kruskal’s Stress
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