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Re: Spatial queries against GENSAT or ABA

From: William Bug <William.Bug@drexelmed.edu>
Date: Sun, 4 Mar 2007 14:04:43 -0500
Message-Id: <E51F8E0F-F56E-4311-B4A6-A5EEB701B975@drexelmed.edu>
Cc: kc28 <kei.cheung@yale.edu>, Alan Ruttenberg <alanruttenberg@gmail.com>, June Kinoshita <junekino@media.mit.edu>, Donald Doherty <donald.doherty@brainstage.com>, Gwen Wong <wonglabow@verizon.net>, W3C HCLSIG hcls <public-semweb-lifesci@w3.org>, "Robert W. Williams" <rwilliam@nb.utmem.edu>, zaslavsk@sdsc.edu
To: Maryann Martone <maryann@ncmir.ucsd.edu>
Given the UNIQUE work BIRN, your lab, and Ilya have done in applying  
GIS techniques to this problem of creating a SPATIAL-QUERY capable  
brain atlasing system (the SMART Atlas), it would be wonderful if  
Ilya could vet the scenarios as I outline them below.  This is my  
best understanding of what is required, but it may be very 3D-biased  
because of the work we do at Drexel.  To my mind, the problem is the  
same, only the strategies for solving it are a little be different -  
in some ways more tractable in 2D - though the answers may come with  
more constraints.

I did pass some emails around to the SMART Atlas folks early last  
week in order to get their feedback on Alan's work on the Google Maps  
Javascript API and backend PERL code to support caching images.  The  
Google Maps API is one that has come up endless in these atlasing  
discussions, and it's nice to see just how it can be made useful -  
what it can and cannot do in this application space.

As Maryann states - and I've stated several times - there is ONGOING  
work on several projects seeking to provide this functionality  
applied to the ABA and GENSAT gene expression image data  
repositories.  None of it - that I'm aware of - would be ready for  
use by the first week in May - or really at least a month before - to  
test.  I do think there are other low-hanging fruit, tractable  
opportunities in the time frame of for the HCLS IG demo for which  
SemWebTech is specifically suited, and Alan is converging on several  
of them.


On Mar 4, 2007, at 1:44 PM, Maryann Martone wrote:

> This is exactly what BIRN has been working on through the Smart  
> Atlas project and now MBAT.  The inverse query is also true:  What  
> genes are expressed here?  As Bill indicated, there are several  
> spatially normalized atlas projects (ABA, GEnepaint) that can do  
> that.  We've been working on spatial normalization of some of the  
> GEnsat images, although we haven't gotten very far.  More  
> importantly, BIRN has been working on exchange of coordinate  
> systems so that different atlases can talk to each other.
> I think that's why Bill has been trying to get everyone together on  
> this. I've added Ilya Zaslavsky, our GIS expert, to this list.
> Maryann Martone, Ph. D.
> Professor-in-Residence
> Dept of Neuroscience
> University of California, San Diego
> San Diego CA  92093-0446
> 858 822 0745 (T)
> 858 822 0828 (F)
> On Sat, 3 Mar 2007, William Bug wrote:
>> Hi Kei,
>> You are right on target re: use of a coordinate-based, spatial  
>> query system to resolve the relatively simple query: "In which  
>> brain regions is GENE X expressed?"
>> This is the whole goal of several major neuroinformatics projects  
>> currently underway which are designed to use either 2D or 3D  
>> digital brain atlases to make such a query possible.  Several of  
>> those efforts are associated with the BIRN project.  In fact  
>> several such projects working on inbred mouse strain atlases have  
>> been striving to function synergistically within a single system  
>> (the Mouse BIRN Atlasing Tool or MBAT) specifically to support  
>> such a query. ABA is not currently available to query within MBAT,  
>> because it's not registered to the primary atlas being used in  
>> MBAT right now.  This work may eventually get done, but it won't  
>> be ready for the demo.
>> The absolute pre-requisites for resolving such a query are:
>> 	1) you must have a set of canonical brain images (2D) or a true  
>> voxel based canonical brain (3D) - "ATLASES" - that include expert- 
>> assisted brain region segmentation.
>> 	2) these canonical pixel-based brain images (2D) or voxel based  
>> images (3D) must be situated within a defined coordinate space.
>> 	3) the segmented brain regions must be deterministically placed  
>> within the same coordinate space.
>> 	4) the images containing the gene expression patterns must be  
>> segmented (manually, semi-automatically, or automatically) to  
>> provide defined geometries for the expression patterns.
>> 	5) the images containing the gene expression patterns must be  
>> registered to the canonical atlas data and coordinate space  
>> (whether 2D or 3D).
>> With these conditions met, you could then present a user with a  
>> nice 3D visualization of the atlas (or even just the list of brain  
>> region IDs or preferred labels) and/or a list of gene names/IDs  
>> and let them ask both of the following questions:
>> 	a) In which brain regions is GENE X expressed?
>> 	b) Which genes does BRAIN REGION X contain defined expression  
>> values beyond some baseline?
>> Right now, GENSAT is not registered to an atlas, so there is no  
>> coordinate frame to support resolving such as query.  They have  
>> manually curated many of the gene-specific images with both brain  
>> regions and cell types, so you can pose that query and get an  
>> answer based on the curation they have had the resources to do so  
>> far, but there is no way to place it in a GIS context (2D or 3D),  
>> since none of their info is YET linked to a canonical coordinate  
>> space (several projects are working on this very issue).
>> ABA has aligned to a 2D mouse brain atlas (F&P C57Bl/6 adult brain  
>> atlas). In doing so, the 2D brain region segmentations on each of  
>> the images in the F&P mouse atlas can be super-imposed on the  
>> registered images from any of the 20,000+ brains.  The problem is  
>> the current registration has a moderate error associated with it,  
>> so that answering that query programmatically is problematic and  
>> often not very informative.  The following can be done:
>> 	- along the coronal sectioning axis, give me the plate numbers  
>> for all the images in the atlas that contain a slice through the  
>> 	- for ABA brain stained for GENE X, give me all the sections that  
>> have been roughly aligned to that set of F&P atlas images.
>> From there the alignment is so coarse at this point, you could  
>> only use the atlas plates and location of the STRIATUM to help  
>> guide a qualitative assessment of whether there appears to be any  
>> staining in the STRIATUM.
>> In fact, via this route, many contributers to GeneNetwork.org have  
>> actually linked the probe sets in their microarray QTL database to  
>> staining patterns in ABA.  In other words, if through there  
>> system, you uncover via QTL a locus or collection of SNPs  
>> associated with altered expression of a given gene - say Dopamine  
>> Receptor, type D2 (DRD2) - you might find someone has added an ABA  
>> or GENSAT annotation for DRD2 using the GeneNetwork.org GeneWiki.
>> 	1) Go to www.genenetwork.org
>> 		http://www.genenetwork.org/search3.html
>> 	2) Enter 'DRD2' in the 'ANY' box searching against the default  
>> settings for other fields - & hit 'Search'
>> 	3) Click on the single result entry
>> 	4) In the record for DRD2, click on the GeneWiki button near the  
>> top of the page
>> 	5) This will bring up a listing of all the annotations in  
>> GeneNetwork for DRD2 including qualitative annotations that  
>> someone did for the ABA DRD2 brain.
>> If you want to see ALL of the genes for which ABA or GENSAT  
>> GeneWiki entries exist, just go back to step '1', enter wiki=ABA  
>> or wiki=GENSAT respectively in one of the 'ANY' boxes, and hit  
>> 'Search'.  Then pick up at step '3' above.
>> Were we able to SCRAPE this, then you would have annotation for  
>> ABA that is roughly equivalent to that which exists for GENSAT -  
>> ONLY - it probably is doesn't cover the ABA very thoroughly (using  
>> the generic 'wiki=aba' brings up 948 probe sets - or ~5% of ABA -  
>> pretty remarkable, actually, given its a manual effort), and these  
>> GeneWiki annotations are mostly in free-text right now and are not  
>> done to a controlled vocabulary or classification scheme. :-(
>> When the registration to the atlas improves to say the 50 - 100  
>> micron range, then the flood-gates will open, and all 20,000  
>> brains in ABA each staining for a particular gene will be able to  
>> automatically provide relatively solid answers to  these straight- 
>> forward questions related to where in the brain is Gene X  
>> expressed - and which genes does Brain Region Y show marked  
>> expression of.  Even here, however, there will be continued room  
>> for nuance in defining the ABA staining patterns - AND - there  
>> will be a need to eventually to add the time dimension to all  
>> these queries (e.g., "When is Gene X expressed in Brain Region Y?").
>> Because the ABA has created multi-resolution versions of their  
>> brain images (both the Nissl stains for cell bodies and the pseudo- 
>> colored ISH images for a given gene), it is possible to use the  
>> very nice Google Maps API GUI Alan created to select a given 1 of  
>> the 20,000 ABA brains and simply Zoom & Pan on the actual pixel  
>> image data.  However, there is no straight-forward way to use it  
>> to pose and answer SPATIAL queries.
>> What MIGHT be possible - based on the alignment they have done and  
>> the information provided in that brain region ontology Excel file  
>> Alan has - is to say, for the 'DRD2' brain, filter the sagittal  
>> image series to create a subset including only those images  
>> aligned to an F&P atlas images which contains a section through  
>> Brain Region X (say 'STRIATUM').  This way, if through some SPARQL  
>> query you pulled up a relation between DRD2 and STRIATUM, you'd be  
>> able to present a user with a very nice, low-tech interface to  
>> quickly pan&zoom on the median section of that 'STRIATUM'-filtered  
>> series to look at the staining pattern.  You could add a  
>> navigation control to go back-n-forth through the series for the  
>> DRD2 brain, so they could get a pretty good sense in 3D where DRD2  
>> expression is in the striatum.  You might also go to BAMS or  
>> CoCoMac (BAMS is better in this instance since it's rodent focused  
>> - whereas CoCoMac is primate focused) to automatically determine  
>> what regions connect to (is_afferent_to) and what regions are  
>> connected to (is_efferent_to) the STRIATUM.  You could then bring  
>> up another HTML frame that gives you a view of the DRD2 subset  
>> series for those brain regions, too.
>> quite tractable for the demo - if this sounds like a useful  
>> feature to provide.
>> Running atlas-based SPATIAL queries against GENSAT and ABA is a  
>> very much sought after goal both for the curators of those  
>> repositories and for the neuroscience community at large, but we  
>> are not there yet.
>> I'm not certain I understand what you are asking re: highly  
>> expressed genes that correlate with high levels of ADDL or Abeta.   
>> I could see how you might be able to use GENSAT (which has a  
>> 'staining intensity' annotation field) to ask whether genes  
>> associated with high levels of specific ADDL species or with  
>> plaque deposition are expressed at high levels in the GENSAT data  
>> set - and if so - where are they expressed in the brain - and at  
>> what developmental time.  Given the sparse nature of the GENSAT  
>> data set, this would not be a comprehensive answer to the  
>> question, but it could prove very interesting. I'm certain June,  
>> Gwen, or Elisabeth could help us identify genes whose expression  
>> correlates with high levels of ADDL species (most interesting  
>> question given current AD research) or with other APP related  
>> macromolecules or plaques.  I'm not certain how you'd ask the same  
>> question of ABA, given there are not systematic annotations on  
>> staining intensity or pattern - though some of this has been done  
>> (see below).
>> Cheers,
>> Bill
>> On Mar 3, 2007, at 8:01 PM, kc28 wrote:
>>> Alan et al.,
>>> In addition to mapping to brain regions, what seems to be also  
>>> missing is some kind of brain coordinates. I thought one major  
>>> advanatage of using Google Map is the ability to issue GIS-like  
>>> queries. With this type queries, one can potentially query  
>>> something like finding expressed genes for a given brain region  
>>> and its neighbouring/adjacent regions.
>>> While we are talking about gene expression, what seems to be also  
>>> logical to consider is whether some highly expressed genes  
>>> correlate with high abundance of pathological proteins (e.g.,  
>>> amyloid beta). Any take from neuroscientists?
>>> -Kei
>>> Alan Ruttenberg wrote:
>>>> On Mar 2, 2007, at 1:56 PM, Kei Cheung wrote:
>>>>> By reading the AD/PD use case, one of the questions has to do  
>>>>> with  what genes are expressed in what regions of the brain (if  
>>>>> such gene expressions are localized to certain brain regions).  
>>>>> I wonder what Alan's currently working on can help address this  
>>>>> type of question  (even though the kind of gene expression data  
>>>>> is for the mouse --  perhaps we can find homologous genes for  
>>>>> human). Also, I'd  encourage people to take look at what Bill  
>>>>> Bug's Wiki page:
>>>> What I can do is add an orthology mapping. Probably from orthogene.
>>>> I can also scrape the Allen site for the following query they  
>>>> provide
>>>> Brain Region(see list below), Expression-level(low/ 
>>>> high),Expression- density(low/high), expression pattern 
>>>> (clustered/not clustered). =>  gene set
>>>> So this would be 16x2x2x2 = 128 different gene sets.
>>>> There is also their "Fine structure search" :
>>>> Fine structure annotation lists are genes that have high  
>>>> specificity expression in particular brain regions or nuclei.
>>>> They provide these gene lists for a set of structures listed  
>>>> below  (fine structures).
>>>> This can lead us to a particular image, though I don't have a  
>>>> way yet  to identify which portion of the image corresponds to a  
>>>> particular  region or structure.
>> Bill Bug
>> Senior Research Analyst/Ontological Engineer
>> Laboratory for Bioimaging  & Anatomical Informatics
>> www.neuroterrain.org
>> Department of Neurobiology & Anatomy
>> Drexel University College of Medicine
>> 2900 Queen Lane
>> Philadelphia, PA    19129
>> 215 991 8430 (ph)
>> 610 457 0443 (mobile)
>> 215 843 9367 (fax)
>> Please Note: I now have a new email - William.Bug@DrexelMed.edu

Bill Bug
Senior Research Analyst/Ontological Engineer

Laboratory for Bioimaging  & Anatomical Informatics
Department of Neurobiology & Anatomy
Drexel University College of Medicine
2900 Queen Lane
Philadelphia, PA    19129
215 991 8430 (ph)
610 457 0443 (mobile)
215 843 9367 (fax)

Please Note: I now have a new email - William.Bug@DrexelMed.edu
Received on Sunday, 4 March 2007 19:05:12 UTC

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