We describe a system for meta-analysis where a wiki stores numerical data in
a simple format and a web service performs the numerical computation.
  We initially apply the system on multiple meta-analyses of structural
neuroimaging data results. The described system allows for mass meta-analysis,
e.g., meta-analysis across multiple brain regions and multiple mental
disorders.Comment: 5 pages, 4 figures SePublica 2012, ESWC 2012 Workshop, 28 May 2012,
  Heraklion, Greec

Kempton, Matthew J.

Nielsen, Finn Årup

Williams, Steven C. R.

English

arXiv

We describe a system for meta-analysis where a wiki stores numerical data in a simple format and a web service performs the numerical computation. We initially apply the system on multiple meta-analyses of structural neuroimaging data results. The described system allows for mass meta-analysis, e.g., meta-analysis across multiple brain regions and multiple mental disorders

Online Research Database In Technology

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R.Publication date:2012Link back to DTU OrbitCitation (APA):Nielsen, F. Å., Kempton, M. J., & Williams, S. C. R. (2012). Online open neuroimaging mass meta-analysis.Paper presented at Extended Semantic Web Conference (ESWC2012), Heraklion, Crete, Greece.Online open neuroimaging mass meta-analysisFinn A˚rup Nielsen1?, Matthew J. Kempton2, and Steven C. R. Williams21 DTU Informatics, Technical University of Denmark, Lyngby, Denmark.fn@imm.dtu.dk, http://www.imm.dtu.dk/~fn/2 Department of Neuroimaging, Institute of Psychiatry, King’s College London,London, UKAbstract. We describe a system for meta-analysis where a wiki storesnumerical data in a simple format and a web service performs the nu-merical computation. We initially apply the system on multiple meta-analyses of structural neuroimaging data results. The described systemallows for mass meta-analysis, e.g., meta-analysis across multiple brainregions and multiple mental disorders.1 IntroductionThe scientific process aggregates a large number of scientific results into a com-mon scientific consensus. Meta-analysis performs the aggregation by statisticalanalysis of numerical values presented across scientific papers. Collaborative sys-tems such as wikis may easily aggregate text and values from multiple sources.However, so far they have had limited ability to apply numerical analysis asrequired, e.g., by meta-analysis.Researchers have discussed the advantages and disadvantage of the toolsfor conducting systematic reviews from “paper and pencil”, over spreadsheets toRevMan and web-based specialized applications [10]: Setup cost, versatility, abil-ity to manage data, etc. In 2009 they concluded that “no single data-extractionmethod is best for all systematic reviews in all circumstances”. For example,RevMan and Archie of the Cochrane Library provide an elaborate system forkeeping track and analyzing textual and numerical data in meta-analyses, butthe system could not import information from electronic databases [10]. Ouroriginal meta-analyses [4, 5] relied on the Microsoft Excel spreadsheets laterdistributed on public web sites. Compared to an ordinary spreadsheet a wikisolution provides data entry provenance and collaborative data entry with im-mediately update. Shareable folders on cloud-based storage systems would helpcollaboration on spreadsheets, but yield no provenance. Online services, such asthe spreadsheet of Google Docs, may lack meta-analytic plotting facility. Web-based specialized applications for systematic reviews may have a high setup cost[10].We have previously explored a simple online meta-analysis system—a “fieldedwiki”—in connection with personality genetics [8]. As implemented specifically? Thanks to the Lundbeck Foundation for the funding of the Center for IntegratedMolecular Brain Imaging (CIMBI).arXiv:1206.2742v1  [cs.DL]  13 Jun 2012for this scientific area the web service lacks generality for other types for meta-analytic data. Furthermore the system relied on PubMed or Brede Wiki to rep-resent bibliographic information.Following Ward Cunningham’s quote “What’s the simplest thing that couldpossibly work?” we present a simple system that allows for mass meta-analysisof numerical data presented as comma-separated values (CSV) in a standardMediaWiki-based wiki, — the Brede Wiki: http://neuro.imm.dtu.dk/wiki/.2 Data and data representationWe use the MediaWiki-based Brede Wiki to represent the data [1]. For ourneuroimaging data each data record usually consists of three values (numberof subjects, their mean and standard deviation). The individual study typicallycompares two such data records, e.g., from a patient and a control group. Wealso record labels for the data record, e.g., the biographic information, as well asextra subject information about the two groups, such as age, gender and clinicalcharacteristics, so that the total number of data items for each study may beseven or more. Each meta-analysis will usually determine what extra relevant in-formation should be included and it may differ between studies, e.g., a Y-BOCSvalue has typically only relevance for obsessive-compulsive disorder patients. Thefunctional neuroimaging area has CogPO and Cognitive Atlas ontologies enablingresearchers to describe the topic of an experiment, but these efforts do not di-rectly apply to our data. One CSV line carries the information for each study.Fig. 1. Screenshot from the wiki showing CSVdata transcluded on a page.Separate wiki pages store—rather than uploaded files—the CSV data, so the Media-Wiki template functionalitycan transclude the CSV dataon other wiki pages. By con-vention pages with CSV in-formation have the “.csv” ex-tension as part of the titleso external scripts can recog-nize them as special pages andthe wiki pages have no wikimarkup.MediaWiki templates maygenerate links for download,editing and meta-analysis of the data. Presently, no controlled vocabulary be-yond the template fields describes the columns in the CSV. To generate anappropriate content-type (text/csv) a bridging web script functions as a proxy,so a download of the CSV page can spawn a client-side spreadsheet program.A few MediaWiki extensions can format CSV information: SimpleTable andTableData. Figure 1 shows the transclusion of CSV data with a modified ver-sion of the SimpleTable extension. The Brede Wiki uses the standard templatesystem for recording structured bibliographic data about the publication and toannotate the CSV information, see Figure 2.{{Metaanalysis csv begin}}{{Metaanalysis csv| title = Major Depressive Disorder Neuroimaging Database - Pituitary, total| topic1 = Pituitary| topic2 = Major depressive disorder| topic3 = MaND}}{{Metaanalysis csv| title = Obsessive-compulsive disorder Neuroimaging Database - Pituitary| topic1 = Pituitary| topic2 = Obsessive-compulsive disorder| topic3 = ObND}}{{Metaanalysis csv end}}Fig. 2. Template to annotate the CSV data anddefine the links to the meta-analysis.The bulk of the data cur-rently presented in the wikicomes from the large massmeta-analysis of volumetricstudies on major depressivedisorder reporting over 50separate meta-analyses for in-dividual brain regions [4].Further data comes frommass meta-analyses acrossmultiple brain regions onbipolar disorder [5] and first-episode schizophrenia [6], a meta-analysis on longi-tudinal development in schizophrenia [7] as well as data from individual originalstudies on obsessive-compulsive disorder.Apart from neuroimaging studies the Brede Wiki also records data frommeta-analyses from a few other studies outside neuroimaging [2], allowing us totest the generality of the framework. The data is distributed under ODbL.3 Web script and meta-analysisThe web script for meta-analysis reads the CSV information, identifies the re-quired columns for meta-analysis, performs the statistical computations andmakes meta-analytic plots— the so-called forest and funnel plots—in the SVGformat, see Figure 3. From either the title information or a PubMed identifierthe script generates back-links from the generated page to pages on the wiki.The script may also export the computed results as JSON or CSV. Furthermore,it may generate a small R script that sets up the data in variables and use themeta library for meta-analysis.The web script attempts to guess the separator used on the CSV page andalso tries to match the elements of the column header, e.g., the strings “controln”, “controls number”, “number of controls”, etc. match for number of con-trol subjects. With no matches the user needs to explicitly specify the relevantcolumns via URL parameters, which in turn a wiki template can setup.Standard meta-analysis computes an effect size from each result in a paperand computes a combined meta-analytic effect size and its confidence inter-val. Although the methodological development continues, there exist establishedstatistical analysis approaches for ordinary meta-analysis [2]. Our system im-plements computations on the standardized mean difference for continuous vari-ables and on the natural logarithm of the odds ratio for categorical variables withfixed and random effects methods using an inverse-weighted variance model, —following the approach in the Stata program. As an extra option we providemeta-analysis on the natural logarithm of the variance ratio [3], for comparisonof the standard deviations between two groups of subjects.4 ResultsFig. 3. Screenshot of web script showing the meta-analytic results with forest and funnel plots.We have added 124pages with CSV data,— most of which con-tain data suitable formeta-analysis. For in-dividual analyses thereading, computation anddownload finish withinseconds. With multiplecalls to the web scriptand JSON output an-other script can plotmultiple meta-analyticresults together as inFigure 4. Generatingsuch a plot takes severalminutes. For generatingthe page shown in Fig-ure 3 we need only theCSV data and the webscript, while the script that generated Figure 4 used information defined in tem-plates, CSV data and the web script with no further adaption of MediaWiki.5 DiscussionBy using MediaWiki in our present system we exploit the template facility tocapture structured information, and free-form wikitext for annotation and com-ment on the individual scientific papers, — as in semantic academic annotationwikis AcaWiki and WikiPapers. It is also possible to use the pages of the wikias a simple means to keep track of the status of the papers considered for themeta-analysis: potentially eligible, eligible, partially entered and fully entered.Why not Semantic MediaWiki? Semantic MediaWiki (SMW) may query textand numerical data, though has not had the ability to make complex computa-tions. The Semantic Result Formats extension includes average, sum, productand count result formats enabling simple computations of a series of numericalvalues, but insufficient for the kind of computations we require. The data formeta-analysis form a n-ary data record (mean, standard deviation, number ofsubjects, labels) so either individual SMW pages should store each data recordor we should invoke the n-ary functionality in Semantic Internal Objects SMWextension, SMW record or the recently-introduced subobject SMW functional-ity. We have not investigated whether these tools provide convenient means forrepresenting our data. The Brede Wiki can export its ontologies defined in Me-diaWiki template to SKOS. Our future research can consider RDFication of theCSV information through the SCOVO format [9].0.2 0.0 0.2 0.4 0.6 0.8Effect magnitude0.00.10.20.30.40.50.60.7UncertaintyLeft subgenual cortexRight orbitofrontal area Orbitofrontal areaWhite matterLeft hippocampusObsessive-compulsive disorderLeft lateral ventricleMajor Depressive DisorderLeft anterior cingulate gyrusIntelligence sex differenceDentifriceParkinson's diseaseLeft hippocampusLeft amygdalaRight hippocampusAmygdalaLeft amygdalaAnterior cingulate gyrusGrey matterRight hippocampusFig. 4. Results from mass meta-analyses shown in aL’Abbe´-like plot and constructed by calling the webscript multiple times. Each dot corresponds to a meta-analysis. Uncertainty as a function of effect size withsize of each dot determined by the number of subjects.The line indicates 0.05-significance.We wrote the webservice in Python,where Numpy makesvector computationavailable and Scipyprovides statisticalmethods, necessary forthe computation. Ina future PHP imple-mentation the scriptcould more closelyintegrate with the wikias either a MediaWikior a SMW extension.A wiki built fromstandard componentsprovides a inexpensivesolution with means tomanage meta-analyticdata in a collaborativeenvironment. The gen-eral framework allowsnot only the meta-analysis of neuroimaging-derived data but has the potentialfor managing and analyzing data from many other domains.References1. Nielsen, F.A˚.: Brede Wiki: Neuroscience data structured in a wiki. SemWiki (2009)129–1332. Hartung, J. et al.: Statistical Meta-Analysis with Applications. (2008)3. Shaffer, J.P.: Caution on the use of variance ratios: a comment. Review of Educa-tional Research 62(4) (1992) 429–4324. Kempton, M.J. et al.: Structural neuroimaging studies in major depressive dis-order: meta-analysis and comparison with bipolar disorder. Archives of GeneralPsychiatry 68(7) (2011) 675–6905. Kempton, M.J. et al.: Meta-analysis, database, and meta-regression of 98 structuralimaging studies in bipolar disorder. Arch. Gen. Psychiatry 65(9) (2008) 1017–10326. Steen, R.G. et al.: Brain volume in first-episode schizophrenia: systematic reviewand meta-analysis of magnetic resonance imaging studies. Brit. J. Psychiatry 188(2006) 510–5187. Kempton, M.J. et al.: Progressive lateral ventricular enlargement in schizophrenia:a meta-analysis of longitudinal MRI studies. Schiz. Res. 120(1–3) (2010) 54–528. Nielsen, F.A˚.: A fielded wiki for personality genetics. WikiSym (2010)9. Hausenblas, M. et al.: SCOVO: Using statistics on the web of data. ESWC (2009)708–72210. Elamin, M.B. et al.: Choice of data extraction tools for systematic reviews dependson resources and review complexity. J. Clin. Epidemiology 62(5) (2009) 506–510

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